Directory of Open Access Journals (Sweden)
Salvidio Sebastiano
2010-02-01
Full Text Available Abstract Background It has been suggested that Plethodontid salamanders are excellent candidates for indicating ecosystem health. However, detailed, long-term data sets of their populations are rare, limiting our understanding of the demographic processes underlying their population fluctuations. Here we present a demographic analysis based on a 1996 - 2008 data set on an underground population of Speleomantes strinatii (Aellen in NW Italy. We utilised a Bayesian state-space approach allowing us to parameterise a stage-structured Lefkovitch model. We used all the available population data from annual temporary removal experiments to provide us with the baseline data on the numbers of juveniles, subadults and adult males and females present at any given time. Results Sampling the posterior chains of the converged state-space model gives us the likelihood distributions of the state-specific demographic rates and the associated uncertainty of these estimates. Analysing the resulting parameterised Lefkovitch matrices shows that the population growth is very close to 1, and that at population equilibrium we expect half of the individuals present to be adults of reproductive age which is what we also observe in the data. Elasticity analysis shows that adult survival is the key determinant for population growth. Conclusion This analysis demonstrates how an understanding of population demography can be gained from structured population data even in a case where following marked individuals over their whole lifespan is not practical.
Bayesian Uncertainty Analyses Via Deterministic Model
Krzysztofowicz, R.
2001-05-01
Rational decision-making requires that the total uncertainty about a variate of interest (a predictand) be quantified in terms of a probability distribution, conditional on all available information and knowledge. Suppose the state-of-knowledge is embodied in a deterministic model, which is imperfect and outputs only an estimate of the predictand. Fundamentals are presented of three Bayesian approaches to producing a probability distribution of the predictand via any deterministic model. The Bayesian Processor of Output (BPO) quantifies the total uncertainty in terms of a posterior distribution, conditional on model output. The Bayesian Processor of Ensemble (BPE) quantifies the total uncertainty in terms of a posterior distribution, conditional on an ensemble of model output. The Bayesian Forecasting System (BFS) decomposes the total uncertainty into input uncertainty and model uncertainty, which are characterized independently and then integrated into a predictive distribution.
Small sample Bayesian analyses in assessment of weapon performance
Institute of Scientific and Technical Information of China (English)
无
2007-01-01
Abundant test data are required in assessment of weapon performance.When weapon test data are insufficient,Bayesian analyses in small sample circumstance should be considered and the test data should be provided by simulations.The several Bayesian approaches are discussed and some limitations are founded.An improvement is put forward after limitations of Bayesian approaches available are analyzed and t he improved approach is applied to assessment of some new weapon performance.
The application of Bayesian networks in natural hazard analyses
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K. Vogel
2013-10-01
Full Text Available In natural hazards we face several uncertainties due to our lack of knowledge and/or the intrinsic randomness of the underlying natural processes. Nevertheless, deterministic analysis approaches are still widely used in natural hazard assessments, with the pitfall of underestimating the hazard with potentially disastrous consequences. In this paper we show that the Bayesian network approach offers a flexible framework for capturing and expressing a broad range of different uncertainties as those encountered in natural hazard assessments. Although well studied in theory, the application of Bayesian networks on real-world data is often not straightforward and requires specific tailoring and adaption of existing algorithms. We demonstrate by way of three case studies (a ground motion model for a seismic hazard analysis, a flood damage assessment, and a landslide susceptibility study the applicability of Bayesian networks across different domains showcasing various properties and benefits of the Bayesian network framework. We offer suggestions as how to tackle practical problems arising along the way, mainly concentrating on the handling of continuous variables, missing observations, and the interaction of both. We stress that our networks are completely data-driven, although prior domain knowledge can be included if desired.
Analysing uncertainties: Towards comparing Bayesian and interval probabilities'
Blockley, David
2013-05-01
Two assumptions, commonly made in risk and reliability studies, have a long history. The first is that uncertainty is either aleatoric or epistemic. The second is that standard probability theory is sufficient to express uncertainty. The purposes of this paper are to provide a conceptual analysis of uncertainty and to compare Bayesian approaches with interval approaches with an example relevant to research on climate change. The analysis reveals that the categorisation of uncertainty as either aleatoric or epistemic is unsatisfactory for practical decision making. It is argued that uncertainty emerges from three conceptually distinctive and orthogonal attributes FIR i.e., fuzziness, incompleteness (epistemic) and randomness (aleatory). Characterisations of uncertainty, such as ambiguity, dubiety and conflict, are complex mixes of interactions in an FIR space. To manage future risks in complex systems it will be important to recognise the extent to which we 'don't know' about possible unintended and unwanted consequences or unknown-unknowns. In this way we may be more alert to unexpected hazards. The Bayesian approach is compared with an interval probability approach to show one way in which conflict due to incomplete information can be managed.
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Tsukasa Mori
2012-02-01
The rapid induction of a defensive morphology by a prey species in face of a predation risk is an intriguing in ecological context; however, the physiological mechanisms that underlie this phenotypic plasticity remain uncertain. Here we investigated the phenotypic changes shown by Rana pirica tadpoles in response to a predation threat by larvae of the salamander Hynobius retardatus. One such response is the bulgy morph phenotype, a relatively rapid swelling in size by the tadpoles that begins within 4 days and reaches a maximum at 8 to 10 days. We found that although the total volume of bodily fluid increased significantly (P<0.01 in bulgy morph tadpoles, osmotic pressure was maintained at the same level as control tadpoles by a significant increase (P<0.01 in Na and Cl ion concentrations. In our previous report, we identified a novel frog gene named pirica that affects the waterproofing of the skin membrane in tadpoles. Our results support the hypothesis that predator-induced expression of pirica on the skin membrane causes retention of absorbed water. Midline sections of bulgy morph tadpoles showed the presence of swollen connective tissue beneath the skin that was sparsely composed of cells containing hyaluronic acid. Mass spectrographic (LC-MS/MS analysis identified histone H3 and 14-3-3 zeta as the most abundant constituents in the liquid aspirated from the connective tissue of bulgy tadpoles. Immunohistochemistry using antibodies against these proteins showed the presence of non-chromatin associated histone H3 in the swollen connective tissue. Histones and 14-3-3 proteins are also involved in antimicrobial activity and secretion of antibacterial proteins, respectively. Bulgy tadpoles have a larger surface area than controls, and their skin often has bite wounds inflicted by the larval salamanders. Thus, formation of the bulgy morph may also require and be supported by activation of innate immune systems.
Bayesian inference analyses of the polygenic architecture of rheumatoid arthritis
Stahl, Eli A.; Wegmann, Daniel; Trynka, Gosia; Gutierrez-Achury, Javier; Do, Ron; Voight, Benjamin F.; Kraft, Peter; Chen, Robert; Kallberg, Henrik J.; Kurreeman, Fina A. S.; Kathiresan, Sekar; Wijmenga, Cisca; Gregersen, Peter K.; Alfredsson, Lars; Siminovitch, Katherine A.; Worthington, Jane; de Bakker, Paul I. W.; Raychaudhuri, Soumya; Plenge, Robert M.
2012-01-01
The genetic architectures of common, complex diseases are largely uncharacterized. We modeled the genetic architecture underlying genome-wide association study (GWAS) data for rheumatoid arthritis and developed a new method using polygenic risk-score analyses to infer the total liability-scale varia
Kadarmideen, H.N.; Janss, L.L.G.
2005-01-01
Bayesian segregation analyses were used to investigate the mode of inheritance of osteochondral lesions (osteochondrosis, OC) in pigs. Data consisted of 1163 animals with OC and their pedigrees included 2891 animals. Mixed-inheritance threshold models (MITM) and several variants of MITM, in conjunct
A space-time multivariate Bayesian model to analyse road traffic accidents by severity
Boulieri, A; Liverani, S; Hoogh, K. de; Blangiardo, M.
2016-01-01
The paper investigates the dependences between levels of severity of road traffic accidents, accounting at the same time for spatial and temporal correlations. The study analyses road traffic accidents data at ward level in England over the period 2005–2013. We include in our model multivariate spatially structured and unstructured effects to capture the dependences between severities, within a Bayesian hierarchical formulation. We also include a temporal component to capture the time effects...
Siwek, M; Finocchiaro, R; Curik, I; Portolano, B
2011-02-01
Genetic structure and relationship amongst the main goat populations in Sicily (Girgentana, Derivata di Siria, Maltese and Messinese) were analysed using information from 19 microsatellite markers genotyped on 173 individuals. A posterior Bayesian approach implemented in the program STRUCTURE revealed a hierarchical structure with two clusters at the first level (Girgentana vs. Messinese, Derivata di Siria and Maltese), explaining 4.8% of variation (amovaФ(ST) estimate). Seven clusters nested within these first two clusters (further differentiations of Girgentana, Derivata di Siria and Maltese), explaining 8.5% of variation (amovaФ(SC) estimate). The analyses and methods applied in this study indicate their power to detect subtle population structure.
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Velimir Gayevskiy
Full Text Available Bayesian inference methods are extensively used to detect the presence of population structure given genetic data. The primary output of software implementing these methods are ancestry profiles of sampled individuals. While these profiles robustly partition the data into subgroups, currently there is no objective method to determine whether the fixed factor of interest (e.g. geographic origin correlates with inferred subgroups or not, and if so, which populations are driving this correlation. We present ObStruct, a novel tool to objectively analyse the nature of structure revealed in Bayesian ancestry profiles using established statistical methods. ObStruct evaluates the extent of structural similarity between sampled and inferred populations, tests the significance of population differentiation, provides information on the contribution of sampled and inferred populations to the observed structure and crucially determines whether the predetermined factor of interest correlates with inferred population structure. Analyses of simulated and experimental data highlight ObStruct's ability to objectively assess the nature of structure in populations. We show the method is capable of capturing an increase in the level of structure with increasing time since divergence between simulated populations. Further, we applied the method to a highly structured dataset of 1,484 humans from seven continents and a less structured dataset of 179 Saccharomyces cerevisiae from three regions in New Zealand. Our results show that ObStruct provides an objective metric to classify the degree, drivers and significance of inferred structure, as well as providing novel insights into the relationships between sampled populations, and adds a final step to the pipeline for population structure analyses.
DEFF Research Database (Denmark)
Heller, Rasmus; Lorenzen, Eline D.; Okello, J.B.A;
2008-01-01
pandemic in the late 1800s, but little is known about the earlier demographic history of the species. We analysed genetic variation at 17 microsatellite loci and a 302-bp fragment of the mitochondrial DNA control region to infer past demographic changes in buffalo populations from East Africa. Two Bayesian...
Odbert, Henry; Hincks, Thea; Aspinall, Willy
2015-04-01
Volcanic hazard assessments must combine information about the physical processes of hazardous phenomena with observations that indicate the current state of a volcano. Incorporating both these lines of evidence can inform our belief about the likelihood (probability) and consequences (impact) of possible hazardous scenarios, forming a basis for formal quantitative hazard assessment. However, such evidence is often uncertain, indirect or incomplete. Approaches to volcano monitoring have advanced substantially in recent decades, increasing the variety and resolution of multi-parameter timeseries data recorded at volcanoes. Interpreting these multiple strands of parallel, partial evidence thus becomes increasingly complex. In practice, interpreting many timeseries requires an individual to be familiar with the idiosyncrasies of the volcano, monitoring techniques, configuration of recording instruments, observations from other datasets, and so on. In making such interpretations, an individual must consider how different volcanic processes may manifest as measureable observations, and then infer from the available data what can or cannot be deduced about those processes. We examine how parts of this process may be synthesised algorithmically using Bayesian inference. Bayesian Belief Networks (BBNs) use probability theory to treat and evaluate uncertainties in a rational and auditable scientific manner, but only to the extent warranted by the strength of the available evidence. The concept is a suitable framework for marshalling multiple strands of evidence (e.g. observations, model results and interpretations) and their associated uncertainties in a methodical manner. BBNs are usually implemented in graphical form and could be developed as a tool for near real-time, ongoing use in a volcano observatory, for example. We explore the application of BBNs in analysing volcanic data from the long-lived eruption at Soufriere Hills Volcano, Montserrat. We show how our method
Evolution of gigantism in amphiumid salamanders.
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Ronald M Bonett
Full Text Available The Amphiumidae contains three species of elongate, permanently aquatic salamanders with four diminutive limbs that append one, two, or three toes. Two of the species, Amphiuma means and A. tridactylum, are among the largest salamanders in the world, reaching lengths of more than one meter, whereas the third species (A. pholeter, extinct amphiumids, and closely related salamander families are relatively small. Amphiuma means and A. tridactylum are widespread species and live in a wide range of lowland aquatic habitats on the Coastal Plain of the southeastern United States, whereas A. pholeter is restricted to very specialized organic muck habitats and is syntopic with A. means. Here we present analyses of sequences of mitochondrial and nuclear loci from across the distribution of the three taxa to assess lineage diversity, relationships, and relative timing of divergence in amphiumid salamanders. In addition we analyze the evolution of gigantism in the clade. Our analyses indicate three lineages that have diverged since the late Miocene, that correspond to the three currently recognized species, but the two gigantic species are not each other's closest relatives. Given that the most closely related salamander families and fossil amphiumids from the Upper Cretaceous and Paleocene are relatively small, our results suggest at least two extreme changes in body size within the Amphuimidae. Gigantic body size either evolved once as the ancestral condition of modern amphiumas, with a subsequent strong size reduction in A. pholeter, or gigantism independently evolved twice in the modern species, A. means and A. tridactylum. These patterns are concordant with differences in habitat breadth and range size among lineages, and have implications for reproductive isolation and diversification of amphiumid salamanders.
Chen, Cong; Zhang, Guohui; Tarefder, Rafiqul; Ma, Jianming; Wei, Heng; Guan, Hongzhi
2015-07-01
Rear-end crash is one of the most common types of traffic crashes in the U.S. A good understanding of its characteristics and contributing factors is of practical importance. Previously, both multinomial Logit models and Bayesian network methods have been used in crash modeling and analysis, respectively, although each of them has its own application restrictions and limitations. In this study, a hybrid approach is developed to combine multinomial logit models and Bayesian network methods for comprehensively analyzing driver injury severities in rear-end crashes based on state-wide crash data collected in New Mexico from 2010 to 2011. A multinomial logit model is developed to investigate and identify significant contributing factors for rear-end crash driver injury severities classified into three categories: no injury, injury, and fatality. Then, the identified significant factors are utilized to establish a Bayesian network to explicitly formulate statistical associations between injury severity outcomes and explanatory attributes, including driver behavior, demographic features, vehicle factors, geometric and environmental characteristics, etc. The test results demonstrate that the proposed hybrid approach performs reasonably well. The Bayesian network reference analyses indicate that the factors including truck-involvement, inferior lighting conditions, windy weather conditions, the number of vehicles involved, etc. could significantly increase driver injury severities in rear-end crashes. The developed methodology and estimation results provide insights for developing effective countermeasures to reduce rear-end crash injury severities and improve traffic system safety performance. PMID:25888994
Energy Technology Data Exchange (ETDEWEB)
Macey, J. Robert
2005-01-19
A new parsimony analysis of 27 complete mitochondrial genomic sequences is conducted to investigate the phylogenetic relationships of plethodontid salamanders. This analysis focuses on the amount of character conflict between phylogenetic trees recovered from newly conducted parsimony searches and the Bayesian and maximum likelihood topology reported by Mueller et al. (2004, PNAS, 101, 13820-13825). Strong support for Hemidactylium as the sister taxon to all other plethodontids is recovered from parsimony analyses. Plotting area relationships on the most parsimonious phylogenetic tree suggests that eastern North America is the origin of the family Plethodontidae supporting the ''Out of Appalachia'' hypothesis. A new taxonomy that recognizes clades recovered from phylogenetic analyses is proposed.
Hellbender genome sequences shed light on genomic expansion at the base of crown salamanders.
Sun, Cheng; Mueller, Rachel Lockridge
2014-07-01
Among animals, genome sizes range from 20 Mb to 130 Gb, with 380-fold variation across vertebrates. Most of the largest vertebrate genomes are found in salamanders, an amphibian clade of 660 species. Thus, salamanders are an important system for studying causes and consequences of genomic gigantism. Previously, we showed that plethodontid salamander genomes accumulate higher levels of long terminal repeat (LTR) retrotransposons than do other vertebrates, although the evolutionary origins of such sequences remained unexplored. We also showed that some salamanders in the family Plethodontidae have relatively slow rates of DNA loss through small insertions and deletions. Here, we present new data from Cryptobranchus alleganiensis, the hellbender. Cryptobranchus and Plethodontidae span the basal phylogenetic split within salamanders; thus, analyses incorporating these taxa can shed light on the genome of the ancestral crown salamander lineage, which underwent expansion. We show that high levels of LTR retrotransposons likely characterize all crown salamanders, suggesting that disproportionate expansion of this transposable element (TE) class contributed to genomic expansion. Phylogenetic and age distribution analyses of salamander LTR retrotransposons indicate that salamanders' high TE levels reflect persistence and diversification of ancestral TEs rather than horizontal transfer events. Finally, we show that relatively slow DNA loss rates through small indels likely characterize all crown salamanders, suggesting that a decreased DNA loss rate contributed to genomic expansion at the clade's base. Our identification of shared genomic features across phylogenetically distant salamanders is a first step toward identifying the evolutionary processes underlying accumulation and persistence of high levels of repetitive sequence in salamander genomes. PMID:25115007
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Karacaören Burak
2011-05-01
Full Text Available Abstract Background It has been shown that if genetic relationships among individuals are not taken into account for genome wide association studies, this may lead to false positives. To address this problem, we used Genome-wide Rapid Association using Mixed Model and Regression and principal component stratification analyses. To account for linkage disequilibrium among the significant markers, principal components loadings obtained from top markers can be included as covariates. Estimation of Bayesian networks may also be useful to investigate linkage disequilibrium among SNPs and their relation with environmental variables. For the quantitative trait we first estimated residuals while taking polygenic effects into account. We then used a single SNP approach to detect the most significant SNPs based on the residuals and applied principal component regression to take linkage disequilibrium among these SNPs into account. For the categorical trait we used principal component stratification methodology to account for background effects. For correction of linkage disequilibrium we used principal component logit regression. Bayesian networks were estimated to investigate relationship among SNPs. Results Using the Genome-wide Rapid Association using Mixed Model and Regression and principal component stratification approach we detected around 100 significant SNPs for the quantitative trait (p Conclusions GRAMMAR could efficiently incorporate the information regarding random genetic effects. Principal component stratification should be cautiously used with stringent multiple hypothesis testing correction to correct for ancestral stratification and association analyses for binary traits when there are systematic genetic effects such as half sib family structures. Bayesian networks are useful to investigate relationships among SNPs and environmental variables.
Reduced genetic variation in the Japanese giant salamander, Andrias japonicus (Amphibia: Caudata).
Matsui, Masafumi; Tominaga, Atsushi; Liu, Wan-zhao; Tanaka-Ueno, Tomoko
2008-10-01
The phylogenetic relationships among 46 samples from 27 populations of the Japanese giant salamander, Andriasjaponicus and its congener, A. davidianus from China was investigated, using 3664 bp sequences of the mitochondrial genes NADH1, NADH3, cyt b and CR, partial NADH6 and intervening genes. In phylogenetic trees constructed by MP, ML, and Bayesian methods, the family Cryptobranchidae and the genus Andrias both form monophyletic groups. Japanese A. japonicus and Chinese A. davidianus are sister taxa and can be regarded as separate species despite a small degree of genetic differentiation. Andriasjaponicus is divided into central and western clades, but the phylogenetic relationships within the latter clade are unresolved. As previously reported from allozyme analyses, A. japonicus exhibits little genetic differentiation, in strong contrast to salamanders of the genus Hynobius with which their distributions overlap. This reduced genetic variability in A. japonicus is attributable to a unique mating system of polygyny, delayed sexual maturity, notable longevity, life in a stable aquatic environment, and gigantism, as well as bottleneck effects following habitat fragmentation and extinction of local populations during Quaternary glaciations. The species is thus susceptible to extinction by potential environmental fluctuations, and requires extensive conservation measures. PMID:18723097
Predictability of Regional Climate: A Bayesian Approach to Analysing a WRF Model Ensemble
Bruyere, C. L.; Mesquita, M. D. S.; Paimazumder, D.
2013-12-01
This study investigates aspects of climate predictability with a focus on climatic variables and different characteristics of extremes over nine North American climatic regions and two selected Atlantic sectors. An ensemble of state-of-the-art Weather Research and Forecasting Model (WRF) simulations is used for the analysis. The ensemble is comprised of a combination of various physics schemes, initial conditions, domain sizes, boundary conditions and breeding techniques. The main objectives of this research are: 1) to increase our understanding of the ability of WRF to capture regional climate information - both at the individual and collective ensemble members, 2) to investigate the role of different members and their synergy in reproducing regional climate 3) to estimate the associated uncertainty. In this study, we propose a Bayesian framework to study the predictability of extremes and associated uncertainties in order to provide a wealth of knowledge about WRF reliability and provide further clarity and understanding of the sensitivities and optimal combinations. The choice of the Bayesian model, as opposed to standard methods, is made because: a) this method has a mean square error that is less than standard statistics, which makes it a more robust method; b) it allows for the use of small sample sizes, which are typical in high-resolution modeling; c) it provides a probabilistic view of uncertainty, which is useful when making decisions concerning ensemble members.
Data congruence, paedomorphosis and salamanders
Directory of Open Access Journals (Sweden)
Struck Torsten H
2007-10-01
Full Text Available Abstract Background The retention of ancestral juvenile characters by adult stages of descendants is called paedomorphosis. However, this process can mislead phylogenetic analyses based on morphological data, even in combination with molecular data, because the assessment if a character is primary absent or secondary lost is difficult. Thus, the detection of incongruence between morphological and molecular data is necessary to investigate the reliability of simultaneous analyses. Different methods have been proposed to detect data congruence or incongruence. Five of them (PABA, PBS, NDI, LILD, DRI are used herein to assess incongruence between morphological and molecular data in a case study addressing salamander phylogeny, which comprises several supposedly paedomorphic taxa. Therefore, previously published data sets were compiled herein. Furthermore, two strategies ameliorating effects of paedomorphosis on phylogenetic studies were tested herein using a statistical rigor. Additionally, efficiency of the different methods to assess incongruence was analyzed using this empirical data set. Finally, a test statistic is presented for all these methods except DRI. Results The addition of morphological data to molecular data results in both different positions of three of the four paedomorphic taxa and strong incongruence, but treating the morphological data using different strategies ameliorating the negative impact of paedomorphosis revokes these changes and minimizes the conflict. Of these strategies the strategy to just exclude paedomorphic character traits seem to be most beneficial. Of the three molecular partitions analyzed herein the RAG1 partition seems to be the most suitable to resolve deep salamander phylogeny. The rRNA and mtDNA partition are either too conserved or too variable, respectively. Of the different methods to detect incongruence, the NDI and PABA approaches are more conservative in the indication of incongruence than LILD and
Jomelli, Vincent; Pavlova, Irina; Eckert, Nicolas; Grancher, Delphine; Brunstein, Daniel
2015-12-01
How can debris flow occurrences be modelled at regional scale and take both environmental and climatic conditions into account? And, of the two, which has the most influence on debris flow activity? In this paper, we try to answer these questions with an innovative Bayesian hierarchical probabilistic model that simultaneously accounts for how debris flows respond to environmental and climatic variables. In it, full decomposition of space and time effects in occurrence probabilities is assumed, revealing an environmental and a climatic trend shared by all years/catchments, respectively, clearly distinguished from residual "random" effects. The resulting regional and annual occurrence probabilities evaluated as functions of the covariates make it possible to weight the respective contribution of the different terms and, more generally, to check the model performances at different spatio-temporal scales. After suitable validation, the model can be used to make predictions at undocumented sites and could be used in further studies for predictions under future climate conditions. Also, the Bayesian paradigm easily copes with missing data, thus making it possible to account for events that may have been missed during surveys. As a case study, we extract 124 debris flow event triggered between 1970 and 2005 in 27 catchments located in the French Alps from the French national natural hazard survey and model their variability of occurrence considering environmental and climatic predictors at the same time. We document the environmental characteristics of each debris flow catchment (morphometry, lithology, land cover, and the presence of permafrost). We also compute 15 climate variables including mean temperature and precipitation between May and October and the number of rainy days with daily cumulative rainfall greater than 10/15/20/25/30/40 mm day- 1. Application of our model shows that the combination of environmental and climatic predictors explained 77% of the overall
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Harlow Timothy J
2005-01-01
Full Text Available Abstract Background Bayesian phylogenetic inference holds promise as an alternative to maximum likelihood, particularly for large molecular-sequence data sets. We have investigated the performance of Bayesian inference with empirical and simulated protein-sequence data under conditions of relative branch-length differences and model violation. Results With empirical protein-sequence data, Bayesian posterior probabilities provide more-generous estimates of subtree reliability than does the nonparametric bootstrap combined with maximum likelihood inference, reaching 100% posterior probability at bootstrap proportions around 80%. With simulated 7-taxon protein-sequence datasets, Bayesian posterior probabilities are somewhat more generous than bootstrap proportions, but do not saturate. Compared with likelihood, Bayesian phylogenetic inference can be as or more robust to relative branch-length differences for datasets of this size, particularly when among-sites rate variation is modeled using a gamma distribution. When the (known correct model was used to infer trees, Bayesian inference recovered the (known correct tree in 100% of instances in which one or two branches were up to 20-fold longer than the others. At ratios more extreme than 20-fold, topological accuracy of reconstruction degraded only slowly when only one branch was of relatively greater length, but more rapidly when there were two such branches. Under an incorrect model of sequence change, inaccurate trees were sometimes observed at less extreme branch-length ratios, and (particularly for trees with single long branches such trees tended to be more inaccurate. The effect of model violation on accuracy of reconstruction for trees with two long branches was more variable, but gamma-corrected Bayesian inference nonetheless yielded more-accurate trees than did either maximum likelihood or uncorrected Bayesian inference across the range of conditions we examined. Assuming an exponential
Energy Technology Data Exchange (ETDEWEB)
Mueller, Rachel Lockridge; Macey, J. Robert; Jaekel, Martin; Wake, David B.; Boore, Jeffrey L.
2004-08-01
The evolutionary history of the largest salamander family (Plethodontidae) is characterized by extreme morphological homoplasy. Analysis of the mechanisms generating such homoplasy requires an independent, molecular phylogeny. To this end, we sequenced 24 complete mitochondrial genomes (22 plethodontids and two outgroup taxa), added data for three species from GenBank, and performed partitioned and unpartitioned Bayesian, ML, and MP phylogenetic analyses. We explored four dataset partitioning strategies to account for evolutionary process heterogeneity among genes and codon positions, all of which yielded increased model likelihoods and decreased numbers of supported nodes in the topologies (PP > 0.95) relative to the unpartitioned analysis. Our phylogenetic analyses yielded congruent trees that contrast with the traditional morphology-based taxonomy; the monophyly of three out of four major groups is rejected. Reanalysis of current hypotheses in light of these new evolutionary relationships suggests that (1) a larval life history stage re-evolved from a direct-developing ancestor multiple times, (2) there is no phylogenetic support for the ''Out of Appalachia'' hypothesis of plethodontid origins, and (3) novel scenarios must be reconstructed for the convergent evolution of projectile tongues, reduction in toe number, and specialization for defensive tail loss. Some of these novel scenarios imply morphological transformation series that proceed in the opposite direction than was previously thought. In addition, they suggest surprising evolutionary lability in traits previously interpreted to be conservative.
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Le Roy Pascale
2003-07-01
Full Text Available Abstract Segregation analyses were performed using both maximum likelihood – via a Quasi Newton algorithm – (ML-QN and Bayesian – via Gibbs sampling – (Bayesian-GS approaches in the Chinese European Tiameslan pig line. Major genes were searched for average ultrasonic backfat thickness (ABT, carcass fat (X2 and X4 and lean (X5 depths, days from 20 to 100 kg (D20100, Napole technological yield (NTY, number of false (FTN and good (GTN teats, as well as total teat number (TTN. The discrete nature of FTN was additionally considered using a threshold model under ML methodology. The results obtained with both methods consistently suggested the presence of major genes affecting ABT, X2, NTY, GTN and FTN. Major genes were also suggested for X4 and X5 using ML-QN, but not the Bayesian-GS, approach. The major gene affecting FTN was confirmed using the threshold model. Genetic correlations as well as gene effect and genotype frequency estimates suggested the presence of four different major genes. The first gene would affect fatness traits (ABT, X2 and X4, the second one a leanness trait (X5, the third one NTY and the last one GTN and FTN. Genotype frequencies of breeding animals and their evolution over time were consistent with the selection performed in the Tiameslan line.
Directory of Open Access Journals (Sweden)
Ben Wielstra
Full Text Available The phylogenetic relationships for rapid species radiations are difficult to disentangle. Here we study one such case, namely the genus Triturus, which is composed of the marbled and crested newts. We analyze data for 38 genetic markers, positioned in 3-prime untranslated regions of protein-coding genes, obtained with 454 sequencing. Our dataset includes twenty Triturus newts and represents all nine species. Bayesian analysis of population structure allocates all individuals to their respective species. The branching patterns obtained by data concatenation, Bayesian concordance analysis and coalescent-based estimations of the species tree differ from one another. The data concatenation based species tree shows high branch support but branching order is considerably affected by allele choice in the case of heterozygotes in the concatenation process. Bayesian concordance analysis expresses the conflict between individual gene trees for part of the Triturus species tree as low concordance factors. The coalescent-based species tree is relatively similar to a previously published species tree based upon morphology and full mtDNA and any conflicting internal branches are not highly supported. Our findings reflect high gene tree discordance due to incomplete lineage sorting (possibly aggravated by hybridization in combination with low information content of the markers employed (as can be expected for relatively recent species radiations. This case study highlights the complexity of resolving rapid radiations and we acknowledge that to convincingly resolve the Triturus species tree even more genes will have to be consulted.
Wafer, Lucas; Kloczewiak, Marek; Luo, Yin
2016-07-01
Analytical ultracentrifugation-sedimentation velocity (AUC-SV) is often used to quantify high molar mass species (HMMS) present in biopharmaceuticals. Although these species are often present in trace quantities, they have received significant attention due to their potential immunogenicity. Commonly, AUC-SV data is analyzed as a diffusion-corrected, sedimentation coefficient distribution, or c(s), using SEDFIT to numerically solve Lamm-type equations. SEDFIT also utilizes maximum entropy or Tikhonov-Phillips regularization to further allow the user to determine relevant sample information, including the number of species present, their sedimentation coefficients, and their relative abundance. However, this methodology has several, often unstated, limitations, which may impact the final analysis of protein therapeutics. These include regularization-specific effects, artificial "ripple peaks," and spurious shifts in the sedimentation coefficients. In this investigation, we experimentally verified that an explicit Bayesian approach, as implemented in SEDFIT, can largely correct for these effects. Clear guidelines on how to implement this technique and interpret the resulting data, especially for samples containing micro-heterogeneity (e.g., differential glycosylation), are also provided. In addition, we demonstrated how the Bayesian approach can be combined with F statistics to draw more accurate conclusions and rigorously exclude artifactual peaks. Numerous examples with an antibody and an antibody-drug conjugate were used to illustrate the strengths and drawbacks of each technique.
Energy Technology Data Exchange (ETDEWEB)
Vinikour, W. S.; LaGory, K. E.; Adduci, J. J.; Environmental Science Division
2006-10-20
The purpose of this conservation assessment is to summarize existing knowledge regarding the biology and ecology of the Siskiyou Mountains salamander and Scott Bar salamander, identify threats to the two species, and identify conservation considerations to aid federal management for persistence of the species. The conservation assessment will serve as the basis for a conservation strategy for the species.
Loudon, Andrew H; Venkataraman, Arvind; Van Treuren, William; Woodhams, Douglas C; Parfrey, Laura Wegener; McKenzie, Valerie J; Knight, Rob; Schmidt, Thomas M; Harris, Reid N
2016-01-01
Skin bacterial communities can protect amphibians from a fungal pathogen; however, little is known about how these communities are maintained. We used a neutral model of community ecology to identify bacteria that are maintained on salamanders by selection or by dispersal from a bacterial reservoir (soil) and ecological drift. We found that 75% (9/12) of bacteria that were consistent with positive selection, extinction) rates of bacteria on salamanders in both treatments. Loss was strongly related to bacterial richness, suggesting competition is important for structuring the community. Bacteria closely related to antifungal isolates were more likely to persist on salamanders with or without a bacterial reservoir, suggesting they had a competitive advantage. Furthermore, over-represented and under-represented operational taxonomic units (OTUs) had similar persistence on salamanders when a bacterial reservoir was present. However, under-represented OTUs were less likely to persist in the absence of a bacterial reservoir, suggesting that the over-represented and under-represented bacteria were selected against or for on salamanders through time. Our findings from the neutral model, migration and persistence analyses show that bacteria that exhibit a high similarity to antifungal isolates persist on salamanders, which likely protect hosts against pathogens and improve fitness. This research is one of the first to apply ecological theory to investigate assembly of host associated-bacterial communities, which can provide insights for probiotic bioaugmentation as a conservation strategy against disease. PMID:27014249
Salamander occupancy in headwater stream networks
Grant, E.H.C.; Green, L.E.; Lowe, W.H.
2009-01-01
1. Stream ecosystems exhibit a highly consistent dendritic geometry in which linear habitat units intersect to create a hierarchical network of connected branches. 2. Ecological and life history traits of species living in streams, such as the potential for overland movement, may interact with this architecture to shape patterns of occupancy and response to disturbance. Specifically, large-scale habitat alteration that fragments stream networks and reduces connectivity may reduce the probability a stream is occupied by sensitive species, such as stream salamanders. 3. We collected habitat occupancy data on four species of stream salamanders in first-order (i.e. headwater) streams in undeveloped and urbanised regions of the eastern U.S.A. We then used an information-theoretic approach to test alternative models of salamander occupancy based on a priori predictions of the effects of network configuration, region and salamander life history. 4. Across all four species, we found that streams connected to other first-order streams had higher occupancy than those flowing directly into larger streams and rivers. For three of the four species, occupancy was lower in the urbanised region than in the undeveloped region. 5. These results demonstrate that the spatial configuration of stream networks within protected areas affects the occurrences of stream salamander species. We strongly encourage preservation of network connections between first-order streams in conservation planning and management decisions that may affect stream species.
Invasive Asian Earthworms Negatively Impact Keystone Terrestrial Salamanders.
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Julie L Ziemba
Full Text Available Asian pheretimoid earthworms (e.g. Amynthas and Metaphire spp. are invading North American forests and consuming the vital detrital layer that forest floor biota [including the keystone species Plethodon cinereus (Eastern Red-backed Salamander], rely on for protection, food, and habitat. Plethodon cinereus population declines have been associated with leaf litter loss following the invasion of several exotic earthworm species, but there have been few studies on the specific interactions between pheretimoid earthworms and P. cinereus. Since some species of large and active pheretimoids spatially overlap with salamanders beneath natural cover objects and in detritus, they may distinctively compound the negative consequences of earthworm-mediated resource degradation by physically disturbing important salamander activities (foraging, mating, and egg brooding. We predicted that earthworms would exclude salamanders from high quality microhabitat, reduce foraging efficiency, and negatively affect salamander fitness. In laboratory trials, salamanders used lower quality microhabitat and consumed fewer flies in the presence of earthworms. In a natural field experiment, conducted on salamander populations from "non-invaded" and "pheretimoid invaded" sites in Ohio, salamanders and earthworms shared cover objects ~60% less than expected. Earthworm abundance was negatively associated with juvenile and male salamander abundance, but had no relationship with female salamander abundance. There was no effect of pheretimoid invasion on salamander body condition. Juvenile and non-resident male salamanders do not hold stable territories centered beneath cover objects such as rocks or logs, which results in reduced access to prey, greater risk of desiccation, and dispersal pressure. Habitat degradation and physical exclusion of salamanders from cover objects may hinder juvenile and male salamander performance, ultimately reducing recruitment and salamander abundance
Invasive Asian Earthworms Negatively Impact Keystone Terrestrial Salamanders.
Ziemba, Julie L; Hickerson, Cari-Ann M; Anthony, Carl D
2016-01-01
Asian pheretimoid earthworms (e.g. Amynthas and Metaphire spp.) are invading North American forests and consuming the vital detrital layer that forest floor biota [including the keystone species Plethodon cinereus (Eastern Red-backed Salamander)], rely on for protection, food, and habitat. Plethodon cinereus population declines have been associated with leaf litter loss following the invasion of several exotic earthworm species, but there have been few studies on the specific interactions between pheretimoid earthworms and P. cinereus. Since some species of large and active pheretimoids spatially overlap with salamanders beneath natural cover objects and in detritus, they may distinctively compound the negative consequences of earthworm-mediated resource degradation by physically disturbing important salamander activities (foraging, mating, and egg brooding). We predicted that earthworms would exclude salamanders from high quality microhabitat, reduce foraging efficiency, and negatively affect salamander fitness. In laboratory trials, salamanders used lower quality microhabitat and consumed fewer flies in the presence of earthworms. In a natural field experiment, conducted on salamander populations from "non-invaded" and "pheretimoid invaded" sites in Ohio, salamanders and earthworms shared cover objects ~60% less than expected. Earthworm abundance was negatively associated with juvenile and male salamander abundance, but had no relationship with female salamander abundance. There was no effect of pheretimoid invasion on salamander body condition. Juvenile and non-resident male salamanders do not hold stable territories centered beneath cover objects such as rocks or logs, which results in reduced access to prey, greater risk of desiccation, and dispersal pressure. Habitat degradation and physical exclusion of salamanders from cover objects may hinder juvenile and male salamander performance, ultimately reducing recruitment and salamander abundance following Asian
Effects of timber harvests and silvicultural edges on terrestrial salamanders.
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Jami E MacNeil
Full Text Available Balancing timber production and conservation in forest management requires an understanding of how timber harvests affect wildlife species. Terrestrial salamanders are useful indicators of mature forest ecosystem health due to their importance to ecosystem processes and sensitivity to environmental change. However, the effects of timber harvests on salamanders, though often researched, are still not well understood. To further this understanding, we used artificial cover objects to monitor the relative abundance of terrestrial salamanders for two seasons (fall and spring pre-harvest and five seasons post-harvest in six forest management treatments, and for three seasons post-harvest across the edge gradients of six recent clearcuts. In total, we recorded 19,048 encounters representing nine species of salamanders. We observed declines in mean encounters of eastern red-backed salamanders (Plethodon cinereus and northern slimy salamanders (P. glutinosus from pre- to post-harvest in group selection cuts and in clearcuts. However, we found no evidence of salamander declines at shelterwoods and forested sites adjacent to harvests. Edge effects induced by recent clearcuts influenced salamanders for approximately 20 m into the forest, but edge influence varied by slope orientation. Temperature, soil moisture, and canopy cover were all correlated with salamander counts. Our results suggest silvicultural techniques that remove the forest canopy negatively affect salamander relative abundance on the local scale during the years immediately following harvest, and that the depth of edge influence of clearcuts on terrestrial salamanders is relatively shallow (<20 m. Small harvests (<4 ha and techniques that leave the forest canopy intact may be compatible with maintaining terrestrial salamander populations across a forested landscape. Our results demonstrate the importance of examining species-specific responses and monitoring salamanders across multiple
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Yann Reynaud
Full Text Available Tuberculosis (TB remains broadly present in the Americas despite intense global efforts for its control and elimination. Starting from a large dataset comprising spoligotyping (n = 21183 isolates and 12-loci MIRU-VNTRs data (n = 4022 isolates from a total of 31 countries of the Americas (data extracted from the SITVIT2 database, this study aimed to get an overview of lineages circulating in the Americas. A total of 17119 (80.8% strains belonged to the Euro-American lineage 4, among which the most predominant genotypic family belonged to the Latin American and Mediterranean (LAM lineage (n = 6386, 30.1% of strains. By combining classical phylogenetic analyses and Bayesian approaches, this study revealed for the first time a clear genetic structuration of LAM9 sublineage into two subpopulations named LAM9C1 and LAM9C2, with distinct genetic characteristics. LAM9C1 was predominant in Chile, Colombia and USA, while LAM9C2 was predominant in Brazil, Dominican Republic, Guadeloupe and French Guiana. Globally, LAM9C2 was characterized by higher allelic richness as compared to LAM9C1 isolates. Moreover, LAM9C2 sublineage appeared to expand close to twenty times more than LAM9C1 and showed older traces of expansion. Interestingly, a significant proportion of LAM9C2 isolates presented typical signature of ancestral LAM-RDRio MIRU-VNTR type (224226153321. Further studies based on Whole Genome Sequencing of LAM strains will provide the needed resolution to decipher the biogeographical structure and evolutionary history of this successful family.
Galbraith, Craig S.; Merrill, Gregory B.; Kline, Doug M.
2012-01-01
In this study we investigate the underlying relational structure between student evaluations of teaching effectiveness (SETEs) and achievement of student learning outcomes in 116 business related courses. Utilizing traditional statistical techniques, a neural network analysis and a Bayesian data reduction and classification algorithm, we find…
Lesaffre, Emmanuel
2012-01-01
The growth of biostatistics has been phenomenal in recent years and has been marked by considerable technical innovation in both methodology and computational practicality. One area that has experienced significant growth is Bayesian methods. The growing use of Bayesian methodology has taken place partly due to an increasing number of practitioners valuing the Bayesian paradigm as matching that of scientific discovery. In addition, computational advances have allowed for more complex models to be fitted routinely to realistic data sets. Through examples, exercises and a combination of introd
Comparing population size estimators for plethodontid salamanders
Bailey, L.L.; Simons, T.R.; Pollock, K.H.
2004-01-01
Despite concern over amphibian declines, few studies estimate absolute abundances because of logistic and economic constraints and previously poor estimator performance. Two estimation approaches recommended for amphibian studies are mark-recapture and depletion (or removal) sampling. We compared abundance estimation via various mark-recapture and depletion methods, using data from a three-year study of terrestrial salamanders in Great Smoky Mountains National Park. Our results indicate that short-term closed-population, robust design, and depletion methods estimate surface population of salamanders (i.e., those near the surface and available for capture during a given sampling occasion). In longer duration studies, temporary emigration violates assumptions of both open- and closed-population mark-recapture estimation models. However, if the temporary emigration is completely random, these models should yield unbiased estimates of the total population (superpopulation) of salamanders in the sampled area. We recommend using Pollock's robust design in mark-recapture studies because of its flexibility to incorporate variation in capture probabilities and to estimate temporary emigration probabilities.
Draper, D.
2001-01-01
© 2012 Springer Science+Business Media, LLC. All rights reserved. Article Outline: Glossary Definition of the Subject and Introduction The Bayesian Statistical Paradigm Three Examples Comparison with the Frequentist Statistical Paradigm Future Directions Bibliography
Institute of Scientific and Technical Information of China (English)
Li WANG; Yong WEI; Yanqing HUANG
2013-01-01
Morganella morganii strain 602-1 was isolated from a sick Chinese giant salamander (Andrias davidianus). The strain 602-1 was identiifed through its physiological and biochemical properties and 16S rDNA gene ampliifcation and analyses. Pathogenicity was proven by experimental animal infection, and histopathological examination. The results showed that the ampliifed 16S rDNA sequence of strain 602-1 was 1455 bp, and showed 99%identity with M. morganii. In the host infection experiment, the mortality of Chinese giant salamanders was about 70%. Pathological changes occurred in the spleen, heart, liver, kidney and intestine. This study will help the prevention, understanding and cure for M. morganii infections in amphibians.
Kuchta, Shawn R; Brown, Ashley D; Converse, Paul E; Highton, Richard
2016-01-01
Species are a fundamental unit of biodiversity, yet can be challenging to delimit objectively. This is particularly true of species complexes characterized by high levels of population genetic structure, hybridization between genetic groups, isolation by distance, and limited phenotypic variation. Previous work on the Cumberland Plateau Salamander, Plethodon kentucki, suggested that it might constitute a species complex despite occupying a relatively small geographic range. To examine this hypothesis, we sampled 135 individuals from 43 populations, and used four mitochondrial loci and five nuclear loci (5693 base pairs) to quantify phylogeographic structure and probe for cryptic species diversity. Rates of evolution for each locus were inferred using the multidistribute package, and time calibrated gene trees and species trees were inferred using BEAST 2 and *BEAST 2, respectively. Because the parameter space relevant for species delimitation is large and complex, and all methods make simplifying assumptions that may lead them to fail, we conducted an array of analyses. Our assumption was that strongly supported species would be congruent across methods. Putative species were first delimited using a Bayesian implementation of the GMYC model (bGMYC), Geneland, and Brownie. We then validated these species using the genealogical sorting index and BPP. We found substantial phylogeographic diversity using mtDNA, including four divergent clades and an inferred common ancestor at 14.9 myr (95% HPD: 10.8-19.7 myr). By contrast, this diversity was not corroborated by nuclear sequence data, which exhibited low levels of variation and weak phylogeographic structure. Species trees estimated a far younger root than did the mtDNA data, closer to 1.0 myr old. Mutually exclusive putative species were identified by the different approaches. Possible causes of data set discordance, and the problem of species delimitation in complexes with high levels of population structure and
Effects of red-backed salamanders on ecosystem functions.
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Daniel J Hocking
Full Text Available Ecosystems provide a vast array of services for human societies, but understanding how various organisms contribute to the functions that maintain these services remains an important ecological challenge. Predators can affect ecosystem functions through a combination of top-down trophic cascades and bottom-up effects on nutrient dynamics. As the most abundant vertebrate predator in many eastern US forests, woodland salamanders (Plethodon spp. likely affect ecosystems functions. We examined the effects of red-backed salamanders (Plethodon cinereus on a variety of forest ecosystem functions using a combined approach of large-scale salamander removals (314-m(2 plots and small-scale enclosures (2 m(2 where we explicitly manipulated salamander density (0, 0.5, 1, 2, 4 m(-2. In these experiments, we measured the rates of litter and wood decomposition, potential nitrogen mineralization and nitrification rates, acorn germination, and foliar insect damage on red oak seedlings. Across both experimental venues, we found no significant effect of red-backed salamanders on any of the ecosystem functions. We also found no effect of salamanders on intraguild predator abundance (carabid beetles, centipedes, spiders. Our study adds to the already conflicting evidence on effects of red-backed salamander and other amphibians on terrestrial ecosystem functions. It appears likely that the impact of terrestrial amphibians on ecosystem functions is context dependent. Future research would benefit from explicitly examining terrestrial amphibian effects on ecosystem functions under a variety of environmental conditions and in different forest types.
Could we also be regenerative superheroes, like salamanders?
Dall'Agnese, Alessandra; Puri, Pier Lorenzo
2016-09-01
Development of methods to reawaken the semi-dormant regenerative potential that lies within adult human tissues would hold promise for the restoration of diseased or damaged organs and tissues. While most of the regeneration potential is suppressed in many vertebrates, including humans, during adult life, urodele amphibians (salamanders) retain their regenerative ability throughout adulthood. Studies in newts and axolotls, two salamander models, have provided significant knowledge about adult limb regeneration. In this review, we present a comparative analysis of salamander and mammalian regeneration and discuss how evolutionarily altered properties of the regenerative environment can be exploited to restore full regenerative potential in the human body. PMID:27338874
Vangelder, B. H. W.
1978-01-01
Non-Bayesian statistics were used in simulation studies centered around laser range observations to LAGEOS. The capabilities of satellite laser ranging especially in connection with relative station positioning are evaluated. The satellite measurement system under investigation may fall short in precise determinations of the earth's orientation (precession and nutation) and earth's rotation as opposed to systems as very long baseline interferometry (VLBI) and lunar laser ranging (LLR). Relative station positioning, determination of (differential) polar motion, positioning of stations with respect to the earth's center of mass and determination of the earth's gravity field should be easily realized by satellite laser ranging (SLR). The last two features should be considered as best (or solely) determinable by SLR in contrast to VLBI and LLR.
Final Critical Habitat for Reticulated Flatwoods Salamander (Ambystoma bishopi)
US Fish and Wildlife Service, Department of the Interior — These data identify, in general, the areas of final critical habitat for the endangered Ambystoma bishopi (reticulated flatwoods salamander).
Streamside Salamander Inventory and Monitoring Northeast Refuges Summer 2003
US Fish and Wildlife Service, Department of the Interior — The objectives of this project are to (1) conduct transect and quadrat sampling for streamside salamanders, (2) determine detection rates and population estimates...
Streamside Salamander Inventory and Monitoring Northeast Refuges Summer 2002
US Fish and Wildlife Service, Department of the Interior — The objectives of this project are to (1) conduct transect and quadrat sampling for streamside salamanders, (2) determine detection rates and population estimates...
Terrestrial salamander abundance on reclaimed mountaintop removal mines
Wood, Petra Bohall; Williams, Jennifer M.
2013-01-01
Mountaintop removal mining, a large-scale disturbance affecting vegetation, soil structure, and topography, converts landscapes from mature forests to extensive grassland and shrubland habitats. We sampled salamanders using drift-fence arrays and coverboard transects on and near mountaintop removal mines in southern West Virginia, USA, during 2000–2002. We compared terrestrial salamander relative abundance and species richness of un-mined, intact forest with habitats on reclaimed mountaintop removal mines (reclaimed grassland, reclaimed shrubland, and fragmented forest). Salamanders within forests increased in relative abundance with increasing distance from reclaimed mine edge. Reclaimed grassland and shrubland habitats had lower relative abundance and species richness than forests. Characteristics of reclaimed habitats that likely contributed to lower salamander abundance included poor soils (dry, compacted, little organic matter, high rock content), reduced vertical structure of vegetation and little tree cover, and low litter and woody debris cover. Past research has shown that salamander populations reduced by clearcutting may rebound in 15–24 years. Time since disturbance was 7–28 years in reclaimed habitats on our study areas and salamander populations had not reached levels found in adjacent mature forests.
Landmark learning by the Ozark zigzag salamander Plethodon angusticlavius
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Adam L. CRANE, Alicia MATHIS
2011-08-01
Full Text Available Although salamanders have been shown to respond to classical conditioning, spatial learning has been largely unstudied. We tested whether salamanders could learn to locate foraging areas by using landmarks. We trained 10 salamanders Plethodon angusticlavius to use landmarks (small rocks to locate patches within the arena containing food (blackworms Lumbriculus variegatus. At the corners of each square testing arena were four plastic dishes, one containing blackworms and the other three empty. A rock was placed in front of the dish containing blackworms, and the location of the food-dish was randomly chosen for each training trial. A control group was also trained to feed on blackworms in the presence of a rock, but the rock was positioned randomly among the four dish locations so that the rock was not a reliable landmark for the worms. Although the length of the training period for individual salamanders varied (22–38 trainings per individual, the mean number of trainings for salamanders in the control and experimental groups was equal (30 training trials. During testing, no blackworms were present to eliminate any visual or chemical cues emanating directly from the prey. Individuals trained with the rock landmarks spent significantly more time in the area of the landmark than did control salamanders [Current Zoology 57 (4: 485–490, 2011].
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Kanagi Kanapathy
2014-01-01
Full Text Available The research question is whether the positive relationship found between supplier involvement practices and new product development performances in developed economies also holds in emerging economies. The role of supplier involvement practices in new product development performance is yet to be substantially investigated in the emerging economies (other than China. This premise was examined by distributing a survey instrument (Jayaram’s (2008 published survey instrument that has been utilised in developed economies to Malaysian manufacturing companies. To gauge the relationship between the supplier involvement practices and new product development (NPD project performance of 146 companies, structural equation modelling was adopted. Our findings prove that supplier involvement practices have a significant positive impact on NPD project performance in an emerging economy with respect to quality objectives, design objectives, cost objectives, and “time-to-market” objectives. Further analysis using the Bayesian Markov Chain Monte Carlo algorithm, yielding a more credible and feasible differentiation, confirmed these results (even in the case of an emerging economy and indicated that these practices have a 28% impact on variance of NPD project performance. This considerable effect implies that supplier involvement is a must have, although further research is needed to identify the contingencies for its practices.
Bessiere, Pierre; Ahuactzin, Juan Manuel; Mekhnacha, Kamel
2013-01-01
Probability as an Alternative to Boolean LogicWhile logic is the mathematical foundation of rational reasoning and the fundamental principle of computing, it is restricted to problems where information is both complete and certain. However, many real-world problems, from financial investments to email filtering, are incomplete or uncertain in nature. Probability theory and Bayesian computing together provide an alternative framework to deal with incomplete and uncertain data. Decision-Making Tools and Methods for Incomplete and Uncertain DataEmphasizing probability as an alternative to Boolean
Phylogeography and evolution of the Red Salamander (Pseudotriton ruber).
Folt, Brian; Garrison, Nicole; Guyer, Craig; Rodriguez, Juanita; Bond, Jason E
2016-05-01
Phylogeographic studies frequently result in the elevation of subspecific taxa to species given monophyly, or the synonymy of subspecies that are not monophyletic. However, given limited or incongruent datasets, retention of subspecies can be useful to describe hypothesized incipient species or to illustrate interesting biological phenomena driving morphological diversity. Four subspecific taxa have been used to describe largely allopatric geographic variation within the species Pseudotriton ruber, a plethodontid salamander occupying stream and spring habitats across eastern North America: P. r. vioscai occurs in lowland Coastal Plain habitats, while P. r. ruber, P. r. nitidus, and P. r. schencki occupy upland regions in and around the Appalachian Mountains. Pseudotriton ruber co-occurs through its distribution with the aposematic newt Notophthalmus viridescens, and both species are hypothesized to be part of a Müllerian mimicry complex. In this study, we sequenced regions of two mitochondrial (cytochrome b, NADH dehydrogenase subunit 2) and one single copy nuclear protein-coding gene (pro-opiomelanocortin) from individuals sampled across much of the distribution of P. ruber and then used maximum-likelihood and Bayesian phylogenetic inference to test the monophyly of subspecies, reconstruct biogeographic history, and make inferences about morphological evolution. Phylogeographic hypotheses from mitochondrial and nuclear datasets described structure among populations of P. ruber which separated Coastal Plain and upland Appalachian populations, but subspecies were not monophyletic. Biogeographic reconstruction estimated the ancestor of all populations to have occupied and initially diverged in the Coastal Plain during the Pliocene (∼3.6mya), before one lineage subsequently invaded upland areas of Appalachia. Bold bright coloration of high elevation subspecies P. r. nitidus and P. r. schencki appears to have evolved twice. We hypothesize that the Müllerian mimicry
Institute of Scientific and Technical Information of China (English)
岳秀廷; 李志农; 陈金刚
2012-01-01
用独立分量分析(ICA)分解和表示数据时,假设整个数据分布完全可以用一个坐标系来描述.然而,当观测数据是由许多自相似的、非高斯的流形组成时,则硬是用一个单独的、全局的表示是不合适的,这样会产生一个次优的表示.针对ICA在盲源分离中的不足,在变分贝叶斯理论的基础上提出了一种基于变分贝叶斯混合独立分量分析的机械故障源盲分离方法.该方法是考虑到源信号来自于多个坐标系,然后在多个坐标系下建立独立分量分析混合模型对观测信号进行学习分离.实验结果表明,本文提出的方法是非常有效的.%Decomposing and representing data using independent component analysers(ICA)assumes that the whole data distribution is adequately described by one coordinate frame.However,if the observed data consists of various self-similar,non-Gaussian manifolds, enforcing a single, global representation is not appropriate and will produce a sub-optimal representation.In order to make up the lack of independent component analyser in blind sources separations, blind separation of mechanical fault sources based on variational Bayesian mixture of independent component analysers is presented based on variational Bayesian theory in this paper.Conside.ring the source signals coming from multiple frames, the method creats a mixture model of independent component analysers in multiple frameworks for learning the observed signals and separating thenuThe experimental results show that the method proposed in this paper is very effective.
Embryonic development and organogenesis of Chinese giant salamander, Andrias davidianus
Institute of Scientific and Technical Information of China (English)
无
2007-01-01
The morphology and organogenesis of Chinese giant salamander, Andrias davidianus, in its different developmental periods and stages are described in detail, which provides an intact criterion for distinguishing different stages of its developmental process.Based on the external morphological and internal histological features, six periods including 20 stages of organogenesis of Chinese giant salamander are established, which are cleavage period, blastula period, gastrula period, neurula period, organogenesis stage and hatching stage. Generally, the embryonic development of Chinese giant salamander is consistent with those of Eastern newt, Cynops orientalis,and Black spots frog, R. nigromaculata. However, they have some differences in the early cleavage process and the development of digestive system. The cleavage of Chinese giant salamander, A. davidianus is not a discoidal division type, which is different from other species reported. And the first three cleavages being meridional and a retardant development of its digestive system without halter and sucker existing are the evident features of the embryonic development of Chinese giant salamander.
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Martínez-Solano Iñigo
2009-02-01
Full Text Available Abstract Background Island populations are excellent model systems for studies of phenotypic, ecological and molecular evolution. In this study, molecular markers of mitochondrial and nuclear derivation were used to investigate the evolution, structure and origin of populations of the California slender salamander (Batrachoseps attenuatus inhabiting the six major islands of San Francisco Bay, formed following the rising of sea level around 9,000 years ago. Results There was a high degree of congruence in the results of analyses of nucleotide and allozyme data, both of which strongly support the hypothesis that, for the majority of the islands, salamanders are descended from hilltop populations that became isolated with the formation of the Bay ca. 9,000 years ago. There are two exceptions (Alcatraz and Yerba Buena where the evidence suggests that salamander populations are wholly or in part, the result of anthropogenic introductions. Comparison of the molecular data and the interpretations drawn therefrom with an earlier morphological study of many of the same salamander populations show some of the same evolutionary trends. Conclusion In spite of marked differences between the evolutionary rates of the two kinds of molecular markers, both indicate distinctive and similar patterns of population structure for B. attenuatus in the San Francisco Bay Area and its islands. With the two noted exceptions, it is clear that most island populations were established prior to the 9,000 years since the formation of the Bay. Results of coalescence-based analyses suggest that for most island populations the mtDNA lineages from which they were derived date from the Pleistocene. It can be said that, based on observed values of genetic diversity, the last 9,000 years of evolution on these islands have been characterized by relative stability, with the occasional extinction of some haplotypes or alleles that were formerly shared between island and mainland
Chloride equilibrium potential in salamander cones
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Bryson Eric J
2004-12-01
Full Text Available Abstract Background GABAergic inhibition and effects of intracellular chloride ions on calcium channel activity have been proposed to regulate neurotransmission from photoreceptors. To assess the impact of these and other chloride-dependent mechanisms on release from cones, the chloride equilibrium potential (ECl was determined in red-sensitive, large single cones from the tiger salamander retinal slice. Results Whole cell recordings were done using gramicidin perforated patch techniques to maintain endogenous Cl- levels. Membrane potentials were corrected for liquid junction potentials. Cone resting potentials were found to average -46 mV. To measure ECl, we applied long depolarizing steps to activate the calcium-activated chloride current (ICl(Ca and then determined the reversal potential for the current component that was inhibited by the Cl- channel blocker, niflumic acid. With this method, ECl was found to average -46 mV. In a complementary approach, we used a Cl-sensitive dye, MEQ, to measure the Cl- flux produced by depolarization with elevated concentrations of K+. The membrane potentials produced by the various high K+ solutions were measured in separate current clamp experiments. Consistent with electrophysiological experiments, MEQ fluorescence measurements indicated that ECl was below -36 mV. Conclusions The results of this study indicate that ECl is close to the dark resting potential. This will minimize the impact of chloride-dependent presynaptic mechanisms in cone terminals involving GABAa receptors, glutamate transporters and ICl(Ca.
Better than fish on land? Hearing across metamorphosis in salamanders
DEFF Research Database (Denmark)
Christensen, Christian Bech; Lauridsen, Henrik; Christensen-Dalsgaard, Jakob;
2015-01-01
Early tetrapods faced an auditory challenge from the impedance mismatch between air and tissue in the transition from aquatic to terrestrial lifestyles during the Early Carboniferous (350 Ma). Consequently, tetrapods may have been deaf to airborne sounds for up to 100 Myr until tympanic middle ears...... hearing in early tetrapods. Here, we combine imaging techniques with neurophysiological measurements to resolve how the change from aquatic larvae to terrestrial adult affects the ear morphology and sensory capabilities of salamanders. We show that air-induced pressure detection enhances underwater...... hearing sensitivity of salamanders at frequencies above 120 Hz, and that both terrestrial adults and fully aquatic juvenile salamanders can detect airborne sound. Collectively, these findings suggest that early atympanic tetrapods may have been pre-equipped to aerial hearing and are able to hear airborne...
Modular functional organisation of the axial locomotor system in salamanders.
Cabelguen, Jean-Marie; Charrier, Vanessa; Mathou, Alexia
2014-02-01
Most investigations on tetrapod locomotion have been concerned with limb movements. However, there is compelling evidence that the axial musculoskeletal system contributes to important functions during locomotion. Adult salamanders offer a remarkable opportunity to examine these functions because these amphibians use axial undulations to propel themselves in both aquatic and terrestrial environments. In this article, we review the currently available biological data on axial functions during various locomotor modes in salamanders. We also present data showing the modular organisation of the neural networks that generate axial synergies during locomotion. The functional implication of this modular organisation is discussed.
Introduction to Bayesian statistics
Bolstad, William M
2016-01-01
There is a strong upsurge in the use of Bayesian methods in applied statistical analysis, yet most introductory statistics texts only present frequentist methods. Bayesian statistics has many important advantages that students should learn about if they are going into fields where statistics will be used. In this Third Edition, four newly-added chapters address topics that reflect the rapid advances in the field of Bayesian staistics. The author continues to provide a Bayesian treatment of introductory statistical topics, such as scientific data gathering, discrete random variables, robust Bayesian methods, and Bayesian approaches to inferenfe cfor discrete random variables, bionomial proprotion, Poisson, normal mean, and simple linear regression. In addition, newly-developing topics in the field are presented in four new chapters: Bayesian inference with unknown mean and variance; Bayesian inference for Multivariate Normal mean vector; Bayesian inference for Multiple Linear RegressionModel; and Computati...
Coalescence patterns of endemic Tibetan species of stream salamanders (Hynobiidae: Batrachuperus).
Lu, Bin; Zheng, Yuchi; Murphy, Robert W; Zeng, Xiaomao
2012-07-01
Orogenesis of topographically diverse montane regions often drives complex evolutionary histories of species. The extensive biodiversity of the eastern edge of the Tibetan Plateau, which gradually decreases eastwardly, facilitates a comparison of historical patterns. We use coalescence methods to compare species of stream salamanders (Batrachuperus) that occur at high and low elevations. Coalescent simulations reveal that closely related species are likely to have been influenced by different drivers of diversification. Species living in the western high-elevation region with its northsouth extending mountains appear to have experienced colonization via dispersal followed by isolation and divergence. In contrast, species on the eastern low-elevation region, which has many discontinuous mountain ranges, appear to have experienced fragmentation, sometimes staged, of wide-ranging ancestral populations. The two groups of species appear to have been affected differently by glaciation. High-elevation species, which are more resistant to cooler temperatures, appear to have experienced population declines as recently as the last glaciation (0.016-0.032Ma). In contrast, salamanders dwelling in the warmer and wetter habitats at low-elevation environs appear to have been affected less by the relatively recent, milder glaciation, and more so by harsher, extensive glaciations (0.5-0.175 Ma). Thus, elevation, topography and cold tolerance appear to drive evolutionary patterns of diversification and demography even among closely related taxa. The comparison of multiple species in genealogical analyses can lead to an understanding of the evolutionary drivers. PMID:22571598
Toxicological responses of red-backed salamanders (Plethodon cinereus) to soil exposures of copper.
Bazar, Matthew A; Quinn, Michael J; Mozzachio, Kristie; Bleiler, John A; Archer, Christine R; Phillips, Carlton T; Johnson, Mark S
2009-07-01
Copper (Cu) has widespread military use in munitions and small arms, particularly as a protective jacket for lead projectiles. The distribution of Cu at many US military sites is substantial and sites of contamination include habitats in and around military storage facilities, manufacturing, load and packing plants, open burning/open detonation areas, and firing ranges. Some of these areas include habitat for amphibian species, which generally lack toxicity data for risk assessment purposes. In an effort to ascertain Cu concentrations in soil that are toxic to terrestrial amphibians, 100 red-backed salamanders (Plethodon cinereus) were randomly sorted by weight, assigned to either a control soil or one of four treatments amended with copper acetate in soil, and exposed for 28 days. Analytical mean soil concentrations were 18, 283, 803, 1333, and 2700 mg Cu/kg soil dry weight. Food consisted of uncontaminated flightless Drosophila melanogaster. Survival was reduced in salamanders exposed to 1333 and 2700 mg/kg by 55% and 100%, respectively. Mortality/morbidity occurred within the first 4 days of exposure. These data suggest that a Cu soil concentration of and exceeding 1333.3 +/- 120.2 mg/kg results in reduced survival, whereas hematology analyses suggest that a concentration of and exceeding 803.3 +/- 98.4 mg/kg might result in reduced total white blood cell count. No effects were observed at 283.3 +/- 36.7 mg/kg. PMID:18825446
Miller, Mark P.; Haig, Susan M.; Wagner, R.S.
2006-01-01
The Southern torrent salamander (Rhyacotriton variegatus) was recently found not warranted for listing under the US Endangered Species Act due to lack of information regarding population fragmentation and gene flow. Found in small-order streams associated with late-successional coniferous forests of the US Pacific Northwest, threats to their persistence include disturbance related to timber harvest activities. We conducted a study of genetic diversity throughout this species' range to 1) identify major phylogenetic lineages and phylogeographic barriers and 2) elucidate regional patterns of population genetic and spatial phylogeographic structure. Cytochrome b sequence variation was examined for 189 individuals from 72 localities. We identified 3 major lineages corresponding to nonoverlapping geographic regions: a northern California clade, a central Oregon clade, and a northern Oregon clade. The Yaquina River may be a phylogeographic barrier between the northern Oregon and central Oregon clades, whereas the Smith River in northern California appears to correspond to the discontinuity between the central Oregon and northern California clades. Spatial analyses of genetic variation within regions encompassing major clades indicated that the extent of genetic structure is comparable among regions. We discuss our results in the context of conservation efforts for Southern torrent salamanders.
Miller, M.P.; Haig, S.M.; Wagner, R.S.
2006-01-01
The Southern torrent salamander (Rhyacotriton variegatus) was recently found not warranted for listing under the US Endangered Species Act due to lack of information regarding population fragmentation and gene flow. Found in small-order streams associated with late-successional coniferous forests of the US Pacific Northwest, threats to their persistence include disturbance related to timber harvest activities. We conducted a study of genetic diversity throughout this species' range to 1) identify major phylogenetic lineages and phylogeographic barriers and 2) elucidate regional patterns of population genetic and spatial phylogeographic structure. Cytochrome b sequence variation was examined for 189 individuals from 72 localities. We identified 3 major lineages corresponding to nonoverlapping geographic regions: a northern California clade, a central Oregon clade, and a northern Oregon clade. The Yaquina River may be a phylogeographic barrier between the northern Oregon and central Oregon clades, whereas the Smith River in northern California appears to correspond to the discontinuity between the central Oregon and northern California clades. Spatial analyses of genetic variation within regions encompassing major clades indicated that the extent of genetic structure is comparable among regions. We discuss our results in the context of conservation efforts for Southern torrent salamanders. ?? The American Genetic Association. 2006. All rights reserved.
Bayesian artificial intelligence
Korb, Kevin B
2003-01-01
As the power of Bayesian techniques has become more fully realized, the field of artificial intelligence has embraced Bayesian methodology and integrated it to the point where an introduction to Bayesian techniques is now a core course in many computer science programs. Unlike other books on the subject, Bayesian Artificial Intelligence keeps mathematical detail to a minimum and covers a broad range of topics. The authors integrate all of Bayesian net technology and learning Bayesian net technology and apply them both to knowledge engineering. They emphasize understanding and intuition but also provide the algorithms and technical background needed for applications. Software, exercises, and solutions are available on the authors' website.
Bayesian artificial intelligence
Korb, Kevin B
2010-01-01
Updated and expanded, Bayesian Artificial Intelligence, Second Edition provides a practical and accessible introduction to the main concepts, foundation, and applications of Bayesian networks. It focuses on both the causal discovery of networks and Bayesian inference procedures. Adopting a causal interpretation of Bayesian networks, the authors discuss the use of Bayesian networks for causal modeling. They also draw on their own applied research to illustrate various applications of the technology.New to the Second EditionNew chapter on Bayesian network classifiersNew section on object-oriente
Bayesian networks as a tool for epidemiological systems analysis
Lewis, F.I.
2012-01-01
Bayesian network analysis is a form of probabilistic modeling which derives from empirical data a directed acyclic graph (DAG) describing the dependency structure between random variables. Bayesian networks are increasingly finding application in areas such as computational and systems biology, and more recently in epidemiological analyses. The key distinction between standard empirical modeling approaches, such as generalised linear modeling, and Bayesian network analyses is that the latter ...
Gelman, Andrew; Stern, Hal S; Dunson, David B; Vehtari, Aki; Rubin, Donald B
2013-01-01
FUNDAMENTALS OF BAYESIAN INFERENCEProbability and InferenceSingle-Parameter Models Introduction to Multiparameter Models Asymptotics and Connections to Non-Bayesian ApproachesHierarchical ModelsFUNDAMENTALS OF BAYESIAN DATA ANALYSISModel Checking Evaluating, Comparing, and Expanding ModelsModeling Accounting for Data Collection Decision AnalysisADVANCED COMPUTATION Introduction to Bayesian Computation Basics of Markov Chain Simulation Computationally Efficient Markov Chain Simulation Modal and Distributional ApproximationsREGRESSION MODELS Introduction to Regression Models Hierarchical Linear
Yuan, Ying; MacKinnon, David P.
2009-01-01
This article proposes Bayesian analysis of mediation effects. Compared to conventional frequentist mediation analysis, the Bayesian approach has several advantages. First, it allows researchers to incorporate prior information into the mediation analysis, thus potentially improving the efficiency of estimates. Second, under the Bayesian mediation analysis, inference is straightforward and exact, which makes it appealing for studies with small samples. Third, the Bayesian approach is conceptua...
Ancient DNA assessment of tiger salamander population in Yellowstone National Park.
Directory of Open Access Journals (Sweden)
Sarah K McMenamin
Full Text Available Recent data indicates that blotched tiger salamanders (Ambystoma tigrinum melanostictum in northern regions of Yellowstone National Park are declining due to climate-related habitat changes. In this study, we used ancient and modern mitochondrial haplotype diversity to model the effective size of this amphibian population through recent geological time and to assess past responses to climatic changes in the region. Using subfossils collected from a cave in northern Yellowstone, we analyzed >700 base pairs of mitochondrial sequence from 16 samples ranging in age from 100 to 3300 years old and found that all shared an identical haplotype. Although mitochondrial diversity was extremely low within the living population, we still were able to detect geographic subdivision within the local area. Using serial coalescent modelling with Bayesian priors from both modern and ancient genetic data we simulated a range of probable population sizes and mutation rates through time. Our simulations suggest that regional mitochondrial diversity has remained relatively constant even through climatic fluctuations of recent millennia.
Bayesian Games with Intentions
Bjorndahl, Adam; Halpern, Joseph Y.; Pass, Rafael
2016-01-01
We show that standard Bayesian games cannot represent the full spectrum of belief-dependent preferences. However, by introducing a fundamental distinction between intended and actual strategies, we remove this limitation. We define Bayesian games with intentions, generalizing both Bayesian games and psychological games, and prove that Nash equilibria in psychological games correspond to a special class of equilibria as defined in our setting.
Impact of valley fills on streamside salamanders in southern West Virginia
Wood, Petra Bohall; Williams, Jennifer M.
2013-01-01
Valley fills associated with mountaintop-removal mining bury stream headwaters and affect water quality and ecological function of reaches below fills. We quantified relative abundance of streamside salamanders in southern West Virginia during 2002 in three streams below valley fills (VFS) and in three reference streams (RS). We surveyed 36 10- × 2-m stream transects, once in summer and fall, paired by order and structure. Of 2,343 salamanders captured, 66.7% were from RS. Total salamanders (adults plus larvae) were more abundant in RS than VFS for first-order and second-order reaches. Adult salamanders had greater abundance in first-order reaches of RS than VFS. Larval salamanders were more abundant in second-order reaches of RS than VFS. No stream width or mesohabitat variables differed between VFS and RS. Only two cover variables differed. Silt cover, greater in VFS than RS first-order reaches, is a likely contributor to reduced abundance of salamanders in VFS. Second-order RS had more boulder cover than second-order VFS, which may have contributed to the higher total and larval salamander abundance in RS. Water chemistry assessments of our VFS and RS reported elevated levels of metal and ion concentrations in VFS, which can depress macroinvertebrate populations and likely affect salamander abundance. Valley fills appear to have significant negative effects on stream salamander abundance due to alterations in habitat structure, water quality and chemistry, and macroinvertebrate communities in streams below fills.
DEFF Research Database (Denmark)
Jensen, Finn Verner; Nielsen, Thomas Dyhre
2016-01-01
Mathematically, a Bayesian graphical model is a compact representation of the joint probability distribution for a set of variables. The most frequently used type of Bayesian graphical models are Bayesian networks. The structural part of a Bayesian graphical model is a graph consisting of nodes...... and edges. The nodes represent variables, which may be either discrete or continuous. An edge between two nodes A and B indicates a direct influence between the state of A and the state of B, which in some domains can also be interpreted as a causal relation. The wide-spread use of Bayesian networks...... is largely due to the availability of efficient inference algorithms for answering probabilistic queries about the states of the variables in the network. Furthermore, to support the construction of Bayesian network models, learning algorithms are also available. We give an overview of the Bayesian network...
Ecological radiation with limited morphological diversification in salamanders.
Blankers, Thomas; Adams, D C; Wiens, J J
2012-04-01
A major goal of evolutionary biology is to explain morphological diversity among species. Many studies suggest that much morphological variation is explained by adaptation to different microhabitats. Here, we test whether morphology and microhabitat use are related in plethodontid salamanders, which contain the majority of salamander species, and have radiated into a striking diversity of microhabitats. We obtained microhabitat data for 189 species that also had both morphometric and phylogenetic data. We then tested for associations between morphology and microhabitat categories using phylogenetic comparative methods. Associations between morphology and ecology in plethodontids are largely confined to a single clade within one subfamily (Bolitoglossinae), whereas variation in morphology across other plethodontids is unrelated to microhabitat categories. These results demonstrate that ecological radiation and morphological evolution can be largely decoupled in a major clade. The results also offer a striking contrast to lizards, which typically show close relationships between morphology and microhabitat.
Ecological radiation with limited morphological diversification in salamanders.
Blankers, Thomas; Adams, D C; Wiens, J J
2012-04-01
A major goal of evolutionary biology is to explain morphological diversity among species. Many studies suggest that much morphological variation is explained by adaptation to different microhabitats. Here, we test whether morphology and microhabitat use are related in plethodontid salamanders, which contain the majority of salamander species, and have radiated into a striking diversity of microhabitats. We obtained microhabitat data for 189 species that also had both morphometric and phylogenetic data. We then tested for associations between morphology and microhabitat categories using phylogenetic comparative methods. Associations between morphology and ecology in plethodontids are largely confined to a single clade within one subfamily (Bolitoglossinae), whereas variation in morphology across other plethodontids is unrelated to microhabitat categories. These results demonstrate that ecological radiation and morphological evolution can be largely decoupled in a major clade. The results also offer a striking contrast to lizards, which typically show close relationships between morphology and microhabitat. PMID:22268991
Presence of the vomeronasal system in aquatic salamanders.
Eisthen, H L
2000-01-01
Previous reports have indicated that members of the proteid family of salamanders lack a vomeronasal system, and this absence has been interpreted as representing the ancestral condition for aquatic amphibians. I examined the anatomy of the nasal cavities, nasal epithelia, and forebrains of members of the proteid family, mudpuppies (Necturus maculosus), as well as members of the amphiumid and sirenid families (Amphiuma tridactylum and Siren intermedia). Using a combination of light and transm...
Salamander growth rates increase along an experimental stream phosphorus gradient.
Bumpers, Phillip M; Maerz, John C; Rosemond, Amy D; Benstead, Jonathan P
2015-11-01
Nutrient-driven perturbations to the resource base of food webs are predicted to attenuate with trophic distance, so it is unclear whether higher-level consumers will generally respond to anthropogenic nutrient loading. Few studies have tested whether nutrient (specifically, nitrogen [N] and phosphorus [P]) enrichment of aquatic ecosystems propagates through multiple trophic levels to affect predators, or whether N vs. P is relatively more important in driving effects on food webs. We conducted two-year whole-stream N and P additions to five streams to generate gradients in N and P concentration and N:P ratio (target N:P = 2, 8, 16, 32, 128). Larval salamanders are vertebrate predators of primary and secondary macroinvertebrate consumers in many heterotrophic headwater streams in which the basal resources are detritus and associated microorganisms. We determined the effects of N and P on the growth rates of caged and free-roaming larval Desmognathus quadramaculatus and the average body size of larval Eurycea wilderae. Growth rates and average body size increased by up to 40% and 60%, respectively, with P concentration and were negatively related to N:P ratio. These findings were consistent across both species of salamanders using different methodologies (cage vs. free-roaming) and at different temporal scales (3 months vs. 2 yr). Nitrogen concentration was not significantly related to increased growth rate or body size of the salamander species tested. Our findings suggest that salamander growth responds to the relaxation of ecosystem-level P limitation and that moderate P enrichment can have relatively large effects on vertebrate predators in detritus-based food webs. PMID:27070018
Telocytes in ileum of the Chinese giant salamander: ultrastructural evidence
Hui ZHANG; Zhong, Shengwei; Ge, Tingting; Peng, Shasha; Yu, Pengcheng; Zhou, Zuohong; Guo, Xiaoquan
2016-01-01
Abstract Telocytes (TCs) and their telopodes (Tps) have been found in various organs of many mammals, including in lower animals. However, knowledge of TCs in lower animals is still very limited. This study identified TCs and their Tps in the ileum of the Chinese giant salamander, Andrias davidianus (Amphibia: Caudata), by transmission electron microscopy. The TCs/Tps were found near epithelial cells, glandular cells and unmyelinated nerve fibres. Moreover, exosomes were also found to be pres...
Detection of an enigmatic plethodontid Salamander using Environmental DNA
Pierson, Todd W.; Mckee, Anna; Spear, Stephen F.; Maerz, John C.; Camp, Carlos D.; Glenn, Travis C.
2016-01-01
The isolation and identification of environmental DNA (eDNA) offers a non-invasive and efficient method for the detection of rare and secretive aquatic wildlife, and it is being widely integrated into inventory and monitoring efforts. The Patch-Nosed Salamander (Urspelerpes brucei) is a tiny, recently discovered species of plethodontid salamander known only from headwater streams in a small region of Georgia and South Carolina. Here, we present results of a quantitative PCR-based eDNA assay capable of detecting Urspelerpes in more than 75% of 33 samples from five confirmed streams. We deployed the method at 31 additional streams and located three previously undocumented populations of Urspelerpes. We compare the results of our eDNA assay with our attempt to use aquatic leaf litterbags for the rapid detection of Urspelerpes and demonstrate the relative efficacy of the eDNA assay. We suggest that eDNA offers great potential for use in detecting other aquatic and semi-aquatic plethodontid salamanders.
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Burke, John N.; Bergeron, Christine M.; Todd, Brian D. [Wildlife Ecotoxicology and Physiological Ecology Program, Department of Fisheries and Wildlife Sciences, Virginia Polytechnic Institute and State University, 100 Cheatham Hall, Blacksburg, VA 24061 (United States); Hopkins, William A., E-mail: hopkinsw@vt.ed [Wildlife Ecotoxicology and Physiological Ecology Program, Department of Fisheries and Wildlife Sciences, Virginia Polytechnic Institute and State University, 100 Cheatham Hall, Blacksburg, VA 24061 (United States)
2010-12-15
Mercury (Hg) causes a range of deleterious effects in wildlife, but little is known about its effects on amphibians. Our objective was to determine whether Hg affects performance and behavior in two-lined salamanders (Eurycea bislineata). We collected salamanders from Hg-contaminated and reference sites and assessed speed, responsiveness, and prey capture ability. Mercury concentrations were >17x higher in salamanders from the contaminated sites and were among the highest documented in amphibians. In the first, but not in the second, locomotion trial, we found a significant effect of Hg on speed and responsiveness. In the prey capture experiment, reference salamanders ate approximately twice as many prey items as the contaminated salamanders. Together, our results suggest that sublethal Hg concentrations may negatively affect salamanders by reducing their ability to successfully execute tasks critical to survival. Future work is warranted to determine whether Hg has other sublethal effects on salamanders and whether other amphibians are similarly affected. - Mercury contamination may alter behavior and performance in the northern two-lined salamander (Eurycea bislineata).
Understanding Computational Bayesian Statistics
Bolstad, William M
2011-01-01
A hands-on introduction to computational statistics from a Bayesian point of view Providing a solid grounding in statistics while uniquely covering the topics from a Bayesian perspective, Understanding Computational Bayesian Statistics successfully guides readers through this new, cutting-edge approach. With its hands-on treatment of the topic, the book shows how samples can be drawn from the posterior distribution when the formula giving its shape is all that is known, and how Bayesian inferences can be based on these samples from the posterior. These ideas are illustrated on common statistic
Bayesian statistics an introduction
Lee, Peter M
2012-01-01
Bayesian Statistics is the school of thought that combines prior beliefs with the likelihood of a hypothesis to arrive at posterior beliefs. The first edition of Peter Lee’s book appeared in 1989, but the subject has moved ever onwards, with increasing emphasis on Monte Carlo based techniques. This new fourth edition looks at recent techniques such as variational methods, Bayesian importance sampling, approximate Bayesian computation and Reversible Jump Markov Chain Monte Carlo (RJMCMC), providing a concise account of the way in which the Bayesian approach to statistics develops as wel
Morphological variation in salamanders and their potential response to climate change.
Ficetola, Gentile Francesco; Colleoni, Emiliano; Renaud, Julien; Scali, Stefano; Padoa-Schioppa, Emilio; Thuiller, Wilfried
2016-06-01
Despite the recognition that some species might quickly adapt to new conditions under climate change, demonstrating and predicting such a fundamental response is challenging. Morphological variations in response to climate may be caused by evolutionary changes or phenotypic plasticity, or both, but teasing apart these processes is difficult. Here, we built on the number of thoracic vertebrae (NTV) in ectothermic vertebrates, a known genetically based feature, to establish a link with body size and evaluate how climate change might affect the future morphological response of this group of species. First, we show that in old-world salamanders, NTV variation is strongly related to changes in body size. Secondly, using 22 salamander species as a case study, we found support for relationships between the spatial variation in selected bioclimatic variables and NTV for most of species. For 44% of species, precipitation and aridity were the predominant drivers of geographical variation of the NTV. Temperature features were dominant for 31% of species, while for 19% temperature and precipitation played a comparable role. This two-step analysis demonstrates that ectothermic vertebrates may evolve in response to climate change by modifying the number of thoracic vertebrae. These findings allow to develop scenarios for potential morphological evolution under future climate change and to identify areas and species in which the most marked evolutionary responses are expected. Resistance to climate change estimated from species distribution models was positively related to present-day species morphological response, suggesting that the ability of morphological evolution may play a role for species' persistence under climate change. The possibility that present-day capacity for local adaptation might help the resistance response to climate change can be integrated into analyses of the impact of global changes and should also be considered when planning management actions favouring
Vences, Miguel; Sanchez, Eugenia; Hauswaldt, J Susanne; Eikelmann, Daniel; Rodríguez, Ariel; Carranza, Salvador; Donaire, David; Gehara, Marcelo; Helfer, Véronique; Lötters, Stefan; Werner, Philine; Schulz, Stefan; Steinfartz, Sebastian
2014-04-01
The genus Salamandra represents a clade of six species of Palearctic salamanders of either contrasted black-yellow, or uniformly black coloration, known to contain steroidal alkaloid toxins in high concentrations in their skin secretions. This study reconstructs the phylogeny of the genus Salamandra based on DNA sequences of segments of 10 mitochondrial and 13 nuclear genes from 31 individual samples representing all Salamandra species and most of the commonly recognized subspecies. The concatenated analysis of the complete dataset produced a fully resolved tree with most nodes strongly supported, suggesting that a clade composed of the Alpine salamander (S. atra) and the Corsican fire salamander (S. corsica) is the sister taxon to a clade containing the remaining species, among which S. algira and S. salamandra are sister species. Separate analyses of mitochondrial and nuclear data partitions disagreed regarding basal nodes and in the position of the root but concordantly recovered the S. atra/S. corsica as well as the S. salamandra/S. algira relationship. A species-tree analysis suggested almost simultaneous temporal splits between these pairs of species, which we hypothesize was caused by vicariance events after the Messinian salinity crisis (from late Miocene to early Pliocene). A survey of toxins with combined gas chromatography/mass spectroscopy confirmed the presence of samandarine and/or samandarone steroidal alkaloids in all species of Salamandra as well as in representatives of their sister group, Lyciasalamandra. Samandarone was also detected in lower concentrations in other salamandrids including Calotriton, Euproctus, Lissotriton, and Triturus, suggesting that the presence and possible biosynthesis of this alkaloid is plesiomorphic within the Salamandridae. PMID:24412216
The bugs book a practical introduction to Bayesian analysis
Lunn, David; Best, Nicky; Thomas, Andrew; Spiegelhalter, David
2012-01-01
Introduction: Probability and ParametersProbabilityProbability distributionsCalculating properties of probability distributionsMonte Carlo integrationMonte Carlo Simulations Using BUGSIntroduction to BUGSDoodleBUGSUsing BUGS to simulate from distributionsTransformations of random variablesComplex calculations using Monte CarloMultivariate Monte Carlo analysisPredictions with unknown parametersIntroduction to Bayesian InferenceBayesian learningPosterior predictive distributionsConjugate Bayesian inferenceInference about a discrete parameterCombinations of conjugate analysesBayesian and classica
Frühwirth-Schnatter, Sylvia
1990-01-01
In the paper at hand we apply it to Bayesian statistics to obtain "Fuzzy Bayesian Inference". In the subsequent sections we will discuss a fuzzy valued likelihood function, Bayes' theorem for both fuzzy data and fuzzy priors, a fuzzy Bayes' estimator, fuzzy predictive densities and distributions, and fuzzy H.P.D .-Regions. (author's abstract)
Yuan, Ying; MacKinnon, David P.
2009-01-01
In this article, we propose Bayesian analysis of mediation effects. Compared with conventional frequentist mediation analysis, the Bayesian approach has several advantages. First, it allows researchers to incorporate prior information into the mediation analysis, thus potentially improving the efficiency of estimates. Second, under the Bayesian…
von der Linden, Wolfgang; Dose, Volker; von Toussaint, Udo
2014-06-01
Preface; Part I. Introduction: 1. The meaning of probability; 2. Basic definitions; 3. Bayesian inference; 4. Combinatrics; 5. Random walks; 6. Limit theorems; 7. Continuous distributions; 8. The central limit theorem; 9. Poisson processes and waiting times; Part II. Assigning Probabilities: 10. Transformation invariance; 11. Maximum entropy; 12. Qualified maximum entropy; 13. Global smoothness; Part III. Parameter Estimation: 14. Bayesian parameter estimation; 15. Frequentist parameter estimation; 16. The Cramer-Rao inequality; Part IV. Testing Hypotheses: 17. The Bayesian way; 18. The frequentist way; 19. Sampling distributions; 20. Bayesian vs frequentist hypothesis tests; Part V. Real World Applications: 21. Regression; 22. Inconsistent data; 23. Unrecognized signal contributions; 24. Change point problems; 25. Function estimation; 26. Integral equations; 27. Model selection; 28. Bayesian experimental design; Part VI. Probabilistic Numerical Techniques: 29. Numerical integration; 30. Monte Carlo methods; 31. Nested sampling; Appendixes; References; Index.
Space Shuttle RTOS Bayesian Network
Morris, A. Terry; Beling, Peter A.
2001-01-01
With shrinking budgets and the requirements to increase reliability and operational life of the existing orbiter fleet, NASA has proposed various upgrades for the Space Shuttle that are consistent with national space policy. The cockpit avionics upgrade (CAU), a high priority item, has been selected as the next major upgrade. The primary functions of cockpit avionics include flight control, guidance and navigation, communication, and orbiter landing support. Secondary functions include the provision of operational services for non-avionics systems such as data handling for the payloads and caution and warning alerts to the crew. Recently, a process to selection the optimal commercial-off-the-shelf (COTS) real-time operating system (RTOS) for the CAU was conducted by United Space Alliance (USA) Corporation, which is a joint venture between Boeing and Lockheed Martin, the prime contractor for space shuttle operations. In order to independently assess the RTOS selection, NASA has used the Bayesian network-based scoring methodology described in this paper. Our two-stage methodology addresses the issue of RTOS acceptability by incorporating functional, performance and non-functional software measures related to reliability, interoperability, certifiability, efficiency, correctness, business, legal, product history, cost and life cycle. The first stage of the methodology involves obtaining scores for the various measures using a Bayesian network. The Bayesian network incorporates the causal relationships between the various and often competing measures of interest while also assisting the inherently complex decision analysis process with its ability to reason under uncertainty. The structure and selection of prior probabilities for the network is extracted from experts in the field of real-time operating systems. Scores for the various measures are computed using Bayesian probability. In the second stage, multi-criteria trade-off analyses are performed between the scores
Salamander Blue-sensitive Cones Lost During Metamorphosis†
Chen, Ying; Znoiko, Sergey; DeGrip, Willem J.; Crouch, Rosalie K.; Ma, Jian-xing
2008-01-01
The tiger salamander lives in shallow water with bright light in the aquatic phase, and in dim tunnels or caves in the terrestrial phase. In the aquatic phase, there are five types of photoreceptors—two types of rods and three types of cones. Our previous studies showed that the green rods and blue-sensitive cones contain the same visual pigment and have the same absorbance spectra; however, the green rods have a larger photon-catch area and thus have higher light sensitivity than the blue-se...
What Do Owls, Salamanders, Flycatchers and Cuckoos Have In Common?
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Musgrave, Maria A. [Los Alamos National Lab. (LANL), Los Alamos, NM (United States). Wildlife Management
2016-09-27
This is an article from the Los Alamos Living magazine. Los Alamos National Laboratory sits on a beautiful and unique landscape that provides important protected habitat to many species, including a few that are federally-listed as threatened or endangered. These species are the Jemez Mountains Salamander, the Mexican Spotted Owl, the Southwestern Willow Flycatcher, the Yellow-billed Cuckoo, and the New Mexico Meadow Jumping Mouse. Part of the job of the Laboratory's wildlife biologists is to survey for these species each year and determine what actions need to be taken if they are found.
Axial dynamics during locomotion in vertebrates lesson from the salamander.
Cabelguen, Jean-Marie; Ijspeert, Auke; Lamarque, Stéphanie; Ryczko, Dimitri
2010-01-01
Much of what we know about the flexibility of the locomotor networks in vertebrates is derived from studies examining the adaptation of limb movements during stepping in various conditions. However, the body movements play important roles during locomotion: they produce the thrust during undulatory locomotion and they help to increase the stride length during legged locomotion. In this chapter, we review our current knowledge about the flexibility in the neuronal circuits controlling the body musculature during locomotion. We focus especially on salamander because, as an amphibian, this animal is able to display a rich repertoire of aquatic and terrestrial locomotor modes.
Directory of Open Access Journals (Sweden)
P.R.C. Nobre
2003-08-01
Full Text Available Growth curves of Nellore cattle were analyzed using body weights measured at ages ranging from 1 day (birth weight to 733 days. Traits considered were birth weight, 10 to 110 days weight, 102 to 202 days weight, 193 to 293 days weight, 283 to 383 days weight, 376 to 476 days weight, 551 to 651 days weight, and 633 to 733 days weight. Two data samples were created: one with 79,849 records from herds that had missing traits and another with 74,601 from herds with no missing traits. Records preadjusted to a fixed age were analyzed by a multiple trait model (MTM, which included the effects of contemporary group, age of dam class, additive direct, additive maternal, and maternal permanent environment. Analyses were carried out by a Bayesian method for all nine traits. The random regression model (RRM included the effects of age of animal, contemporary group, age of dam class, additive direct, permanent environment, additive maternal, and maternal permanent environment. Legendre cubic polynomials were used to describe random effects. MTM estimated covariance components and genetic parameters for birth weight and sequential weights and RRM for all ages. Due to the fact that covariance components based on RRM were inflated for herds with missing traits, MTM should be used and converted to covariance functions.Curvas de crescimento de gado Nelore foram analisadas com base nos pesos corporais coletados do nascer aos 733 dias de idade. As características consideradas foram peso ao nascer e pesos dos 10 aos 110, dos 102 aos 202, dos 193 aos 293, dos 283 aos 383, dos 376 aos 476, dos 467 aos 567, dos 551 aos 651 e dos 633 aos 733 dias de idade. Duas amostras foram geradas: a primeira, constituída de 79.849 medidas, continha dados de rebanhos com informações perdidas, e a segunda, de 74.601 medidas, originou-se de rebanhos com informações completas. Os pesos pré-ajustados para as idades fixas foram analisados por meio de um modelo de características m
Wagner, R.S.; Miller, Mark P.; Crisafulli, Charles; Haig, Susan M.
2005-01-01
The Larch Mountain salamander (Plethodon larselli Burns, 1954) is an endemic species in the Pacific northwestern United States facing threats related to habitat destruction. To facilitate development of conservation strategies, we used DNA sequences and RAPDs (random amplified polymorphic DNA) to examine differences among populations of this species. Phylogenetic analyses of cytochrome b revealed a clade of haplotypes from populations north of the Columbia River derived from a clade containing haplotypes from the river's southwestern region. Haplotypes from southeastern populations formed a separate clade. Nucleotide diversity was reduced in northern populations relative to southern populations. These results were corroborated by analyses of RAPD loci, which revealed similar patterns of clustering and diversity. Network analyses suggested that northern populations were colonized following a range expansion mediated by individuals from populations located southwest of the river. Changes in the Columbia River's location during the Pliocene and Pleistocene likely released distributional constraints on this species, permitting their northern range expansion. Based on the barrier presented by the Columbia River's present location and differences in haplotype diversity and population structure observed between northern and southern populations, we suggest that designation of separate management units encompassing each region may assist with mitigating different threats to this species.
Environmental influences on egg and clutch sizes in lentic- and lotic-breeding salamanders
Directory of Open Access Journals (Sweden)
Jon M. Davenport
2010-12-01
Full Text Available Recent research indicates that social and environmental factors influence egg and clutch sizes in amphibians. However, most of this work is based on the reproductively diverse order Anura (frogs and toads, whereas less research has been conducted on Caudata (salamanders and Gymnophiona (caecilians. Researchers have suggested that a relationship exists between social and environmental factors and egg and clutch sizes in salamanders, but studies controlling for phylogenetic context are lacking. We could not identify a sufficient number of comparisons for social influences on egg and clutch sizes; therefore, we focused on environmental influences for this study. Data on egg size, clutch size, environmental factors, and phylogenies for salamanders were assembled from the scientific literature. We used independent, pair-wise comparisons to investigate the association of larval salamander habitat and egg size and the association of larval salamander habitat with clutch sizes within a phylogenetic framework. There is a significant association between larval habitat and egg size; specifically, stream-breeding species produce larger eggs. There is no significant association between larval habitat and clutchsize. Our study confirms earlier reports that salamander egg size is associated with larval environments, but is the first to use phylogenetically independent contrasts to account for the lack of phylogenetic independence of the traits measured (egg size and clutch size associated with many of the diverse lineages. Our study shows that environmental selection pressure can be quite strong on one aspect of salamander reproduction—egg size.
DeGross, Douglas J.; Bury, R. Bruce
2007-01-01
The Plethodon elongatus Complex in the Klamath-Siskiyou Ecoregion of southern Oregon and northern California includes three species: the Del Norte salamander, Plethodon elongatus; the Siskiyou Mountains salamander, P. stormi; and the Scott Bar salamander, P. asupak. This review aims to summarize the current literature and information available on select topics for P. stormi and P. asupak. These are both terrestrial salamanders belonging to the Family Plethodontidae, which contains more species and has a wider geographic distribution than any other family of salamanders (Wake 1966, 2006; Pough 1989). The genera of this family have greatly diversified ecologically across North America, Central America, northern South America, Sardinia, southeastern France and northwestern Italy, and have recently been discovered on the Korean peninsula (Min et al. 2005). The genus Plethodon is found exclusively in North America and is split into three distinct clades, based upon morphology and phylogenetics (Highton and Larson 1979): eastern small Plethodon, eastern large Plethodon, and the western Plethodon. The western Plethodon are the greatest representation of Plethodontidae in the Pacific Northwest, with 8 species. The two species with the most restricted ranges of these regional congeners are the Siskiyou Mountains and Scott Bar salamanders. These salamanders occupy the interior of the Klamath-Siskiyou Ecoregion which straddles the California and Oregon state lines, between Siskiyou County (CA) and Jackson and Josephine Counties (OR). The relatively recent discovery of P. asupak (Mead et al. 2005) and the limited range of both species have created an environment of uncertain conservation status for these species. This review will focus on four central topics of concern for land and resource managers: Biology; Taxonomy; Habitat; and Detection Probabilities/Occupancy.
Road deicing salt irreversibly disrupts osmoregulation of salamander egg clutches
Energy Technology Data Exchange (ETDEWEB)
Karraker, Nancy E., E-mail: karraker@hku.hk [Department of Environmental and Forest Biology, State University of New York, College of Environmental Science and Forestry, Syracuse, NY 13210 (United States); Gibbs, James P. [Department of Environmental and Forest Biology, State University of New York, College of Environmental Science and Forestry, Syracuse, NY 13210 (United States)
2011-03-15
It has been postulated that road deicing salts are sufficiently diluted by spring rains to ameliorate any physiological impacts to amphibians breeding in wetlands near roads. We tested this conjecture by exposing clutches of the spotted salamander (Ambystoma maculatum) to three chloride concentrations (1 mg/L, 145 mg/L, 945 mg/L) for nine days, then transferred clutches to control water for nine days, and measured change in mass at three-day intervals. We measured mass change because water uptake by clutches reduces risks to embryos associated with freezing, predation, and disease. Clutches in controls sequestered water asymptotically. Those in the moderate concentrations lost 18% mass initially and regained 14% after transfer to control water. Clutches in high concentration lost 33% mass and then lost an additional 8% after transfer. Our results suggest that spring rains do not ameliorate the effects of deicing salts in wetlands with extremely high chloride concentrations. - Road deicing salts irreversibly disrupts osmoregulation of salamander egg clutches.
Granade, Christopher; Cory, D G
2015-01-01
In recent years, Bayesian methods have been proposed as a solution to a wide range of issues in quantum state and process tomography. State-of- the-art Bayesian tomography solutions suffer from three problems: numerical intractability, a lack of informative prior distributions, and an inability to track time-dependent processes. Here, we solve all three problems. First, we use modern statistical methods, as pioneered by Husz\\'ar and Houlsby and by Ferrie, to make Bayesian tomography numerically tractable. Our approach allows for practical computation of Bayesian point and region estimators for quantum states and channels. Second, we propose the first informative priors on quantum states and channels. Finally, we develop a method that allows online tracking of time-dependent states and estimates the drift and diffusion processes affecting a state. We provide source code and animated visual examples for our methods.
Noncausal Bayesian Vector Autoregression
DEFF Research Database (Denmark)
Lanne, Markku; Luoto, Jani
We propose a Bayesian inferential procedure for the noncausal vector autoregressive (VAR) model that is capable of capturing nonlinearities and incorporating effects of missing variables. In particular, we devise a fast and reliable posterior simulator that yields the predictive distribution...
Bayesian Lensing Shear Measurement
Bernstein, Gary M
2013-01-01
We derive an estimator of weak gravitational lensing shear from background galaxy images that avoids noise-induced biases through a rigorous Bayesian treatment of the measurement. The Bayesian formalism requires a prior describing the (noiseless) distribution of the target galaxy population over some parameter space; this prior can be constructed from low-noise images of a subsample of the target population, attainable from long integrations of a fraction of the survey field. We find two ways to combine this exact treatment of noise with rigorous treatment of the effects of the instrumental point-spread function and sampling. The Bayesian model fitting (BMF) method assigns a likelihood of the pixel data to galaxy models (e.g. Sersic ellipses), and requires the unlensed distribution of galaxies over the model parameters as a prior. The Bayesian Fourier domain (BFD) method compresses galaxies to a small set of weighted moments calculated after PSF correction in Fourier space. It requires the unlensed distributi...
An introduction to Gaussian Bayesian networks.
Grzegorczyk, Marco
2010-01-01
The extraction of regulatory networks and pathways from postgenomic data is important for drug -discovery and development, as the extracted pathways reveal how genes or proteins regulate each other. Following up on the seminal paper of Friedman et al. (J Comput Biol 7:601-620, 2000), Bayesian networks have been widely applied as a popular tool to this end in systems biology research. Their popularity stems from the tractability of the marginal likelihood of the network structure, which is a consistent scoring scheme in the Bayesian context. This score is based on an integration over the entire parameter space, for which highly expensive computational procedures have to be applied when using more complex -models based on differential equations; for example, see (Bioinformatics 24:833-839, 2008). This chapter gives an introduction to reverse engineering regulatory networks and pathways with Gaussian Bayesian networks, that is Bayesian networks with the probabilistic BGe scoring metric [see (Geiger and Heckerman 235-243, 1995)]. In the BGe model, the data are assumed to stem from a Gaussian distribution and a normal-Wishart prior is assigned to the unknown parameters. Gaussian Bayesian network methodology for analysing static observational, static interventional as well as dynamic (observational) time series data will be described in detail in this chapter. Finally, we apply these Bayesian network inference methods (1) to observational and interventional flow cytometry (protein) data from the well-known RAF pathway to evaluate the global network reconstruction accuracy of Bayesian network inference and (2) to dynamic gene expression time series data of nine circadian genes in Arabidopsis thaliana to reverse engineer the unknown regulatory network topology for this domain. PMID:20824469
Malicious Bayesian Congestion Games
Gairing, Martin
2008-01-01
In this paper, we introduce malicious Bayesian congestion games as an extension to congestion games where players might act in a malicious way. In such a game each player has two types. Either the player is a rational player seeking to minimize her own delay, or - with a certain probability - the player is malicious in which case her only goal is to disturb the other players as much as possible. We show that such games do in general not possess a Bayesian Nash equilibrium in pure strategies (i.e. a pure Bayesian Nash equilibrium). Moreover, given a game, we show that it is NP-complete to decide whether it admits a pure Bayesian Nash equilibrium. This result even holds when resource latency functions are linear, each player is malicious with the same probability, and all strategy sets consist of singleton sets. For a slightly more restricted class of malicious Bayesian congestion games, we provide easy checkable properties that are necessary and sufficient for the existence of a pure Bayesian Nash equilibrium....
Dynamic Bayesian Combination of Multiple Imperfect Classifiers
Simpson, Edwin; Psorakis, Ioannis; Smith, Arfon
2012-01-01
Classifier combination methods need to make best use of the outputs of multiple, imperfect classifiers to enable higher accuracy classifications. In many situations, such as when human decisions need to be combined, the base decisions can vary enormously in reliability. A Bayesian approach to such uncertain combination allows us to infer the differences in performance between individuals and to incorporate any available prior knowledge about their abilities when training data is sparse. In this paper we explore Bayesian classifier combination, using the computationally efficient framework of variational Bayesian inference. We apply the approach to real data from a large citizen science project, Galaxy Zoo Supernovae, and show that our method far outperforms other established approaches to imperfect decision combination. We go on to analyse the putative community structure of the decision makers, based on their inferred decision making strategies, and show that natural groupings are formed. Finally we present ...
Bayesian inference of the metazoan phylogeny
DEFF Research Database (Denmark)
Glenner, Henrik; Hansen, Anders J; Sørensen, Martin V;
2004-01-01
been the only feasible combined approach but is highly sensitive to long-branch attraction. Recent development of stochastic models for discrete morphological characters and computationally efficient methods for Bayesian inference has enabled combined molecular and morphological data analysis...... with rigorous statistical approaches less prone to such inconsistencies. We present the first statistically founded analysis of a metazoan data set based on a combination of morphological and molecular data and compare the results with a traditional parsimony analysis. Interestingly, the Bayesian analyses...... such as the ecdysozoans and lophotrochozoans. Parsimony, on the contrary, shows conflicting results, with morphology being congruent to the Bayesian results and the molecular data set producing peculiarities that are largely reflected in the combined analysis....
Cheat Mountain Salamander coverboard data analysis Canaan Valley National Wildlife Refuge
US Fish and Wildlife Service, Department of the Interior — From 2000 to 2008 data was collected from three Cheat Mountain salamander coverboard sites at Canaan Valley National Wildlife Refuge: Cabin Knob A, Cabin Knob B,...
US Fish and Wildlife Service, Department of the Interior — Aquatic habitat of the endangered Barton Springs salamander, Eurycea sosorum, in Travis County, Texas can potentially be impacted by contaminants in surface runoff...
Regulatory agencies need rapid indicators of hydrologic permanence for jurisdictional determinations of headwater streams. Our study objective was to assess the utility of larval salamander presence and assemblage structure and habitat variables for determining stream permanence ...
Water and sediment quality in habitat springs of Edwards Aquifer salamanders
US Fish and Wildlife Service, Department of the Interior — Many springs associated with the Edwards Aquifer of Texas are inhabited by relict populations of neotenic salamanders in the genus Eurycea. This study was done to...
Egg predators of an endemic Italian salamander, Salamandrina perspicillata (Savi, 1821
Directory of Open Access Journals (Sweden)
Antonio Romano
2008-05-01
Full Text Available We report new aquatic predators feeding on Northern spectacled salamander eggs, Salamandrina perspicillata, an endemic Italian species. Eggs were preyed upon by the leech, Trocheta bykowskii, and the trichopteran larvae of Potamophylax cingulatus and Halesus appenninus.
Salamander võib õpetada jäsemete kasvatamist / Tiit Kändler
Kändler, Tiit, 1948-
2008-01-01
Salamander on selgroogsete seas ainulaadne olevus. Ta suudab endale kasvatada ka täiskasvanuna uued kehaosad. Kui arstiteadlased välja uurivad, kuidas ta seda teeb, võib see aidata ka inimest rasketest haavadest ravida
Reintroduction and Post-Release Survival of a Living Fossil: The Chinese Giant Salamander.
Zhang, Lu; Jiang, Wei; Wang, Qi-Jun; Zhao, Hu; Zhang, Hong-Xing; Marcec, Ruth M; Willard, Scott T; Kouba, Andrew J
2016-01-01
Captive rearing and reintroduction / translocation are increasingly used as tools to supplement wild populations of threatened species. Reintroducing captive-reared Chinese giant salamanders may help to augment the declining wild populations and conserve this critically endangered amphibian. We released 31 captive-reared juvenile giant salamanders implanted with VHF radio transmitters at the Heihe River (n = 15) and the Donghe River (n = 16) in the Qinling Mountains of central China. Salamanders were monitored every day for survival from April 28th 2013 to September 3rd 2014. We attempted to recapture all living individuals by the end of the study, measured their body mass and total body length, and checked for abnormalities and presence of external parasites. Two salamanders at the Heihe River and 10 animals at the Donghe River survived through the project timeline. Nine salamanders were confirmed dead, while the status of the other 10 animals was undetermined. The annual survival rate of giant salamanders at the Donghe River (0.702) was 1.7-fold higher than that at the Heihe River (0.405). Survival increased as individuals were held longer following surgery, whereas body mass did not have a significant impact on survival rate. All salamanders recaptured from the Donghe River (n = 8) increased in mass (0.50 ± 0.13 kg) and length (5.5 ± 1.5 cm) after approximately 11 months in the wild, and they were only 7% lighter than wild animals of the same length (mean residual = -0.033 ± 0.025). Our results indicate that captive-reared Chinese giant salamanders can survive in the wild one year after release and adequate surgical recovery time is extremely important to post-release survival. Future projects may reintroduce older juveniles to achieve better survival and longer monitoring duration.
Reintroduction and Post-Release Survival of a Living Fossil: The Chinese Giant Salamander.
Directory of Open Access Journals (Sweden)
Lu Zhang
Full Text Available Captive rearing and reintroduction / translocation are increasingly used as tools to supplement wild populations of threatened species. Reintroducing captive-reared Chinese giant salamanders may help to augment the declining wild populations and conserve this critically endangered amphibian. We released 31 captive-reared juvenile giant salamanders implanted with VHF radio transmitters at the Heihe River (n = 15 and the Donghe River (n = 16 in the Qinling Mountains of central China. Salamanders were monitored every day for survival from April 28th 2013 to September 3rd 2014. We attempted to recapture all living individuals by the end of the study, measured their body mass and total body length, and checked for abnormalities and presence of external parasites. Two salamanders at the Heihe River and 10 animals at the Donghe River survived through the project timeline. Nine salamanders were confirmed dead, while the status of the other 10 animals was undetermined. The annual survival rate of giant salamanders at the Donghe River (0.702 was 1.7-fold higher than that at the Heihe River (0.405. Survival increased as individuals were held longer following surgery, whereas body mass did not have a significant impact on survival rate. All salamanders recaptured from the Donghe River (n = 8 increased in mass (0.50 ± 0.13 kg and length (5.5 ± 1.5 cm after approximately 11 months in the wild, and they were only 7% lighter than wild animals of the same length (mean residual = -0.033 ± 0.025. Our results indicate that captive-reared Chinese giant salamanders can survive in the wild one year after release and adequate surgical recovery time is extremely important to post-release survival. Future projects may reintroduce older juveniles to achieve better survival and longer monitoring duration.
Reintroduction and Post-Release Survival of a Living Fossil: The Chinese Giant Salamander
Zhang, Lu; Jiang, Wei; Wang, Qi-Jun; Zhao, Hu; Zhang, Hong-Xing; Marcec, Ruth M.; Willard, Scott T.; Kouba, Andrew J.
2016-01-01
Captive rearing and reintroduction / translocation are increasingly used as tools to supplement wild populations of threatened species. Reintroducing captive-reared Chinese giant salamanders may help to augment the declining wild populations and conserve this critically endangered amphibian. We released 31 captive-reared juvenile giant salamanders implanted with VHF radio transmitters at the Heihe River (n = 15) and the Donghe River (n = 16) in the Qinling Mountains of central China. Salamanders were monitored every day for survival from April 28th 2013 to September 3rd 2014. We attempted to recapture all living individuals by the end of the study, measured their body mass and total body length, and checked for abnormalities and presence of external parasites. Two salamanders at the Heihe River and 10 animals at the Donghe River survived through the project timeline. Nine salamanders were confirmed dead, while the status of the other 10 animals was undetermined. The annual survival rate of giant salamanders at the Donghe River (0.702) was 1.7-fold higher than that at the Heihe River (0.405). Survival increased as individuals were held longer following surgery, whereas body mass did not have a significant impact on survival rate. All salamanders recaptured from the Donghe River (n = 8) increased in mass (0.50 ± 0.13 kg) and length (5.5 ± 1.5 cm) after approximately 11 months in the wild, and they were only 7% lighter than wild animals of the same length (mean residual = -0.033 ± 0.025). Our results indicate that captive-reared Chinese giant salamanders can survive in the wild one year after release and adequate surgical recovery time is extremely important to post-release survival. Future projects may reintroduce older juveniles to achieve better survival and longer monitoring duration. PMID:27258650
Using a GIS model to assess terrestrial salamander response to alternative forest management plans.
Gustafson, E J; Murphy, N L; Crow, T R
2001-11-01
A GIS model predicting the spatial distribution of terrestrial salamander abundance based on topography and forest age was developed using parameters derived from the literature. The model was tested by sampling salamander abundance across the full range of site conditions used in the model. A regression of the predictions of our GIS model against these sample data showed that the model has a modest but significant ability to predict both salamander abundance and mass per unit area. The model was used to assess the impacts of alternative management plans for the Hoosier National Forest (Indiana, USA) on salamanders. These plans differed in the spatial delineation of management areas where timber harvest was permitted, and the intensity of timber harvest within those management areas. The spatial pattern of forest openings produced by alternative forest management scenarios based on these plans was projected over 150 years using a timber-harvest simulator (HARVEST). We generated a predictive map of salamander abundance for each scenario over time, and summarized each map by calculating mean salamander abundance and the mean colonization distance (average distance from map cells with low predicted abundance to those with relatively high abundance). Projected salamander abundance was affected more by harvest rate (area harvested each decade) than by the management area boundaries. The alternatives had a varying effect on the mean distance salamanders would have to travel to colonize regenerating stands. Our GIS modeling approach is an example of a spatial analytical tool that could help resource management planners to evaluate the potential ecological impact of management alternatives. PMID:11775500
Reintroduction and Post-Release Survival of a Living Fossil: The Chinese Giant Salamander.
Zhang, Lu; Jiang, Wei; Wang, Qi-Jun; Zhao, Hu; Zhang, Hong-Xing; Marcec, Ruth M; Willard, Scott T; Kouba, Andrew J
2016-01-01
Captive rearing and reintroduction / translocation are increasingly used as tools to supplement wild populations of threatened species. Reintroducing captive-reared Chinese giant salamanders may help to augment the declining wild populations and conserve this critically endangered amphibian. We released 31 captive-reared juvenile giant salamanders implanted with VHF radio transmitters at the Heihe River (n = 15) and the Donghe River (n = 16) in the Qinling Mountains of central China. Salamanders were monitored every day for survival from April 28th 2013 to September 3rd 2014. We attempted to recapture all living individuals by the end of the study, measured their body mass and total body length, and checked for abnormalities and presence of external parasites. Two salamanders at the Heihe River and 10 animals at the Donghe River survived through the project timeline. Nine salamanders were confirmed dead, while the status of the other 10 animals was undetermined. The annual survival rate of giant salamanders at the Donghe River (0.702) was 1.7-fold higher than that at the Heihe River (0.405). Survival increased as individuals were held longer following surgery, whereas body mass did not have a significant impact on survival rate. All salamanders recaptured from the Donghe River (n = 8) increased in mass (0.50 ± 0.13 kg) and length (5.5 ± 1.5 cm) after approximately 11 months in the wild, and they were only 7% lighter than wild animals of the same length (mean residual = -0.033 ± 0.025). Our results indicate that captive-reared Chinese giant salamanders can survive in the wild one year after release and adequate surgical recovery time is extremely important to post-release survival. Future projects may reintroduce older juveniles to achieve better survival and longer monitoring duration. PMID:27258650
Computational statistics using the bBayesian Inference Engine
Weinberg, Martin D
2012-01-01
This paper introduces the Bayesian Inference Engine (BIE), a general parallel-optimised software package for parameter inference and model selection. This package is motivated by the analysis needs of modern astronomical surveys and the need to organise and reuse expensive derived data. I describe key concepts that illustrate the power of Bayesian inference to address these needs and outline the computational challenge. The techniques presented are based on experience gained in modelling star-counts and stellar populations, analysing the morphology of galaxy images, and performing Bayesian investigations of semi-analytic models of galaxy formation. These inference problems require advanced Markov chain Monte Carlo (MCMC) algorithms that expedite sampling, mixing, and the analysis of the Bayesian posterior distribution. The BIE was designed to be a collaborative platform for applying Bayesian methodology to astronomy. By providing a variety of statistical algorithms for all phases of the inference problem, a u...
Chevallier, Stéphanie; Jan Ijspeert, Auke; Ryczko, Dimitri; Nagy, Frédéric; Cabelguen, Jean-Marie
2008-01-01
Among living tetrapods, salamanders are regarded as most closely resembling the first terrestrial vertebrates, and are therefore an interesting group in which the evolutionary changes in the locomotor behaviour from aquatic to terrestrial habitats can be inferred. Salamanders exhibit two locomotor modes: swimming and terrestrial stepping. The swimming is anguilliform and resembles closely that of the lamprey. On the ground, the salamander switches to a stepping gait with axial undulations that is also observed in many reptiles. The salamander is therefore ideally suited for examining the neural mechanisms for the generation of these two locomotor modes, as well as the neural mechanisms of gait transition. In the present paper, we describe the kinematics and patterns of activation of axial and limb muscles during stepping and swimming in adult salamanders. We then review the current neurobiological data about the organisation of the spinal networks underlying swimming and stepping, and the mechanisms of gait transition. Finally we report modelling studies aimed at understanding the organisation and operation of the salamander locomotor circuits. Altogether, the neurobiological and the modelling data support the hypothesis of a phylogenetic conservatism from agnathians to amphibians of the spinal locomotor networks generating axial motor patterns.
A re-examination and re-evaluation of salamander orbital glands.
Rehorek, Susan J; Grand-Pierre, Alix E; Cummings, Joshua R; Jewell, Bridgette; Constantine, Julieanne; Hillenius, W Jaap
2013-11-01
The amphibian integument contains numerous multicellular glands. Although two of these, the nasolabial and orbital glands and the associated nasolacrimal duct (NLD), have historically received considerable attention, interpretation of the original observations can be problematic in the context of current literature. Salamanders, in particular, are frequently regarded as at least indicative of aspects of the morphology of the common ancestor to all extant tetrapods; hence, an understanding of these glands in salamanders might prove to be informative about their evolution. For this study, the orbitonasal region of salamanders from three families was histologically examined. Three themes emerged: (1) examination of the effect of phylogeny on the nasolabial gland and NLD revealed a combination of features that may be unique to plethodontid salamanders, and may be correlated to their nose-tapping behavior by which substances are moved into the vomeronasal organ; (2) ecology appears to impact the relative development of the orbital glands, but not necessarily the nasolabial gland, with smaller glands being present in the aquatic species; (3) the nomenclature of the salamander orbital gland remains problematic, especially in light of comparative studies, as several alternate possibilities are viable. From this nomenclatural conundrum, however, it could be concluded that there may be a global pattern in the location of tetrapod orbital gland development. Molecular questions in terms of ontogeny and genetic homology affect the nature of the debate on orbital gland nomenclature. These observations suggest that rather than reflecting an ancestral condition, salamanders may instead represent a case of specialized, convergent evolution. PMID:24106029
Bayesian phylogeography finds its roots.
Directory of Open Access Journals (Sweden)
Philippe Lemey
2009-09-01
Full Text Available As a key factor in endemic and epidemic dynamics, the geographical distribution of viruses has been frequently interpreted in the light of their genetic histories. Unfortunately, inference of historical dispersal or migration patterns of viruses has mainly been restricted to model-free heuristic approaches that provide little insight into the temporal setting of the spatial dynamics. The introduction of probabilistic models of evolution, however, offers unique opportunities to engage in this statistical endeavor. Here we introduce a Bayesian framework for inference, visualization and hypothesis testing of phylogeographic history. By implementing character mapping in a Bayesian software that samples time-scaled phylogenies, we enable the reconstruction of timed viral dispersal patterns while accommodating phylogenetic uncertainty. Standard Markov model inference is extended with a stochastic search variable selection procedure that identifies the parsimonious descriptions of the diffusion process. In addition, we propose priors that can incorporate geographical sampling distributions or characterize alternative hypotheses about the spatial dynamics. To visualize the spatial and temporal information, we summarize inferences using virtual globe software. We describe how Bayesian phylogeography compares with previous parsimony analysis in the investigation of the influenza A H5N1 origin and H5N1 epidemiological linkage among sampling localities. Analysis of rabies in West African dog populations reveals how virus diffusion may enable endemic maintenance through continuous epidemic cycles. From these analyses, we conclude that our phylogeographic framework will make an important asset in molecular epidemiology that can be easily generalized to infer biogeogeography from genetic data for many organisms.
Institute of Scientific and Technical Information of China (English)
闫放; 许开立; 姚锡文; 王文菁
2015-01-01
Fussell-Vesely worth of each event is calculated by Bayesian network .Prevention measures are adopted to the reason event with higher worth .The event tree analysis is conducted to determine control measures and calculate the probability of biomass gasification poisoning accidents before and after measures are taken .Finally the biomass gasification poisoning acci-dents after using bow-tie analysis based on Bayesian network are evaluated by risk assessment matrix .As the result ,this method can reduce probability and risk of accidents by adopting safety measures to parts of the whole points of the system .%本文通过贝叶斯网络计算各原因事件的弗塞－维思利重要度，选取重要度较高的原因事件采取预防措施；并通过事件树分析确定控制措施，计算采取措施前后生物质气化中毒事故发生的概率，最后通过危险性评价矩阵对采取基于贝叶斯网络的bow－tie分析后的生物质气化中毒事故风险进行评价。结果表明，采用该方法只需对系统中部分节点采取安全措施即可有效降低事故发生概率，从而降低事故风险。
Deep divergences and extensive phylogeographic structure in a clade of lowland tropical salamanders
Directory of Open Access Journals (Sweden)
Rovito Sean M
2012-12-01
Full Text Available Abstract Background The complex geological history of Mesoamerica provides the opportunity to study the impact of multiple biogeographic barriers on population differentiation. We examine phylogeographic patterns in a clade of lowland salamanders (Bolitoglossa subgenus Nanotriton using two mitochondrial genes and one nuclear gene. We use several phylogeographic analyses to infer the history of this clade and test hypotheses regarding the geographic origin of species and location of genetic breaks within species. We compare our results to those for other taxa to determine if historical events impacted different species in a similar manner. Results Deep genetic divergence between species indicates that they are relatively old, and two of the three widespread species show strong phylogeographic structure. Comparison of mtDNA and nuclear gene trees shows no evidence of hybridization or introgression between species. Isolated populations of Bolitoglossa rufescens from Los Tuxtlas region constitute a separate lineage based on molecular data and morphology, and divergence between Los Tuxtlas and other areas appears to predate the arrival of B. rufescens in other areas west of the Isthmus of Tehuantepec. The Isthmus appears responsible for Pliocene vicariance within B. rufescens, as has been shown for other taxa. The Motagua-Polochic fault system does not appear to have caused population vicariance, unlike in other systems. Conclusions Species of Nanotriton have responded to some major geological events in the same manner as other taxa, particularly in the case of the Isthmus of Tehuantepec. The deep divergence of the Los Tuxtlas populations of B. rufescens from other populations highlights the contribution of this volcanic system to patterns of regional endemism, and morphological differences observed in the Los Tuxtlas populations suggests that they may represent an undescribed species of Bolitoglossa. The absence of phylogeographic structure in B
Directory of Open Access Journals (Sweden)
Rachael Y Dudaniec
Full Text Available With predicted decreases in genetic diversity and greater genetic differentiation at range peripheries relative to their cores, it can be difficult to distinguish between the roles of current disturbance versus historic processes in shaping contemporary genetic patterns. To address this problem, we test for differences in historic demography and landscape genetic structure of coastal giant salamanders (Dicamptodon tenebrosus in two core regions (Washington State, United States versus the species' northern peripheral region (British Columbia, Canada where the species is listed as threatened. Coalescent-based demographic simulations were consistent with a pattern of post-glacial range expansion, with both ancestral and current estimates of effective population size being much larger within the core region relative to the periphery. However, contrary to predictions of recent human-induced population decline in the less genetically diverse peripheral region, there was no genetic signature of population size change. Effects of current demographic processes on genetic structure were evident using a resistance-based landscape genetics approach. Among core populations, genetic structure was best explained by length of the growing season and isolation by resistance (i.e. a 'flat' landscape, but at the periphery, topography (slope and elevation had the greatest influence on genetic structure. Although reduced genetic variation at the range periphery of D. tenebrosus appears to be largely the result of biogeographical history rather than recent impacts, our analyses suggest that inherent landscape features act to alter dispersal pathways uniquely in different parts of the species' geographic range, with implications for habitat management.
Bayesian least squares deconvolution
Ramos, A Asensio
2015-01-01
Aims. To develop a fully Bayesian least squares deconvolution (LSD) that can be applied to the reliable detection of magnetic signals in noise-limited stellar spectropolarimetric observations using multiline techniques. Methods. We consider LSD under the Bayesian framework and we introduce a flexible Gaussian Process (GP) prior for the LSD profile. This prior allows the result to automatically adapt to the presence of signal. We exploit several linear algebra identities to accelerate the calculations. The final algorithm can deal with thousands of spectral lines in a few seconds. Results. We demonstrate the reliability of the method with synthetic experiments and we apply it to real spectropolarimetric observations of magnetic stars. We are able to recover the magnetic signals using a small number of spectral lines, together with the uncertainty at each velocity bin. This allows the user to consider if the detected signal is reliable. The code to compute the Bayesian LSD profile is freely available.
Bayesian least squares deconvolution
Asensio Ramos, A.; Petit, P.
2015-11-01
Aims: We develop a fully Bayesian least squares deconvolution (LSD) that can be applied to the reliable detection of magnetic signals in noise-limited stellar spectropolarimetric observations using multiline techniques. Methods: We consider LSD under the Bayesian framework and we introduce a flexible Gaussian process (GP) prior for the LSD profile. This prior allows the result to automatically adapt to the presence of signal. We exploit several linear algebra identities to accelerate the calculations. The final algorithm can deal with thousands of spectral lines in a few seconds. Results: We demonstrate the reliability of the method with synthetic experiments and we apply it to real spectropolarimetric observations of magnetic stars. We are able to recover the magnetic signals using a small number of spectral lines, together with the uncertainty at each velocity bin. This allows the user to consider if the detected signal is reliable. The code to compute the Bayesian LSD profile is freely available.
Hybrid Batch Bayesian Optimization
Azimi, Javad; Fern, Xiaoli
2012-01-01
Bayesian Optimization aims at optimizing an unknown non-convex/concave function that is costly to evaluate. We are interested in application scenarios where concurrent function evaluations are possible. Under such a setting, BO could choose to either sequentially evaluate the function, one input at a time and wait for the output of the function before making the next selection, or evaluate the function at a batch of multiple inputs at once. These two different settings are commonly referred to as the sequential and batch settings of Bayesian Optimization. In general, the sequential setting leads to better optimization performance as each function evaluation is selected with more information, whereas the batch setting has an advantage in terms of the total experimental time (the number of iterations). In this work, our goal is to combine the strength of both settings. Specifically, we systematically analyze Bayesian optimization using Gaussian process as the posterior estimator and provide a hybrid algorithm t...
Loredo, T J
2004-01-01
I describe a framework for adaptive scientific exploration based on iterating an Observation--Inference--Design cycle that allows adjustment of hypotheses and observing protocols in response to the results of observation on-the-fly, as data are gathered. The framework uses a unified Bayesian methodology for the inference and design stages: Bayesian inference to quantify what we have learned from the available data and predict future data, and Bayesian decision theory to identify which new observations would teach us the most. When the goal of the experiment is simply to make inferences, the framework identifies a computationally efficient iterative ``maximum entropy sampling'' strategy as the optimal strategy in settings where the noise statistics are independent of signal properties. Results of applying the method to two ``toy'' problems with simulated data--measuring the orbit of an extrasolar planet, and locating a hidden one-dimensional object--show the approach can significantly improve observational eff...
Bayesian Exploratory Factor Analysis
DEFF Research Database (Denmark)
Conti, Gabriella; Frühwirth-Schnatter, Sylvia; Heckman, James J.;
2014-01-01
This paper develops and applies a Bayesian approach to Exploratory Factor Analysis that improves on ad hoc classical approaches. Our framework relies on dedicated factor models and simultaneously determines the number of factors, the allocation of each measurement to a unique factor, and the corr......This paper develops and applies a Bayesian approach to Exploratory Factor Analysis that improves on ad hoc classical approaches. Our framework relies on dedicated factor models and simultaneously determines the number of factors, the allocation of each measurement to a unique factor......, and the corresponding factor loadings. Classical identification criteria are applied and integrated into our Bayesian procedure to generate models that are stable and clearly interpretable. A Monte Carlo study confirms the validity of the approach. The method is used to produce interpretable low dimensional aggregates...
Bayesian multiple target tracking
Streit, Roy L
2013-01-01
This second edition has undergone substantial revision from the 1999 first edition, recognizing that a lot has changed in the multiple target tracking field. One of the most dramatic changes is in the widespread use of particle filters to implement nonlinear, non-Gaussian Bayesian trackers. This book views multiple target tracking as a Bayesian inference problem. Within this framework it develops the theory of single target tracking, multiple target tracking, and likelihood ratio detection and tracking. In addition to providing a detailed description of a basic particle filter that implements
Bayesian and frequentist inequality tests
David M. Kaplan; Zhuo, Longhao
2016-01-01
Bayesian and frequentist criteria are fundamentally different, but often posterior and sampling distributions are asymptotically equivalent (and normal). We compare Bayesian and frequentist hypothesis tests of inequality restrictions in such cases. For finite-dimensional parameters, if the null hypothesis is that the parameter vector lies in a certain half-space, then the Bayesian test has (frequentist) size $\\alpha$; if the null hypothesis is any other convex subspace, then the Bayesian test...
Bayesian Analysis of Individual Level Personality Dynamics
Directory of Open Access Journals (Sweden)
Edward Cripps
2016-07-01
Full Text Available A Bayesian technique with analyses of within-person processes at the level of the individual is presented. The approach is used to examine if the patterns of within-person responses on a 12 trial simulation task are consistent with the predictions of ITA theory (Dweck, 1999. ITA theory states that the performance of an individual with an entity theory of ability is more likely to spiral down following a failure experience than the performance of an individual with an incremental theory of ability. This is because entity theorists interpret failure experiences as evidence of a lack of ability, which they believe is largely innate and therefore relatively ﬁxed; whilst incremental theorists believe in the malleability of abilities and interpret failure experiences as evidence of more controllable factors such as poor strategy or lack of effort. The results of our analyses support ITA theory at both the within- and between-person levels of analyses and demonstrate the beneﬁts of Bayesian techniques for the analysis of within-person processes. These include more formal speciﬁcation of the theory and the ability to draw inferences about each individual, which allows for more nuanced interpretations of individuals within a personality category, such as differences in the individual probabilities of spiralling. While Bayesian techniques have many potential advantages for the analyses of within-person processes at the individual level, ease of use is not one of them for psychologists trained in traditional frequentist statistical techniques.
Bayesian Analysis of Individual Level Personality Dynamics
Cripps, Edward; Wood, Robert E.; Beckmann, Nadin; Lau, John; Beckmann, Jens F.; Cripps, Sally Ann
2016-01-01
A Bayesian technique with analyses of within-person processes at the level of the individual is presented. The approach is used to examine whether the patterns of within-person responses on a 12-trial simulation task are consistent with the predictions of ITA theory (Dweck, 1999). ITA theory states that the performance of an individual with an entity theory of ability is more likely to spiral down following a failure experience than the performance of an individual with an incremental theory of ability. This is because entity theorists interpret failure experiences as evidence of a lack of ability which they believe is largely innate and therefore relatively fixed; whilst incremental theorists believe in the malleability of abilities and interpret failure experiences as evidence of more controllable factors such as poor strategy or lack of effort. The results of our analyses support ITA theory at both the within- and between-person levels of analyses and demonstrate the benefits of Bayesian techniques for the analysis of within-person processes. These include more formal specification of the theory and the ability to draw inferences about each individual, which allows for more nuanced interpretations of individuals within a personality category, such as differences in the individual probabilities of spiraling. While Bayesian techniques have many potential advantages for the analyses of processes at the level of the individual, ease of use is not one of them for psychologists trained in traditional frequentist statistical techniques. PMID:27486415
Bayesian Analysis of Individual Level Personality Dynamics.
Cripps, Edward; Wood, Robert E; Beckmann, Nadin; Lau, John; Beckmann, Jens F; Cripps, Sally Ann
2016-01-01
A Bayesian technique with analyses of within-person processes at the level of the individual is presented. The approach is used to examine whether the patterns of within-person responses on a 12-trial simulation task are consistent with the predictions of ITA theory (Dweck, 1999). ITA theory states that the performance of an individual with an entity theory of ability is more likely to spiral down following a failure experience than the performance of an individual with an incremental theory of ability. This is because entity theorists interpret failure experiences as evidence of a lack of ability which they believe is largely innate and therefore relatively fixed; whilst incremental theorists believe in the malleability of abilities and interpret failure experiences as evidence of more controllable factors such as poor strategy or lack of effort. The results of our analyses support ITA theory at both the within- and between-person levels of analyses and demonstrate the benefits of Bayesian techniques for the analysis of within-person processes. These include more formal specification of the theory and the ability to draw inferences about each individual, which allows for more nuanced interpretations of individuals within a personality category, such as differences in the individual probabilities of spiraling. While Bayesian techniques have many potential advantages for the analyses of processes at the level of the individual, ease of use is not one of them for psychologists trained in traditional frequentist statistical techniques. PMID:27486415
A. Korattikara; V. Rathod; K. Murphy; M. Welling
2015-01-01
We consider the problem of Bayesian parameter estimation for deep neural networks, which is important in problem settings where we may have little data, and/ or where we need accurate posterior predictive densities p(y|x, D), e.g., for applications involving bandits or active learning. One simple ap
Bayesian logistic regression analysis
Van Erp, H.R.N.; Van Gelder, P.H.A.J.M.
2012-01-01
In this paper we present a Bayesian logistic regression analysis. It is found that if one wishes to derive the posterior distribution of the probability of some event, then, together with the traditional Bayes Theorem and the integrating out of nuissance parameters, the Jacobian transformation is an
Loredo, Thomas J.
2004-04-01
I describe a framework for adaptive scientific exploration based on iterating an Observation-Inference-Design cycle that allows adjustment of hypotheses and observing protocols in response to the results of observation on-the-fly, as data are gathered. The framework uses a unified Bayesian methodology for the inference and design stages: Bayesian inference to quantify what we have learned from the available data and predict future data, and Bayesian decision theory to identify which new observations would teach us the most. When the goal of the experiment is simply to make inferences, the framework identifies a computationally efficient iterative ``maximum entropy sampling'' strategy as the optimal strategy in settings where the noise statistics are independent of signal properties. Results of applying the method to two ``toy'' problems with simulated data-measuring the orbit of an extrasolar planet, and locating a hidden one-dimensional object-show the approach can significantly improve observational efficiency in settings that have well-defined nonlinear models. I conclude with a list of open issues that must be addressed to make Bayesian adaptive exploration a practical and reliable tool for optimizing scientific exploration.
DEFF Research Database (Denmark)
Antoniou, Constantinos; Harrison, Glenn W.; Lau, Morten I.;
2015-01-01
A large literature suggests that many individuals do not apply Bayes’ Rule when making decisions that depend on them correctly pooling prior information and sample data. We replicate and extend a classic experimental study of Bayesian updating from psychology, employing the methods of experimental...
Bayesian Independent Component Analysis
DEFF Research Database (Denmark)
Winther, Ole; Petersen, Kaare Brandt
2007-01-01
In this paper we present an empirical Bayesian framework for independent component analysis. The framework provides estimates of the sources, the mixing matrix and the noise parameters, and is flexible with respect to choice of source prior and the number of sources and sensors. Inside the engine...
DEFF Research Database (Denmark)
Hartelius, Karsten; Carstensen, Jens Michael
2003-01-01
A method for locating distorted grid structures in images is presented. The method is based on the theories of template matching and Bayesian image restoration. The grid is modeled as a deformable template. Prior knowledge of the grid is described through a Markov random field (MRF) model which...
Bayesian Networks and Influence Diagrams
DEFF Research Database (Denmark)
Kjærulff, Uffe Bro; Madsen, Anders Læsø
, and exercises are included for the reader to check his/her level of understanding. The techniques and methods presented for knowledge elicitation, model construction and verification, modeling techniques and tricks, learning models from data, and analyses of models have all been developed and refined......, troubleshooting, and data mining under uncertainty. Bayesian Networks and Influence Diagrams: A Guide to Construction and Analysis provides a comprehensive guide for practitioners who wish to understand, construct, and analyze intelligent systems for decision support based on probabilistic networks. Intended...... primarily for practitioners, this book does not require sophisticated mathematical skills or deep understanding of the underlying theory and methods nor does it discuss alternative technologies for reasoning under uncertainty. The theory and methods presented are illustrated through more than 140 examples...
Ildikó Ungvári; Gábor Hullám; Péter Antal; Petra Sz Kiszel; András Gézsi; Éva Hadadi; Viktor Virág; Gergely Hajós; András Millinghoffer; Adrienne Nagy; András Kiss; Semsei, Ágnes F.; Gergely Temesi; Béla Melegh; Péter Kisfali
2012-01-01
Genetic studies indicate high number of potential factors related to asthma. Based on earlier linkage analyses we selected the 11q13 and 14q22 asthma susceptibility regions, for which we designed a partial genome screening study using 145 SNPs in 1201 individuals (436 asthmatic children and 765 controls). The results were evaluated with traditional frequentist methods and we applied a new statistical method, called bayesian network based bayesian multilevel analysis of relevance (BN-BMLA). Th...
Improving Environmental Scanning Systems Using Bayesian Networks
Simon Welter; Jörg H. Mayer; Reiner Quick
2013-01-01
As companies’ environment is becoming increasingly volatile, scanning systems gain in importance. We propose a hybrid process model for such systems' information gathering and interpretation tasks that combines quantitative information derived from regression analyses and qualitative knowledge from expert interviews. For the latter, we apply Bayesian networks. We derive the need for such a hybrid process model from a literature review. We lay out our model to find a suitable set of business e...
Yu, Jihnhee; Hutson, Alan D; Siddiqui, Adnan H; Kedron, Mary A
2016-02-01
In some small clinical trials, toxicity is not a primary endpoint; however, it often has dire effects on patients' quality of life and is even life-threatening. For such clinical trials, rigorous control of the overall incidence of adverse events is desirable, while simultaneously collecting safety information. In this article, we propose group sequential toxicity monitoring strategies to control overall toxicity incidents below a certain level as opposed to performing hypothesis testing, which can be incorporated into an existing study design based on the primary endpoint. We consider two sequential methods: a non-Bayesian approach in which stopping rules are obtained based on the 'future' probability of an excessive toxicity rate; and a Bayesian adaptation modifying the proposed non-Bayesian approach, which can use the information obtained at interim analyses. Through an extensive Monte Carlo study, we show that the Bayesian approach often provides better control of the overall toxicity rate than the non-Bayesian approach. We also investigate adequate toxicity estimation after the studies. We demonstrate the applicability of our proposed methods in controlling the symptomatic intracranial hemorrhage rate for treating acute ischemic stroke patients.
Alexandrino, J.; Ferrand, N.; Arntzen, J.W.
2005-01-01
Morphometric and colour pattern variation in the endemic Iberian salamander Chioglossa lusitanica is concordant with the genetic differentiation of two groups of populations separated by the Mondego river in Portugal. Salamanders from the south have shorter digits than those from the north. Clinal v
Kleinteich, Thomas; Herzen, Julia; Beckmann, Felix; Matsui, Masafumi; Haas, Alexander
2014-02-01
Larval salamanders (Lissamphibia: Caudata) are known to be effective suction feeders in their aquatic environments, although they will eventually transform into terrestrial tongue feeding adults during metamorphosis. Early tetrapods may have had a similar biphasic life cycle and this makes larval salamanders a particularly interesting model to study the anatomy, function, development, and evolution of the feeding apparatus in terrestrial vertebrates. Here, we provide a description of the muscles that are involved in the feeding strike in salamander larvae of the Hynobiidae and compare them to larvae of the paedomorphic Cryptobranchidae. We provide a functional and evolutionary interpretation for the observed muscle characters. The cranial muscles in larvae from species of the Hynobiidae and Cryptobranchidae are generally very similar. Most notable are the differences in the presence of the m. hyomandibularis, a muscle that connects the hyobranchial apparatus with the lower jaw. We found this muscle only in Onychodactylus japonicus (Hynobiidae) but not in other hynobiid or cryptobranchid salamanders. Interestingly, the m. hyomandibularis in O. japonicus originates from the ceratobranchial I and not the ceratohyal, and thus exhibits what was previously assumed to be the derived condition. Finally, we applied a biomechanical model to simulate suction feeding in larval salamanders. We provide evidence that a flattened shape of the hyobranchial apparatus in its resting position is beneficial for a fast and successful suction feeding strike.
Larval long-toed salamanders incur nonconsumptive effects in the presence of nonnative trout
Kenison, Erin K.; Litt, Andrea R.; Pilliod, David; McMahon, Thomas E.
2016-01-01
Predators can influence prey directly through consumption or indirectly through nonconsumptive effects (NCEs) by altering prey behavior, morphology, and life history. We investigated whether predator-avoidance behaviors by larval long-toed salamanders (Ambystoma macrodactylum) in lakes with nonnative trout result in NCEs on morphology and development. Field studies in lakes with and without trout were corroborated by experimental enclosures, where prey were exposed only to visual and chemical cues of predators. We found that salamanders in lakes with trout were consistently smaller than in lakes without trout: 38% lower weight, 24% shorter body length, and 29% shorter tail length. Similarly, salamanders in protective enclosures grew 2.9 times slower when exposed to visual and olfactory trout cues than when no trout cues were present. Salamanders in trout-free lakes and enclosures were 22.7 times and 1.48 times, respectively, more likely to metamorphose during the summer season than those exposed to trout in lakes and/or their cues. Observed changes in larval growth rate and development likely resulted from a facultative response to predator-avoidance behavior and demonstrate NCEs occurred even when predation risk was only perceived. Reduced body size and growth, as well as delayed metamorphosis, could have ecological consequences for salamander populations existing with fish if those effects carry-over into lower recruitment, survival, and fecundity.
Tyler, T.; Liss, W.J.; Ganio, L.; Larson, Gary L.; Hoffman, Robert L.; Deimling, E.; Lomnicky, G.A.
1998-01-01
The larval stage of the long-toed salamander (Ambystoma macrodactylum) is the top vertebrate predator in high-elevation fishless lakes in the North Cascades National Park Service Complex, Washington (U.S.A.). Although most of these high-elevation lakes were naturally fishless, trout have been stocked in many of them. We sought to determine the effects of physicochemical factors and introduced trout on abundance and behavior of A. macrodactylum larvae. Larval salamander densities were estimated by snorkeling. Snorkelers carefully searched through substrate materials within 2 m of the shoreline and recorded the number of larvae observed and if larvae were hidden in benthic substrates. Physicochemical factors were measured in each lake on the same day that snorkel surveys were conducted. In fishless lakes, larval salamander densities were positively related to total Kjeldahl-N concentration and negatively related to lake elevation. Crustacean zooplankton, especially cladocerans, were important food resources for larval A. macrodactylum. Crustacean zooplankton and cladoceran densities were positively related to total Kjeldahl-N, suggesting that increased food resources contributed to increased densities of larval A. macrodactylum. Differences in larval salamander densities between fish and fishless lakes were related to total Kjeldahl-N concentrations and the reproductive status of trout. Mean larval salamander densities for fishless lakes with total Kjeldahl-N amphibians requires an understanding of natural abiotic and biotic factors and processes influencing amphibian distribution and abundance.
Welsh, H.H.; Droege, S.
2001-01-01
Terrestrial salamanders of the family P!ethodontidae have unique attributes that make them excellent indicators of biodiversity and ecosystem integrity in forested habitats. Their longevity, small territory size, site fidelity, sensitivity to natural and anthropogenic perturbations, tendency to occur in high densities, and low sampling costs mean that counts of plethodontid salamanders provide numerous advantages over counts of other North American forest organisms for indicating environmental change. Furthermore, they are tightly linked physiologically to microclimatic and successional processes that influence the distribution and abundance of numerous other hydrophilic but difficult-to-study forest-dwelling plants and animals. Ecosystem processes such as moisture cycling, food-web dynamics, and succession, with their related structural and microclimatic variability, all affect forest biodiversity and have been shown to affect salamander populations as well. We determined the variability associated with sampling for plethodontid salamanders by estimating the coefficient of variation (CV) from available time-series data. The median coefficient of variation indicated that variation in counts of individuals among studies was much lower in plethodonticis (27%) than in lepidoptera (93%), passerine birds (57%), small mammals (69%), or other amphibians (37-46%), which means plethodontid salamanders provide an important statistical advantage over other species for monitoring long-term forest health.
Estimating superpopulation size and annual probability of breeding for pond-breeding salamanders
Kinkead, K.E.; Otis, D.L.
2007-01-01
It has long been accepted that amphibians can skip breeding in any given year, and environmental conditions act as a cue for breeding. In this paper, we quantify temporary emigration or nonbreeding probability for mole and spotted salamanders (Ambystoma talpoideum and A. maculatum). We estimated that 70% of mole salamanders may skip breeding during an average rainfall year and 90% may skip during a drought year. Spotted salamanders may be more likely to breed, with only 17% avoiding the breeding pond during an average rainfall year. We illustrate how superpopulations can be estimated using temporary emigration probability estimates. The superpopulation is the total number of salamanders associated with a given breeding pond. Although most salamanders stay within a certain distance of a breeding pond for the majority of their life spans, it is difficult to determine true overall population sizes for a given site if animals are only captured during a brief time frame each year with some animals unavailable for capture at any time during a given year. ?? 2007 by The Herpetologists' League, Inc.
Bayesian data analysis in population ecology: motivations, methods, and benefits
Dorazio, Robert
2016-01-01
During the 20th century ecologists largely relied on the frequentist system of inference for the analysis of their data. However, in the past few decades ecologists have become increasingly interested in the use of Bayesian methods of data analysis. In this article I provide guidance to ecologists who would like to decide whether Bayesian methods can be used to improve their conclusions and predictions. I begin by providing a concise summary of Bayesian methods of analysis, including a comparison of differences between Bayesian and frequentist approaches to inference when using hierarchical models. Next I provide a list of problems where Bayesian methods of analysis may arguably be preferred over frequentist methods. These problems are usually encountered in analyses based on hierarchical models of data. I describe the essentials required for applying modern methods of Bayesian computation, and I use real-world examples to illustrate these methods. I conclude by summarizing what I perceive to be the main strengths and weaknesses of using Bayesian methods to solve ecological inference problems.
Testicular structure and germ cells morphology in salamanders
Uribe, Mari Carmen; Mejía-Roa, Víctor
2014-01-01
Testes of salamanders or urodeles are paired elongated organs that are attached to the dorsal wall of the body by a mesorchium. The testes are composed of one or several lobes. Each lobe is morphologically and functionally a similar testicular unit. The lobes of the testis are joined by cords covered by a single peritoneal epithelium and subjacent connective tissue. The cords contain spermatogonia. Spermatogonia associate with Sertoli cells to form spermatocysts or cysts. The spermatogenic cells in a cyst undergo their development through spermatogenesis synchronously. The distribution of cysts displays the cephalo-caudal gradient in respect to the stage of spermatogenesis. The formation of cysts at cephalic end of the testis causes their migration along the lobules to the caudal end. Consequently, the disposition in cephalo-caudal regions of spermatogenesis can be observed in longitudinal sections of the testis. The germ cells are spermatogonia, diploid cells with mitotic activity; primary and second spermatocytes characterized by meiotic divisions that develop haploid spermatids; during spermiogenesis the spermatids differentiate to spermatozoa. During spermiation the cysts open and spermatozoa leave the testicular lobules. After spermiation occurs the development of Leydig cells into glandular tissue. This glandular tissue regressed at the end of the reproductive cycle. PMID:26413406
Sandoval-Guzmán, Tatiana; Wang, Heng; Khattak, Shahryar; Schuez, Maritta; Roensch, Kathleen; Nacu, Eugeniu; Tazaki, Akira; Joven, Alberto; Tanaka, Elly M; Simon, András
2014-02-01
Salamanders regenerate appendages via a progenitor pool called the blastema. The cellular mechanisms underlying regeneration of muscle have been much debated but have remained unclear. Here we applied Cre-loxP genetic fate mapping to skeletal muscle during limb regeneration in two salamander species, Notophthalmus viridescens (newt) and Ambystoma mexicanum (axolotl). Remarkably, we found that myofiber dedifferentiation is an integral part of limb regeneration in the newt, but not in axolotl. In the newt, myofiber fragmentation results in proliferating, PAX7(-) mononuclear cells in the blastema that give rise to the skeletal muscle in the new limb. In contrast, myofibers in axolotl do not generate proliferating cells, and do not contribute to newly regenerated muscle; instead, resident PAX7(+) cells provide the regeneration activity. Our results therefore show significant diversity in limb muscle regeneration mechanisms among salamanders and suggest that multiple strategies may be feasible for inducing regeneration in other species, including mammals. PMID:24268695
Wildlife disease. Recent introduction of a chytrid fungus endangers Western Palearctic salamanders.
Martel, A; Blooi, M; Adriaensen, C; Van Rooij, P; Beukema, W; Fisher, M C; Farrer, R A; Schmidt, B R; Tobler, U; Goka, K; Lips, K R; Muletz, C; Zamudio, K R; Bosch, J; Lötters, S; Wombwell, E; Garner, T W J; Cunningham, A A; Spitzen-van der Sluijs, A; Salvidio, S; Ducatelle, R; Nishikawa, K; Nguyen, T T; Kolby, J E; Van Bocxlaer, I; Bossuyt, F; Pasmans, F
2014-10-31
Emerging infectious diseases are reducing biodiversity on a global scale. Recently, the emergence of the chytrid fungus Batrachochytrium salamandrivorans resulted in rapid declines in populations of European fire salamanders. Here, we screened more than 5000 amphibians from across four continents and combined experimental assessment of pathogenicity with phylogenetic methods to estimate the threat that this infection poses to amphibian diversity. Results show that B. salamandrivorans is restricted to, but highly pathogenic for, salamanders and newts (Urodela). The pathogen likely originated and remained in coexistence with a clade of salamander hosts for millions of years in Asia. As a result of globalization and lack of biosecurity, it has recently been introduced into naïve European amphibian populations, where it is currently causing biodiversity loss.
An orphan gene is necessary for preaxial digit formation during salamander limb development
Kumar, Anoop; Gates, Phillip B.; Czarkwiani, Anna; Brockes, Jeremy P.
2015-01-01
Limb development in salamanders differs from other tetrapods in that the first digits to form are the two most anterior (preaxial dominance). This has been proposed as a salamander novelty and its mechanistic basis is unknown. Salamanders are the only adult tetrapods able to regenerate the limb, and the contribution of preaxial dominance to limb regeneration is unclear. Here we show that during early outgrowth of the limb bud, a small cohort of cells express the orphan gene Prod1 together with Bmp2, a critical player in digit condensation in amniotes. Disruption of Prod1 with a gene-editing nuclease abrogates these cells, and blocks formation of the radius and ulna, and outgrowth of the anterior digits. Preaxial dominance is a notable feature of limb regeneration in the larval newt, but this changes abruptly after metamorphosis so that the formation of anterior and posterior digits occurs together within the autopodium resembling an amniote-like pattern. PMID:26498026
Probability and Bayesian statistics
1987-01-01
This book contains selected and refereed contributions to the "Inter national Symposium on Probability and Bayesian Statistics" which was orga nized to celebrate the 80th birthday of Professor Bruno de Finetti at his birthplace Innsbruck in Austria. Since Professor de Finetti died in 1985 the symposium was dedicated to the memory of Bruno de Finetti and took place at Igls near Innsbruck from 23 to 26 September 1986. Some of the pa pers are published especially by the relationship to Bruno de Finetti's scientific work. The evolution of stochastics shows growing importance of probability as coherent assessment of numerical values as degrees of believe in certain events. This is the basis for Bayesian inference in the sense of modern statistics. The contributions in this volume cover a broad spectrum ranging from foundations of probability across psychological aspects of formulating sub jective probability statements, abstract measure theoretical considerations, contributions to theoretical statistics an...
DEFF Research Database (Denmark)
Mørup, Morten; Schmidt, Mikkel N
2012-01-01
Many networks of scientific interest naturally decompose into clusters or communities with comparatively fewer external than internal links; however, current Bayesian models of network communities do not exert this intuitive notion of communities. We formulate a nonparametric Bayesian model...... for community detection consistent with an intuitive definition of communities and present a Markov chain Monte Carlo procedure for inferring the community structure. A Matlab toolbox with the proposed inference procedure is available for download. On synthetic and real networks, our model detects communities...... consistent with ground truth, and on real networks, it outperforms existing approaches in predicting missing links. This suggests that community structure is an important structural property of networks that should be explicitly modeled....
Brody, Samuel; Lapata, Mirella
2009-01-01
Sense induction seeks to automatically identify word senses directly from a corpus. A key assumption underlying previous work is that the context surrounding an ambiguous word is indicative of its meaning. Sense induction is thus typically viewed as an unsupervised clustering problem where the aim is to partition a word’s contexts into different classes, each representing a word sense. Our work places sense induction in a Bayesian context by modeling the contexts of the ambiguous word as samp...
Bayesian Generalized Rating Curves
Helgi Sigurðarson 1985
2014-01-01
A rating curve is a curve or a model that describes the relationship between water elevation, or stage, and discharge in an observation site in a river. The rating curve is fit from paired observations of stage and discharge. The rating curve then predicts discharge given observations of stage and this methodology is applied as stage is substantially easier to directly observe than discharge. In this thesis a statistical rating curve model is proposed working within the framework of Bayesian...
Efficient Bayesian Phase Estimation
Wiebe, Nathan; Granade, Chris
2016-07-01
We introduce a new method called rejection filtering that we use to perform adaptive Bayesian phase estimation. Our approach has several advantages: it is classically efficient, easy to implement, achieves Heisenberg limited scaling, resists depolarizing noise, tracks time-dependent eigenstates, recovers from failures, and can be run on a field programmable gate array. It also outperforms existing iterative phase estimation algorithms such as Kitaev's method.
Editorial: Bayesian benefits for child psychology and psychiatry researchers.
Oldehinkel, Albertine J
2016-09-01
For many scientists, performing statistical tests has become an almost automated routine. However, p-values are frequently used and interpreted incorrectly; and even when used appropriately, p-values tend to provide answers that do not match researchers' questions and hypotheses well. Bayesian statistics present an elegant and often more suitable alternative. The Bayesian approach has rarely been applied in child psychology and psychiatry research so far, but the development of user-friendly software packages and tutorials has placed it well within reach now. Because Bayesian analyses require a more refined definition of hypothesized probabilities of possible outcomes than the classical approach, going Bayesian may offer the additional benefit of sparkling the development and refinement of theoretical models in our field. PMID:27535649
Bayesian multimodel inference for dose-response studies
Link, W.A.; Albers, P.H.
2007-01-01
Statistical inference in dose?response studies is model-based: The analyst posits a mathematical model of the relation between exposure and response, estimates parameters of the model, and reports conclusions conditional on the model. Such analyses rarely include any accounting for the uncertainties associated with model selection. The Bayesian inferential system provides a convenient framework for model selection and multimodel inference. In this paper we briefly describe the Bayesian paradigm and Bayesian multimodel inference. We then present a family of models for multinomial dose?response data and apply Bayesian multimodel inferential methods to the analysis of data on the reproductive success of American kestrels (Falco sparveriuss) exposed to various sublethal dietary concentrations of methylmercury.
Editorial: Bayesian benefits for child psychology and psychiatry researchers.
Oldehinkel, Albertine J
2016-09-01
For many scientists, performing statistical tests has become an almost automated routine. However, p-values are frequently used and interpreted incorrectly; and even when used appropriately, p-values tend to provide answers that do not match researchers' questions and hypotheses well. Bayesian statistics present an elegant and often more suitable alternative. The Bayesian approach has rarely been applied in child psychology and psychiatry research so far, but the development of user-friendly software packages and tutorials has placed it well within reach now. Because Bayesian analyses require a more refined definition of hypothesized probabilities of possible outcomes than the classical approach, going Bayesian may offer the additional benefit of sparkling the development and refinement of theoretical models in our field.
Bayesian theory and applications
Dellaportas, Petros; Polson, Nicholas G; Stephens, David A
2013-01-01
The development of hierarchical models and Markov chain Monte Carlo (MCMC) techniques forms one of the most profound advances in Bayesian analysis since the 1970s and provides the basis for advances in virtually all areas of applied and theoretical Bayesian statistics. This volume guides the reader along a statistical journey that begins with the basic structure of Bayesian theory, and then provides details on most of the past and present advances in this field. The book has a unique format. There is an explanatory chapter devoted to each conceptual advance followed by journal-style chapters that provide applications or further advances on the concept. Thus, the volume is both a textbook and a compendium of papers covering a vast range of topics. It is appropriate for a well-informed novice interested in understanding the basic approach, methods and recent applications. Because of its advanced chapters and recent work, it is also appropriate for a more mature reader interested in recent applications and devel...
Wiegerinck, Wim; Schoenaker, Christiaan; Duane, Gregory
2016-04-01
Recently, methods for model fusion by dynamically combining model components in an interactive ensemble have been proposed. In these proposals, fusion parameters have to be learned from data. One can view these systems as parametrized dynamical systems. We address the question of learnability of dynamical systems with respect to both short term (vector field) and long term (attractor) behavior. In particular we are interested in learning in the imperfect model class setting, in which the ground truth has a higher complexity than the models, e.g. due to unresolved scales. We take a Bayesian point of view and we define a joint log-likelihood that consists of two terms, one is the vector field error and the other is the attractor error, for which we take the L1 distance between the stationary distributions of the model and the assumed ground truth. In the context of linear models (like so-called weighted supermodels), and assuming a Gaussian error model in the vector fields, vector field learning leads to a tractable Gaussian solution. This solution can then be used as a prior for the next step, Bayesian attractor learning, in which the attractor error is used as a log-likelihood term. Bayesian attractor learning is implemented by elliptical slice sampling, a sampling method for systems with a Gaussian prior and a non Gaussian likelihood. Simulations with a partially observed driven Lorenz 63 system illustrate the approach.
The effect of waist twisting on walking speed of an amphibious salamander like robot
Yin, Xin-Yan; Jia, Li-Chao; Wang, Chen; Xie, Guang-Ming
2016-06-01
Amphibious salamanders often swing their waist to coordinate quadruped walking in order to improve their crawling speed. A robot with a swing waist joint, like an amphibious salamander, is used to mimic this locomotion. A control method is designed to allow the robot to maintain the rotational speed of its legs continuous and avoid impact between its legs and the ground. An analytical expression is established between the amplitude of the waist joint and the step length. Further, an optimization amplitude is obtained corresponding to the maximum stride. The simulation results based on automatic dynamic analysis of mechanical systems (ADAMS) and physical experiments verify the rationality and validity of this expression.
The effect of waist twisting on walking speed of an amphibious salamander like robot
Institute of Scientific and Technical Information of China (English)
Xin-Yan Yin; Li-Chao Jia; Chen Wang; Guang-Ming Xie
2016-01-01
Amphibious salamanders often swing their waist to coordinate quadruped walking in order to improve their crawling speed. A robot with a swing waist joint, like an amphibious salamander, is used to mimic this locomotion. A control method is designed to allow the robot to maintain the rotational speed of its legs continuous and avoid impact between its legs and the ground. An analytical expression is established between the amplitude of the waist joint and the step length. Further, an optimization amplitude is obtained corresponding to the maximum stride. The simulation results based on automatic dynamic analysis of mechanical systems (ADAMS) and physical experiments verify the rationality and validity of this expression.
Bayesian optimization for materials design
Frazier, Peter I.; Wang, Jialei
2015-01-01
We introduce Bayesian optimization, a technique developed for optimizing time-consuming engineering simulations and for fitting machine learning models on large datasets. Bayesian optimization guides the choice of experiments during materials design and discovery to find good material designs in as few experiments as possible. We focus on the case when materials designs are parameterized by a low-dimensional vector. Bayesian optimization is built on a statistical technique called Gaussian pro...
Bayesian Posteriors Without Bayes' Theorem
Hill, Theodore P
2012-01-01
The classical Bayesian posterior arises naturally as the unique solution of several different optimization problems, without the necessity of interpreting data as conditional probabilities and then using Bayes' Theorem. For example, the classical Bayesian posterior is the unique posterior that minimizes the loss of Shannon information in combining the prior and the likelihood distributions. These results, direct corollaries of recent results about conflations of probability distributions, reinforce the use of Bayesian posteriors, and may help partially reconcile some of the differences between classical and Bayesian statistics.
Skutschas, Pavel; Stein, Koen
2015-04-01
Kokartus honorarius from the Middle Jurassic (Bathonian) of Kyrgyzstan is one of the oldest salamanders in the fossil record, characterized by a mixture of plesiomorphic morphological features and characters shared with crown-group salamanders. Here we present a detailed histological analysis of its long bones. The analysis of a growth series demonstrates a significant histological maturation during ontogeny, expressed by the progressive appearance of longitudinally oriented primary vascular canals, primary osteons, growth marks, remodelling features in primary bone tissues, as well as progressive resorption of the calcified cartilage, formation of endochondral bone and development of cartilaginous to bony trabeculae in the epiphyses. Apart from the presence of secondary osteons, the long bone histology of Kokartus is very similar to that of miniaturized temnospondyls, other Jurassic stem salamanders, miniaturized seymouriamorphs and modern crown-group salamanders. We propose that the presence of secondary osteons in Kokartus honorarius is a plesiomorphic feature, and the loss of secondary osteons in the long bones of crown-group salamanders as well as in those of miniaturized temnospondyls is the result of miniaturization processes. Hitherto, all stem salamander long bong histology (Kokartus, Marmorerpeton and 'salamander A') has been generally described as having paedomorphic features (i.e. the presence of Katschenko's Line and a layer of calcified cartilage), these taxa were thus most likely neotenic forms. The absence of clear lines of arrested growth and annuli in long bones of Kokartus honorarius suggests that the animals lived in an environment with stable local conditions. PMID:25682890
Skutschas, Pavel; Stein, Koen
2015-04-01
Kokartus honorarius from the Middle Jurassic (Bathonian) of Kyrgyzstan is one of the oldest salamanders in the fossil record, characterized by a mixture of plesiomorphic morphological features and characters shared with crown-group salamanders. Here we present a detailed histological analysis of its long bones. The analysis of a growth series demonstrates a significant histological maturation during ontogeny, expressed by the progressive appearance of longitudinally oriented primary vascular canals, primary osteons, growth marks, remodelling features in primary bone tissues, as well as progressive resorption of the calcified cartilage, formation of endochondral bone and development of cartilaginous to bony trabeculae in the epiphyses. Apart from the presence of secondary osteons, the long bone histology of Kokartus is very similar to that of miniaturized temnospondyls, other Jurassic stem salamanders, miniaturized seymouriamorphs and modern crown-group salamanders. We propose that the presence of secondary osteons in Kokartus honorarius is a plesiomorphic feature, and the loss of secondary osteons in the long bones of crown-group salamanders as well as in those of miniaturized temnospondyls is the result of miniaturization processes. Hitherto, all stem salamander long bong histology (Kokartus, Marmorerpeton and 'salamander A') has been generally described as having paedomorphic features (i.e. the presence of Katschenko's Line and a layer of calcified cartilage), these taxa were thus most likely neotenic forms. The absence of clear lines of arrested growth and annuli in long bones of Kokartus honorarius suggests that the animals lived in an environment with stable local conditions.
Molecular mechanisms of extensive mitochondrial gene rearrangementin plethodontid salamanders
Energy Technology Data Exchange (ETDEWEB)
Mueller, Rachel Lockridge; Boore, Jeffrey L.
2005-06-01
Extensive gene rearrangement is reported in the mitochondrial genomes of lungless salamanders (Plethodontidae). In each genome with a novel gene order, there is evidence that the rearrangement was mediated by duplication of part of the mitochondrial genome, including the presence of both pseudogenes and additional, presumably functional, copies of duplicated genes. All rearrangement-mediating duplications include either the origin of light strand replication and the nearby tRNA genes or the regions flanking the origin of heavy strand replication. The latter regions comprise nad6, trnE, cob, trnT, an intergenic spacer between trnT and trnP and, in some genomes, trnP, the control region, trnF, rrnS, trnV, rrnL, trnL1, and nad1. In some cases, two copies of duplicated genes, presumptive regulatory regions, and/or sequences with no assignable function have been retained in the genome following the initial duplication; in other genomes, only one of the duplicated copies has been retained. Both tandem and non-tandem duplications are present in these genomes, suggesting different duplication mechanisms. In some of these mtDNAs, up to 25 percent of the total length is composed of tandem duplications of non-coding sequence that includes putative regulatory regions and/or pseudogenes of tRNAs and protein-coding genes along with otherwise unassignable sequences. These data indicate that imprecise initiation and termination of replication, slipped-strand mispairing, and intra-molecular recombination may all have played a role in generating repeats during the evolutionary history of plethodontid mitochondrial genomes.
Institute of Scientific and Technical Information of China (English)
无
2010-01-01
little is known about the ecology of the chinese giant salamander (andrias davidianus),a critically endangered species.such information is needed to make informed decisions concerning the conservation and management of this species.four a.davidianus raised in a pool were released into their native habitat on 04 may 2005 and were subsequently radio-tracked for approximately 155-168 days.following their release,the giant salamanders traveled upstream in search of suitable micro-habitats,and settled after 10 days.later,a devastating summer flash flood destroyed the salamanders' dens,triggering another bout of habitat searching by the animals.eventually,the salamanders settled in different sections of the stream where they remained until the end of the study.on average,each habitat searching endeavor took 7.5 days,during which a giant salamander explored a 310 m stretch of stream with a surface area of about 1157 m2 and occupied 3.5 temporary dwellings.each giant salamander spent an average of 144.5 days in semi-permanent micro-habitats,and occupied territories that had a mean size of 34.75 m2.our results indicate that the chinese giant salamander responds to habitat disturbance by seeking new habitats upstream,both water temperature and water level affect the salamander's habitat searching activity,and the size of the salamander's semi-permanent territory is influenced by the size of the pool containing the animal's den.
Valorie Titus; Dale Madison; Timothy Green
2014-01-01
Most amphibians use both wetland and upland habitats, but the extent of their movement in forested habitats is poorly known. We used radiotelemetry to observe the movements of adult and juvenile eastern tiger salamanders over a 4-year period. Females tended to move farther from the breeding ponds into upland forested habitat than males, while the distance a juvenile moved appeared to be related to body size, with the largest individuals moving as far as the adult females. Individuals chose re...
Congdon, Peter
2014-01-01
This book provides an accessible approach to Bayesian computing and data analysis, with an emphasis on the interpretation of real data sets. Following in the tradition of the successful first edition, this book aims to make a wide range of statistical modeling applications accessible using tested code that can be readily adapted to the reader's own applications. The second edition has been thoroughly reworked and updated to take account of advances in the field. A new set of worked examples is included. The novel aspect of the first edition was the coverage of statistical modeling using WinBU
Computationally efficient Bayesian tracking
Aughenbaugh, Jason; La Cour, Brian
2012-06-01
In this paper, we describe the progress we have achieved in developing a computationally efficient, grid-based Bayesian fusion tracking system. In our approach, the probability surface is represented by a collection of multidimensional polynomials, each computed adaptively on a grid of cells representing state space. Time evolution is performed using a hybrid particle/grid approach and knowledge of the grid structure, while sensor updates use a measurement-based sampling method with a Delaunay triangulation. We present an application of this system to the problem of tracking a submarine target using a field of active and passive sonar buoys.
Bayesian nonparametric data analysis
Müller, Peter; Jara, Alejandro; Hanson, Tim
2015-01-01
This book reviews nonparametric Bayesian methods and models that have proven useful in the context of data analysis. Rather than providing an encyclopedic review of probability models, the book’s structure follows a data analysis perspective. As such, the chapters are organized by traditional data analysis problems. In selecting specific nonparametric models, simpler and more traditional models are favored over specialized ones. The discussed methods are illustrated with a wealth of examples, including applications ranging from stylized examples to case studies from recent literature. The book also includes an extensive discussion of computational methods and details on their implementation. R code for many examples is included in on-line software pages.
Bayesian Geostatistical Design
DEFF Research Database (Denmark)
Diggle, Peter; Lophaven, Søren Nymand
2006-01-01
locations to, or deletion of locations from, an existing design, and prospective design, which consists of choosing positions for a new set of sampling locations. We propose a Bayesian design criterion which focuses on the goal of efficient spatial prediction whilst allowing for the fact that model......This paper describes the use of model-based geostatistics for choosing the set of sampling locations, collectively called the design, to be used in a geostatistical analysis. Two types of design situation are considered. These are retrospective design, which concerns the addition of sampling...
Directory of Open Access Journals (Sweden)
Joseph J. Apodaca
2015-03-01
Full Text Available Forestry practices are placing ever increasing emphasis on sustainability and the maintenance of ecological processes, biodiversity, and endangered species or populations. Balancing timber harvest and the management of imperiled species presents a particularly difficult challenge during this shift, as we often know very little about these species’ natural history and how and why silviculture practices affect their populations. Accordingly, investigation of and improvement on current management practices for threatened species is imperative. We investigated the effectiveness of habitat buffers as a management technique for the imperiled Red Hills salamander (Phaeognathus hubrichti by combining genetic, transect, and body-condition data. We found that populations where habitat buffers have been employed have higher genetic diversity and higher population densities, and individuals have better overall body condition. These results indicate that buffering the habitat of imperiled species can be an effective management tool for terrestrial salamanders. Additionally, they provide further evidence that leaving the habitat of imperiled salamanders unbuffered can have both immediate and long-term negative impacts on populations.
Cheat Mountain Salamanders Search Report 2006 Canaan Valley National Wildlife Refuge
US Fish and Wildlife Service, Department of the Interior — The objective of the survey was to document Cheat Mountain salamander use on either side of Powderline ski trail or Three-Mile ski trail in an effort to continue to...
Using the Eastern Hellbender Salamander in a High School Genetics & Ecological Conservation Activity
Chudyk, Sarah; McMillan, Amy; Lange, Catherine
2014-01-01
This article contains an original 5E lesson plan developed from conservation genetics research on the giant North American hellbender salamander, Cryptobranchus alleganiensis alleganiensis. The lesson plan provides background information on the hellbender, reviews basic genetics, and exposes students to the scientific process that is used during…
Directory of Open Access Journals (Sweden)
Andrés R. Acosta-Galvis
2012-01-01
Full Text Available Eight species of salamanders are recognized to Cordillera Oriental of Colombia. Here we describe a new species of the genus Bolitoglossa, named Bolitoglossa guaneae sp. nov. The highest number of species of this genus is found in the cloud forests located in the western flank of the Cordillera Oriental.
Sal-Site: Integrating new and existing ambystomatid salamander research and informational resources
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Weisrock David W
2005-12-01
Full Text Available Abstract Salamanders of the genus Ambystoma are a unique model organism system because they enable natural history and biomedical research in the laboratory or field. We developed Sal-Site to integrate new and existing ambystomatid salamander research resources in support of this model system. Sal-Site hosts six important resources: 1 Salamander Genome Project: an information-based web-site describing progress in genome resource development, 2 Ambystoma EST Database: a database of manually edited and analyzed contigs assembled from ESTs that were collected from A. tigrinum tigrinum and A. mexicanum, 3 Ambystoma Gene Collection: a database containing full-length protein-coding sequences, 4 Ambystoma Map and Marker Collection: an image and database resource that shows the location of mapped markers on linkage groups, provides information about markers, and provides integrating links to Ambystoma EST Database and Ambystoma Gene Collection databases, 5 Ambystoma Genetic Stock Center: a website and collection of databases that describe an NSF funded salamander rearing facility that generates and distributes biological materials to researchers and educators throughout the world, and 6 Ambystoma Research Coordination Network: a web-site detailing current research projects and activities involving an international group of researchers. Sal-Site is accessible at http://www.ambystoma.org.
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Jéssica Barata da Silva
2014-09-01
Full Text Available Plethodontid salamanders of genus Bolitoglossa constitute the largest and most diverse group of salamanders, including around 20% of living caudate species. Recent studies have indicated the occurrence of five recognized species in the Brazilian Amazon Rainforest. We present here the first cytogenetic data of a Brazilian salamander, which may prove to be a useful by contribution to the cytotaxonomy of the genus. Specimens were collected near the "type" locality (Utinga, Belém, PA, Brazil. Chromosomal preparations from duodenal epithelial cells and testes were subjected to Giemsa staining, C-banding and DAPI/CMA3 fluorochrome staining. All specimens showed a karyotype with 13 bi-armed chromosome pairs (2n = 26. Nucleolar Organizer Regions, evidenced by CMA3, were located distally on the long arm of pair 7 (7q. DAPI+ heterochromatin was predominantly centromeric, with some small pericentromeric bands. Although the C-banding patterns of other Bolitoglossa species are so far unknown, cytogenetic studies conducted in other Plethodontid salamanders have demonstrated that pericentromeric heterochromatin is a useful cytological marker for identifying interspecific homeologies. Species diversification is usually accompanied by chromosomal changes. Therefore, the cytogenetic characterization of Bolitoglossa populations from the middle and western Brazilian Amazon Basin could identify differences which may lead to the identification of new species.
Directory of Open Access Journals (Sweden)
Adam L. Crane
2012-01-01
Full Text Available When new predators invade a habitat, either through range extensions or introductions, prey may be at a high risk because they do not recognize the predators as dangerous. The nine-banded armadillo (Dasypus novemcinctus has recently expanded its range in North America. Armadillos forage by searching soil and leaf litter, consuming invertebrates and small vertebrates, including salamanders. We tested whether Ozark zigzag salamanders (Plethodon angusticlavius from a population coexisting with armadillos for about 30 years exhibit antipredator behavior in the presence of armadillo chemical cues and whether they can discriminate between stimuli from armadillos and a nonpredatory sympatric mammal (white-tailed deer, Odocoileus virginianus. Salamanders appeared to recognize substrate cues from armadillos as a threat because they increased escape behaviors and oxygen consumption. When exposed to airborne cues from armadillos, salamanders also exhibited an antipredator response by spending more time in an inconspicuous posture. Additionally, individually consistent behaviors across treatments for some response variables suggest the potential for a behavioral syndrome in this species.
Cutaneous bacteria of the redback salamander prevent morbidity associated with a lethal disease.
Directory of Open Access Journals (Sweden)
Matthew H Becker
Full Text Available Chytridiomycosis, caused by the fungal pathogen Batrachochytrium dendrobatidis (Bd, is an infectious disease that causes population declines of many amphibians. Cutaneous bacteria isolated from redback salamanders, Plethodon cinereus, and mountain yellow-legged frogs, Rana muscosa, inhibit the growth of Bd in vitro. In this study, the bacterial community present on the skin of P. cinereus individuals was investigated to determine if it provides protection to salamanders from the lethal and sub-lethal effects of chytridiomycosis. When the cutaneous bacterial community was reduced prior to Bd exposure, salamanders experienced a significantly greater decrease in body mass, which is a symptom of the disease, when compared to infected individuals with a normal bacterial community. In addition, a greater proportion of infected individuals with a reduced bacterial community experienced limb-lifting, a behavior seen only in infected individuals. Overall, these results demonstrate that the cutaneous bacterial community of P. cinereus provides protection to the salamander from Bd and that alteration of this community can change disease resistance. Therefore, symbiotic microbes associated with this species appear to be an important component of its innate skin defenses.
Data from proteomic analysis of the skin of Chinese giant salamander (Andrias davidianus
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Xiaofang Geng
2015-06-01
Full Text Available The Chinese giant salamander (Andrias davidianus, renowned as a living fossil, is the largest and longest-lived amphibian species in the world. Its skin is rich in collagens, and has developed mucous gland which could secrete a large amount of mucus under the scraping and electric stimulation. The molting is the degraded skin stratum corneum. To establish the functional skin proteome of Chinese giant salamander, two-dimensional gel electrophoresis (2DE and mass spectrometry (MS were applied to detect the composition and relative abundance of the proteins in the skin, mucus and molting. The determination of the general proteome in the skin can potentially serve as a foundation for future studies characterizing the skin proteomes from diseased salamander to provide molecular and mechanistic insights into various disease states and potential therapeutic interventions. Data presented here are also related to the research article “Proteomic analysis of the skin of Chinese giant salamander (Andrias davidianus” in the Journal of Proteomics [1].
NIR spectra were collected at three surface locations for Chinese giant salamanders to ascertain whether spectral signatures could be separated by anatomical, presumably physiologically-based, locations. The first location was the smooth area immediately above the cloaca on the animal’s abdomen, whi...
Grant, E.H.C.; Jung, R.E.; Rice, K.C.
2005-01-01
Stream salamanders are sensitive to acid mine drainage and may be sensitive to acidification and low acid neutralizing capacity (ANC) of a watershed. Streams in Shenandoah National Park, Virginia, are subject to episodic acidification from precipitation events. We surveyed 25 m by 2 m transects located on the stream bank adjacent to the water channel in Shenandoah National Park for salamanders using a stratified random sampling design based on elevation, aspect and bedrock geology. We investigated the relationships of four species (Eurycea bislineata, Desmognathus fuscus, D. monticola and Gyrinophilus porphyriticus) to habitat and water quality variables. We did not find overwhelming evidence that stream salamanders are affected by the acid-base status of streams in Shenandoah National Park. Desmognathus fuscus and D. monticola abundance was greater both in streams that had a higher potential to neutralize acidification, and in higher elevation (>700 m) streams. Neither abundance of E. bislineata nor species richness were related to any of the habitat variables. Our sampling method preferentially detected the adult age class of the study species and did not allow us to estimate population sizes. We suggest that continued monitoring of stream salamander populations in SNP will determine the effects of stream acidification on these taxa.
A new approach for surveying the Alpine Salamander (Salamandra atra in Austria
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Ursula Reinthaler-Lottermoser
2010-12-01
Full Text Available The Alpine Salamander is a small pitch black amphibian which is endemic to the European Alps and the Dinarides. It is strictly protected according to the European FFH guidelines. Despite its central role in the alpine ecosystem our actual published record in Austria is small. In order to resolve this shortcoming our project explores its distribution in Austria. It uses a participatory and community based approach to gather data. Everybody can enter and look at Alpine Salamander observations on our website www.alpensalamander.eu. This approach also allows us to establish an “oral history” of Salamander observations in the past 50 years by conducting interviews in the local community. Since July 2009 the website and salamander report database are online. From the actual data (more than 5600 records we already obtained an overview about the present distribution and data quality. The data are an excellent basis for detailed scientific studies on these remarkable amphibians. With this new and highly interactive approach science and education are combined to initiate protection measures with the public.
Inference in hybrid Bayesian networks
DEFF Research Database (Denmark)
Lanseth, Helge; Nielsen, Thomas Dyhre; Rumí, Rafael;
2009-01-01
Since the 1980s, Bayesian Networks (BNs) have become increasingly popular for building statistical models of complex systems. This is particularly true for boolean systems, where BNs often prove to be a more efficient modelling framework than traditional reliability-techniques (like fault trees...... decade's research on inference in hybrid Bayesian networks. The discussions are linked to an example model for estimating human reliability....
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Putta Srikrishna
2010-06-01
Full Text Available Abstract Background The Mexican axolotl (Ambystoma mexicanum is considered a hopeful monster because it exhibits an adaptive and derived mode of development - paedomorphosis - that has evolved rapidly and independently among tiger salamanders. Unlike related tiger salamanders that undergo metamorphosis, axolotls retain larval morphological traits into adulthood and thus present an adult body plan that differs dramatically from the ancestral (metamorphic form. The basis of paedomorphic development was investigated by comparing temporal patterns of gene transcription between axolotl and tiger salamander larvae (Ambystoma tigrinum tigrinum that typically undergo a metamorphosis. Results Transcript abundances from whole brain and pituitary were estimated via microarray analysis on four different days post hatching (42, 56, 70, 84 dph and regression modeling was used to independently identify genes that were differentially expressed as a function of time in both species. Collectively, more differentially expressed genes (DEGs were identified as unique to the axolotl (n = 76 and tiger salamander (n = 292 than were identified as shared (n = 108. All but two of the shared DEGs exhibited the same temporal pattern of expression and the unique genes tended to show greater changes later in the larval period when tiger salamander larvae were undergoing anatomical metamorphosis. A second, complementary analysis that directly compared the expression of 1320 genes between the species identified 409 genes that differed as a function of species or the interaction between time and species. Of these 409 DEGs, 84% exhibited higher abundances in tiger salamander larvae at all sampling times. Conclusions Many of the unique tiger salamander transcriptional responses are probably associated with metamorphic biological processes. However, the axolotl also showed unique patterns of transcription early in development. In particular, the axolotl showed a genome
At random meetings to the creation of new species of Salamander
Brillant, Marie-Pierre
2013-04-01
The pupils in final year of high school (15-18 years old) study the notion "species" and the creation of new species in various ways. Having studied genetic admixtures, this activity allows the pupils to build a scenario explaining the creation of a new species of Salamander in southern California from an ancestral population existing in northern Oregon. They can observe, on Google Earth, various populations of Salamander of the genus Ensatina. Salamanders of the genus Ensatina live in California around the Joaquin and Sacramento dry valleys. In this software, the pupils get information about the salamanders' environment and photographs of individuals and environments. During a migratory movement toward new territories to be colonized, these salamanders meet an inhospitable environment that they can not occupy. This population then splits up into two migratory branches, east and west, each overcoming the obstacles in different ways. The two groups gradually colonized southern territories but they avoided the too dry and hot San Joaquin plains. The two main branches of the original population gradually move away from each other, and genetic exchanges between them decrease over time. Eventually, we can find various populations of Salamander on both sides of the valleys, since the salamanders occupied new territories and diversified along the way. Among mutations that randomly occur, only those mutations that are best adapted in the origin were conserved in the genetic heritage of every population. When the individuals stemming from different western populations met, they were interfertile and give fertile hybrids, which was verified in the laboratory. Likewise, when individuals of the different eastern subspecies met accidentally, fertile hybrids also could arise from these crossings. The pupils can observe what happens in the overlap of various populations : interfertility or not. They also have geological, geographical and climatic information about the San Joaquin
Bayesian Inference on Gravitational Waves
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Asad Ali
2015-12-01
Full Text Available The Bayesian approach is increasingly becoming popular among the astrophysics data analysis communities. However, the Pakistan statistics communities are unaware of this fertile interaction between the two disciplines. Bayesian methods have been in use to address astronomical problems since the very birth of the Bayes probability in eighteenth century. Today the Bayesian methods for the detection and parameter estimation of gravitational waves have solid theoretical grounds with a strong promise for the realistic applications. This article aims to introduce the Pakistan statistics communities to the applications of Bayesian Monte Carlo methods in the analysis of gravitational wave data with an overview of the Bayesian signal detection and estimation methods and demonstration by a couple of simplified examples.
You, Xiuling; Sheng, Jianghong; Liu, Liu; Nie, Dongsong; Liao, Zhiyong
2015-10-01
Ferritin, an evolutionarily conserved iron-binding protein, plays important roles in iron storage and detoxification and in host immune response to invading stimulus as well. In the present study, we identified three ferritin subunit analog cDNAs from Chinese giant salamander (Andrias davidianus). All the three ferritin subunit cDNAs had a putative iron responsive element in the 5'-untranslated region. Two deduced ferritin subunits (designated as cgsFerH and cgsFerM) had the highest identity of 90% to H type subunit of vertebrate ferritins, while another deduced ferritin subunit (designated as cgsFerL) had the highest identity of 84% to L type subunit of vertebrate ferritins. The Chinese giant salamander ferritin (cgsFer) was widely expressed in various tissues, with highest expression for cgsFerH and cgsFerL in liver and highest expression for cgsFerM in spleen. Infection of Chinese giant salamander with A. davidianus ranavirus showed significant induction of cgsFer expression. Both lipopolysaccharide and iron challenge drastically augmented cgsFer expression in the splenocytes and hepatocytes from Chinese giant salamander. In addition, recombinant cgsFers bound to ferrous iron in a dose-dependent manner, with significant ferroxidase activity. Furthermore, the recombinant cgsFer inhibited the growth of the pathogen Vibrio anguillarum. These results indicated that cgsFer was potential candidate of immune molecules involved in acute phase response to invading microbial pathogens in Chinese giant salamander possibly through its regulatory roles in iron homeostasis. PMID:26319314
Bayesian networks as a tool for epidemiological systems analysis
Lewis, F. I.
2012-11-01
Bayesian network analysis is a form of probabilistic modeling which derives from empirical data a directed acyclic graph (DAG) describing the dependency structure between random variables. Bayesian networks are increasingly finding application in areas such as computational and systems biology, and more recently in epidemiological analyses. The key distinction between standard empirical modeling approaches, such as generalised linear modeling, and Bayesian network analyses is that the latter attempts not only to identify statistically associated variables, but to additionally, and empirically, separate these into those directly and indirectly dependent with one or more outcome variables. Such discrimination is vastly more ambitious but has the potential to reveal far more about key features of complex disease systems. Applying Bayesian network modeling to biological and medical data has considerable computational demands, combined with the need to ensure robust model selection given the vast model space of possible DAGs. These challenges require the use of approximation techniques, such as the Laplace approximation, Markov chain Monte Carlo simulation and parametric bootstrapping, along with computational parallelization. A case study in structure discovery - identification of an optimal DAG for given data - is presented which uses additive Bayesian networks to explore veterinary disease data of industrial and medical relevance.
Bayesian analysis of cosmic structures
Kitaura, Francisco-Shu
2011-01-01
We revise the Bayesian inference steps required to analyse the cosmological large-scale structure. Here we make special emphasis in the complications which arise due to the non-Gaussian character of the galaxy and matter distribution. In particular we investigate the advantages and limitations of the Poisson-lognormal model and discuss how to extend this work. With the lognormal prior using the Hamiltonian sampling technique and on scales of about 4 h^{-1} Mpc we find that the over-dense regions are excellent reconstructed, however, under-dense regions (void statistics) are quantitatively poorly recovered. Contrary to the maximum a posteriori (MAP) solution which was shown to over-estimate the density in the under-dense regions we obtain lower densities than in N-body simulations. This is due to the fact that the MAP solution is conservative whereas the full posterior yields samples which are consistent with the prior statistics. The lognormal prior is not able to capture the full non-linear regime at scales ...
Implementing Bayesian Vector Autoregressions Implementing Bayesian Vector Autoregressions
Directory of Open Access Journals (Sweden)
Richard M. Todd
1988-03-01
Full Text Available Implementing Bayesian Vector Autoregressions This paper discusses how the Bayesian approach can be used to construct a type of multivariate forecasting model known as a Bayesian vector autoregression (BVAR. In doing so, we mainly explain Doan, Littermann, and Sims (1984 propositions on how to estimate a BVAR based on a certain family of prior probability distributions. indexed by a fairly small set of hyperparameters. There is also a discussion on how to specify a BVAR and set up a BVAR database. A 4-variable model is used to iliustrate the BVAR approach.
Directory of Open Access Journals (Sweden)
Michael R. Warburg
2007-11-01
Full Text Available This is a long-term study (1974-1999 on the phenology of the rare, xeric- inhabiting salamander Salamandra infraimmaculata in a small isolated population during the breeding season near the breeding ponds on Mt. Carmel. This is a fringe area of the genus’ south-easternmost Palaearctic distribution. Salamanders were captured during the 25 year long study. The first years up to the 1980s the total number of salamanders increased but during the last years there seems to have been a decline. Although this could be a phase in normal population cyclic oscillations nevertheless when compared with long-term data on a European Salamandra it does not seem so. The interpretation of the species’ status is dependent on numbers of salamanders captured as well as on the duration of the study. These subjects are reviewed and discussed in this paper.
US Fish and Wildlife Service, Department of the Interior — This outlines the results of field surveys that were conducted for the Cheat Mountain salamander on the Kelley property on three mountains in the Cabin Mountain...
Currens, C.R.; Liss, W.J.; Hoffman, R.L.
2007-01-01
The formation of amphibian population structure is directly affected by predation. Although aquatic predators have been shown to have direct negative effects on larval salamanders in laboratory and field experiments, the potential impacts of gape-limited fish on larval salamander growth has been largely underexplored. We designed an enclosure experiment conducted in situ to quantify the effects of gape-limited Brook Trout (Salvelinus fontinalis) on larval Northwestern Salamander (Ambystoma gracile) growth. We specifically tested whether the presence of fish too small to consume larvae had a negative effect on larval growth. The results of this study indicate that the presence of a gape-limited S. fontinalis can have a negative effect on growth of larval A. gracile salamanders. Copyright 2007 Society for the Study of Amphibians and Reptiles.
Bayesian Analysis of Type Ia Supernova Data
Institute of Scientific and Technical Information of China (English)
王晓峰; 周旭; 李宗伟; 陈黎
2003-01-01
Recently, the distances to type Ia supernova (SN Ia) at z ～ 0.5 have been measured with the motivation of estimating cosmological parameters. However, different sleuthing techniques tend to give inconsistent measurements for SN Ia distances (～0.3 mag), which significantly affects the determination of cosmological parameters.A Bayesian "hyper-parameter" procedure is used to analyse jointly the current SN Ia data, which considers the relative weights of different datasets. For a flat Universe, the combining analysis yields ΩM = 0.20 ± 0.07.
Dynamic Bayesian diffusion estimation
Dedecius, K
2012-01-01
The rapidly increasing complexity of (mainly wireless) ad-hoc networks stresses the need of reliable distributed estimation of several variables of interest. The widely used centralized approach, in which the network nodes communicate their data with a single specialized point, suffers from high communication overheads and represents a potentially dangerous concept with a single point of failure needing special treatment. This paper's aim is to contribute to another quite recent method called diffusion estimation. By decentralizing the operating environment, the network nodes communicate just within a close neighbourhood. We adopt the Bayesian framework to modelling and estimation, which, unlike the traditional approaches, abstracts from a particular model case. This leads to a very scalable and universal method, applicable to a wide class of different models. A particularly interesting case - the Gaussian regressive model - is derived as an example.
Book review: Bayesian analysis for population ecology
Link, William A.
2011-01-01
Brian Dennis described the field of ecology as “fertile, uncolonized ground for Bayesian ideas.” He continued: “The Bayesian propagule has arrived at the shore. Ecologists need to think long and hard about the consequences of a Bayesian ecology. The Bayesian outlook is a successful competitor, but is it a weed? I think so.” (Dennis 2004)
Bayesian model discrimination for glucose-insulin homeostasis
DEFF Research Database (Denmark)
Andersen, Kim Emil; Brooks, Stephen P.; Højbjerre, Malene
In this paper we analyse a set of experimental data on a number of healthy and diabetic patients and discuss a variety of models for describing the physiological processes involved in glucose absorption and insulin secretion within the human body. We adopt a Bayesian approach which facilitates...... the reformulation of existing deterministic models as stochastic state space models which properly accounts for both measurement and process variability. The analysis is further enhanced by Bayesian model discrimination techniques and model averaged parameter estimation which fully accounts for model as well...
Current trends in Bayesian methodology with applications
Upadhyay, Satyanshu K; Dey, Dipak K; Loganathan, Appaia
2015-01-01
Collecting Bayesian material scattered throughout the literature, Current Trends in Bayesian Methodology with Applications examines the latest methodological and applied aspects of Bayesian statistics. The book covers biostatistics, econometrics, reliability and risk analysis, spatial statistics, image analysis, shape analysis, Bayesian computation, clustering, uncertainty assessment, high-energy astrophysics, neural networking, fuzzy information, objective Bayesian methodologies, empirical Bayes methods, small area estimation, and many more topics.Each chapter is self-contained and focuses on
Irregular-Time Bayesian Networks
Ramati, Michael
2012-01-01
In many fields observations are performed irregularly along time, due to either measurement limitations or lack of a constant immanent rate. While discrete-time Markov models (as Dynamic Bayesian Networks) introduce either inefficient computation or an information loss to reasoning about such processes, continuous-time Markov models assume either a discrete state space (as Continuous-Time Bayesian Networks), or a flat continuous state space (as stochastic dif- ferential equations). To address these problems, we present a new modeling class called Irregular-Time Bayesian Networks (ITBNs), generalizing Dynamic Bayesian Networks, allowing substantially more compact representations, and increasing the expressivity of the temporal dynamics. In addition, a globally optimal solution is guaranteed when learning temporal systems, provided that they are fully observed at the same irregularly spaced time-points, and a semiparametric subclass of ITBNs is introduced to allow further adaptation to the irregular nature of t...
Neuronanatomy, neurology and Bayesian networks
Bielza Lozoya, Maria Concepcion
2014-01-01
Bayesian networks are data mining models with clear semantics and a sound theoretical foundation. In this keynote talk we will pinpoint a number of neuroscience problems that can be addressed using Bayesian networks. In neuroanatomy, we will show computer simulation models of dendritic trees and classification of neuron types, both based on morphological features. In neurology, we will present the search for genetic biomarkers in Alzheimer's disease and the prediction of health-related qualit...
Keinath, Melissa C; Timoshevskiy, Vladimir A; Timoshevskaya, Nataliya Y; Tsonis, Panagiotis A; Voss, S Randal; Smith, Jeramiah J
2015-01-01
Vertebrates exhibit substantial diversity in genome size, and some of the largest genomes exist in species that uniquely inform diverse areas of basic and biomedical research. For example, the salamander Ambystoma mexicanum (the Mexican axolotl) is a model organism for studies of regeneration, development and genome evolution, yet its genome is ~10× larger than the human genome. As part of a hierarchical approach toward improving genome resources for the species, we generated 600 Gb of shotgun sequence data and developed methods for sequencing individual laser-captured chromosomes. Based on these data, we estimate that the A. mexicanum genome is ~32 Gb. Notably, as much as 19 Gb of the A. mexicanum genome can potentially be considered single copy, which presumably reflects the evolutionary diversification of mobile elements that accumulated during an ancient episode of genome expansion. Chromosome-targeted sequencing permitted the development of assemblies within the constraints of modern computational platforms, allowed us to place 2062 genes on the two smallest A. mexicanum chromosomes and resolves key events in the history of vertebrate genome evolution. Our analyses show that the capture and sequencing of individual chromosomes is likely to provide valuable information for the systematic sequencing, assembly and scaffolding of large genomes. PMID:26553646
Keinath, Melissa C; Timoshevskiy, Vladimir A; Timoshevskaya, Nataliya Y; Tsonis, Panagiotis A; Voss, S Randal; Smith, Jeramiah J
2015-11-10
Vertebrates exhibit substantial diversity in genome size, and some of the largest genomes exist in species that uniquely inform diverse areas of basic and biomedical research. For example, the salamander Ambystoma mexicanum (the Mexican axolotl) is a model organism for studies of regeneration, development and genome evolution, yet its genome is ~10× larger than the human genome. As part of a hierarchical approach toward improving genome resources for the species, we generated 600 Gb of shotgun sequence data and developed methods for sequencing individual laser-captured chromosomes. Based on these data, we estimate that the A. mexicanum genome is ~32 Gb. Notably, as much as 19 Gb of the A. mexicanum genome can potentially be considered single copy, which presumably reflects the evolutionary diversification of mobile elements that accumulated during an ancient episode of genome expansion. Chromosome-targeted sequencing permitted the development of assemblies within the constraints of modern computational platforms, allowed us to place 2062 genes on the two smallest A. mexicanum chromosomes and resolves key events in the history of vertebrate genome evolution. Our analyses show that the capture and sequencing of individual chromosomes is likely to provide valuable information for the systematic sequencing, assembly and scaffolding of large genomes.
A Bayesian approach to combining animal abundance and demographic data
Directory of Open Access Journals (Sweden)
Brooks, S. P.
2004-06-01
Full Text Available In studies of wild animals, one frequently encounters both count and mark-recapture-recovery data. Here, we consider an integrated Bayesian analysis of ring¿recovery and count data using a state-space model. We then impose a Leslie-matrix-based model on the true population counts describing the natural birth-death and age transition processes. We focus upon the analysis of both count and recovery data collected on British lapwings (Vanellus vanellus combined with records of the number of frost days each winter. We demonstrate how the combined analysis of these data provides a more robust inferential framework and discuss how the Bayesian approach using MCMC allows us to remove the potentially restrictive normality assumptions commonly assumed for analyses of this sort. It is shown how WinBUGS may be used to perform the Bayesian analysis. WinBUGS code is provided and its performance is critically discussed.
Distribution of the Sonora Tiger Salamander (Ambystoma mavortium stebbinsi) in Mexico
Hossack, Blake R.; Muths, Erin L.; Rorabaugh, James C.; Lemos Espinal, Julio A.; Sigafus, Brent H.; Chambert, Thierry A; Carreon Arroyo, Gerardo; Hurtado Felix, David; Toyos Martinez, Daniel; Jones, Thomas R
2016-01-01
The Sonoran Tiger Salamander (Ambystoma mavortium stebbinsi Lowe, 1954) was listed as federally endangered in the USA in 1997 (USFWS 1997). In the USA, the distribution of A. mavortium stebbinsi is limited to the San Rafael Valley (approximately 567 km2), between the Sierra San Antonio (called the Patagonia Mountains in Arizona) and Huachuca Mountains, and south of the Canelo Hills, Arizona (Fig. 1). The USA listing was triggered by loss of natural wetland habitats, threats from invasive predators, frequent die-offs from disease, introgression with the introduced Barred Tiger Salamander (A. mavortium mavortium), and small range and number of breeding sites that increases susceptibility to stochastic events (USFWS 1997). Small population sizes and limited gene flow have caused inbreeding, which may further reduce population viability and the potential for recovery (Jones et al. 1988; Storfer et al. 2014).
Elite Athletes Refine Their Internal Clocks: A Bayesian Analysis.
Chen, Yin-Hua; Verdinelli, Isabella; Cesari, Paola
2016-07-01
This paper carries out a full Bayesian analysis for a data set examined in Chen & Cesari (2015). These data were collected for assessing people's ability in evaluating short intervals of time. Chen & Cesari (2015) showed evidence of the existence of two independent internal clocks for evaluating time intervals below and above the second. We reexamine here, the same question by performing a complete statistical Bayesian analysis of the data. The Bayesian approach can be used to analyze these data thanks to the specific trial design. Data were obtained from evaluation of time ranges from two groups of individuals. More specifically, information gathered from a nontrained group (considered as baseline) allowed us to build a prior distribution for the parameter(s) of interest, and data from the trained group determined the likelihood function. This paper's main goals are (i) showing how the Bayesian inferential method can be used in statistical analyses and (ii) showing that the Bayesian methodology gives additional support to the findings presented in Chen & Cesari (2015) regarding the existence of two internal clocks in assessing duration of time intervals.
Dale Poirier
2008-01-01
This paper provides Bayesian rationalizations for White’s heteroskedastic consistent (HC) covariance estimator and various modifications of it. An informed Bayesian bootstrap provides the statistical framework.
Martínez-Solano Iñigo; Lawson Robin
2009-01-01
Abstract Background Island populations are excellent model systems for studies of phenotypic, ecological and molecular evolution. In this study, molecular markers of mitochondrial and nuclear derivation were used to investigate the evolution, structure and origin of populations of the California slender salamander (Batrachoseps attenuatus) inhabiting the six major islands of San Francisco Bay, formed following the rising of sea level around 9,000 years ago. Results There was a high degree of ...
Directory of Open Access Journals (Sweden)
Clint R V Otto
Full Text Available Habitat degradation resulting from anthropogenic activities poses immediate and prolonged threats to biodiversity, particularly among declining amphibians. Many studies infer amphibian response to habitat degradation by correlating patterns in species occupancy or abundance with environmental effects, often without regard to the demographic processes underlying these patterns. We evaluated how retention of vertical green trees (CANOPY and coarse woody debris (CWD influenced terrestrial salamander abundance and apparent survival in recently clearcut forests. Estimated abundance of unmarked salamanders was positively related to CANOPY (β Canopy = 0.21 (0.02-1.19; 95% CI, but not CWD (β CWD = 0.11 (-0.13-0.35 within 3,600 m2 sites, whereas estimated abundance of unmarked salamanders was not related to CANOPY (β Canopy = -0.01 (-0.21-0.18 or CWD (β CWD = -0.02 (-0.23-0.19 for 9 m2 enclosures. In contrast, apparent survival of marked salamanders within our enclosures over 1 month was positively influenced by both CANOPY and CWD retention (β Canopy = 0.73 (0.27-1.19; 95% CI and β CWD = 1.01 (0.53-1.50. Our results indicate that environmental correlates to abundance are scale dependent reflecting habitat selection processes and organism movements after a habitat disturbance event. Our study also provides a cautionary example of how scientific inference is conditional on the response variable(s, and scale(s of measure chosen by the investigator, which can have important implications for species conservation and management. Our research highlights the need for joint evaluation of population state variables, such as abundance, and population-level process, such as survival, when assessing anthropogenic impacts on forest biodiversity.
Ancient DNA Assessment of Tiger Salamander Population in Yellowstone National Park
McMenamin, Sarah K.; Hadly, Elizabeth A.
2012-01-01
Recent data indicates that blotched tiger salamanders (Ambystoma tigrinum melanostictum) in northern regions of Yellowstone National Park are declining due to climate-related habitat changes. In this study, we used ancient and modern mitochondrial haplotype diversity to model the effective size of this amphibian population through recent geological time and to assess past responses to climatic changes in the region. Using subfossils collected from a cave in northern Yellowstone, we analyzed >...
Environmental factors determining growth of salamander larvae：A field study
Institute of Scientific and Technical Information of China (English)
Laura LIMONGI; Gentile Francesco FICETOLA; Giuseppe ROMEO; Raoul MANENTI
2015-01-01
Larval growth and survival of organisms are strongly influenced by abiotic and biotic factors, as demonstrated by ex-perimental studies performed under controlled laboratory or semi-natural conditions. Even if they have many advantages, ex-periments cannot cover the full complexity of natural conditions and field studies are needed for a better understanding of how environmental variation determines growth and development rate. Fire salamanderSalamandra salamandrafemales give birth to larvae in a variety of habitats, both epigean and subterranean. In caves, salamander larvae successfully grow and metamorphose, but their growth is more than three times longer than in epigean streams and factors determining these differences require inves-tigation. We performed a field study to understand the factors related to the growth of fire salamander larvae in different envi-ronmental conditions, evaluating the relationship between environmental features and larval growth and differences between caves and epigean spring habitats. Both caves and epigean larvae successfully grew. Capture-mark-recapture allowed to individu-ally track individuals along their whole development, and measure their performance. Growth rate was significantly affected by environmental variables: larvae grew faster in environments with abundant invertebrates and few conspecifics. Taking into ac-count the effect of environmental variables, larval growth was significantly lower in caves. Food availability plays a different ef-fect in the two environments. Larval growth was positively related to the availability of invertebrates in epigean sites only. The development rate of hypogeous populations of salamanders is slower because of multiple parameters, but biotic factors play a much stronger role than the abiotic ones [Current Zoology 61 (3): 421–427, 2015].
Marcec, Ruth; Kouba, Andrew; Zhang, Lu; Zhang, Hongxing; Wang, Qijun; Zhao, Hu; Jiang, Wei; Willard, Scott
2016-03-01
Worldwide, there are only a handful of reintroduction programs for threatened salamander species, and very few have conducted postrelease studies to examine survival, habitat selection, and dispersal. Limitations in postrelease monitoring are primarily due to size constraints of amphibians and to dimensions of the radiotransmitters available for implantation. However, due to the large size of the critically endangered Chinese giant salamander (Andrias davidianus), these animals make optimal candidates for surgical implantation of radiotransmitters prior to reintroduction or translocation. The objective of this study was to develop an anesthetic protocol using tricane methanesulfonate (MS-222) and test a surgical procedure for coelomic implantation of radiotransmitters for this species. A total of 32 Chinese giant salamanders from two age groups (Group A: 4.7 yr old, n = 16; Group B: 2.7 yr old, n = 16) were implanted with 4-g radiotransmitters designed for underwater monitoring of fish. Group A was held 16 wk before release while Group B was held 6 wk before release, and the salamanders' survival and postoperative complications recorded for the first month postrelease. Group A animals took longer to reach a surgical plane of anesthesia than did Group B animals, and this was directly correlated to mass of the animals. Postsurgery, one animal from Group B died of dehiscence before release while 83.9% animals survived after the first month in the wild. All of the animals that died postrelease were from Group B; three animals experienced dehiscence of the suture site and died while another two animals expired from trauma and fungal infection, respectively. Improvements for future studies include use of alternative suture material for closure after implantation and additional healing time of the incision. PMID:27010279
Dynamic Batch Bayesian Optimization
Azimi, Javad; Fern, Xiaoli
2011-01-01
Bayesian optimization (BO) algorithms try to optimize an unknown function that is expensive to evaluate using minimum number of evaluations/experiments. Most of the proposed algorithms in BO are sequential, where only one experiment is selected at each iteration. This method can be time inefficient when each experiment takes a long time and more than one experiment can be ran concurrently. On the other hand, requesting a fix-sized batch of experiments at each iteration causes performance inefficiency in BO compared to the sequential policies. In this paper, we present an algorithm that asks a batch of experiments at each time step t where the batch size p_t is dynamically determined in each step. Our algorithm is based on the observation that the sequence of experiments selected by the sequential policy can sometimes be almost independent from each other. Our algorithm identifies such scenarios and request those experiments at the same time without degrading the performance. We evaluate our proposed method us...
Nonparametric Bayesian Classification
Coram, M A
2002-01-01
A Bayesian approach to the classification problem is proposed in which random partitions play a central role. It is argued that the partitioning approach has the capacity to take advantage of a variety of large-scale spatial structures, if they are present in the unknown regression function $f_0$. An idealized one-dimensional problem is considered in detail. The proposed nonparametric prior uses random split points to partition the unit interval into a random number of pieces. This prior is found to provide a consistent estimate of the regression function in the $\\L^p$ topology, for any $1 \\leq p < \\infty$, and for arbitrary measurable $f_0:[0,1] \\rightarrow [0,1]$. A Markov chain Monte Carlo (MCMC) implementation is outlined and analyzed. Simulation experiments are conducted to show that the proposed estimate compares favorably with a variety of conventional estimators. A striking resemblance between the posterior mean estimate and the bagged CART estimate is noted and discussed. For higher dimensions, a ...
Evidence for the local evolution of mechanisms underlying limb regeneration in salamanders.
Garza-Garcia, A Acely; Driscoll, Paul C; Brockes, Jeremy P
2010-10-01
The most extensive regenerative ability in adult vertebrates is found in the salamanders. Although it is often suggested that regeneration is an ancestral property for vertebrates, our studies on the cell-surface three-finger-protein Prod 1 provide clear evidence for the importance of local evolution of limb regeneration in salamanders. Prod 1 is implicated in both patterning and growth in the regeneration of limbs. It interacts with well-conserved proteins such as the epidermal growth-factor receptor and the anterior gradient protein that are widely expressed in phylogeny. A detailed analysis of the structure and sequence of Prod 1 in relation to other vertebrate three-finger proteins in mammals and zebra fish supports the view that it is a salamander-specific protein. This is the first example of a taxon-specific protein that is clearly implicated in the mechanisms of regeneration. We propose the hypothesis that regeneration depends on the activity of taxon-specific components in orchestrating a cellular machinery that is extensively conserved between regenerating and non-regenerating taxa. This hypothesis has significant implications for our outlook on regeneration in vertebrates, as well as for the strategies employed in extending regenerative ability in mammals.
Muletz, Carly; Caruso, Nicholas M.; Fleischer, Robert C.; McDiarmid, Roy W.; Lips, Karen R.
2014-01-01
Widespread population declines in terrestrial Plethodon salamanders occurred by the 1980s throughout the Appalachian Mountains, the center of global salamander diversity, with no evident recovery. We tested the hypothesis that the historic introduction and spread of the pathogenic fungus Batrachochytrium dendrobatidis (Bd) into the eastern US was followed by Plethodon population declines. We expected to detect elevated prevalence of Bd prior to population declines as observed for Central American plethodontids. We tested 1,498 Plethodon salamanders of 12 species (892 museum specimens, 606 wild individuals) for the presence of Bd, and tested 94 of those for Batrachochytrium salamandrivorans (Bs) and for ranavirus. Field samples were collected in 2011 from 48 field sites across a 767 km transect. Historic samples from museum specimens were collected at five sites with the greatest number and longest duration of collection (1957–987), four of which were sampled in the field in 2011. None of the museum specimens were positive for Bd, but four P. cinereus from field surveys were positive. The overall Bd prevalence from 1957–2011 for 12 Plethodon species sampled across a 757 km transect was 0.2% (95% CI 0.1–0.7%). All 94 samples were negative for Bs and ranavirus. We conclude that known amphibian pathogens are unlikely causes for declines in these Plethodon populations. Furthermore, these exceptionally low levels of Bd, in a region known to harbor Bd, may indicate that Plethodon specific traits limit Bd infection. PMID:25084159
Muletz, Carly; Caruso, Nicholas M; Fleischer, Robert C; McDiarmid, Roy W; Lips, Karen R
2014-01-01
Widespread population declines in terrestrial Plethodon salamanders occurred by the 1980s throughout the Appalachian Mountains, the center of global salamander diversity, with no evident recovery. We tested the hypothesis that the historic introduction and spread of the pathogenic fungus Batrachochytrium dendrobatidis (Bd) into the eastern US was followed by Plethodon population declines. We expected to detect elevated prevalence of Bd prior to population declines as observed for Central American plethodontids. We tested 1,498 Plethodon salamanders of 12 species (892 museum specimens, 606 wild individuals) for the presence of Bd, and tested 94 of those for Batrachochytrium salamandrivorans (Bs) and for ranavirus. Field samples were collected in 2011 from 48 field sites across a 767 km transect. Historic samples from museum specimens were collected at five sites with the greatest number and longest duration of collection (1957-987), four of which were sampled in the field in 2011. None of the museum specimens were positive for Bd, but four P. cinereus from field surveys were positive. The overall Bd prevalence from 1957-2011 for 12 Plethodon species sampled across a 757 km transect was 0.2% (95% CI 0.1-0.7%). All 94 samples were negative for Bs and ranavirus. We conclude that known amphibian pathogens are unlikely causes for declines in these Plethodon populations. Furthermore, these exceptionally low levels of Bd, in a region known to harbor Bd, may indicate that Plethodon specific traits limit Bd infection.
Directory of Open Access Journals (Sweden)
Carly Muletz
Full Text Available Widespread population declines in terrestrial Plethodon salamanders occurred by the 1980s throughout the Appalachian Mountains, the center of global salamander diversity, with no evident recovery. We tested the hypothesis that the historic introduction and spread of the pathogenic fungus Batrachochytrium dendrobatidis (Bd into the eastern US was followed by Plethodon population declines. We expected to detect elevated prevalence of Bd prior to population declines as observed for Central American plethodontids. We tested 1,498 Plethodon salamanders of 12 species (892 museum specimens, 606 wild individuals for the presence of Bd, and tested 94 of those for Batrachochytrium salamandrivorans (Bs and for ranavirus. Field samples were collected in 2011 from 48 field sites across a 767 km transect. Historic samples from museum specimens were collected at five sites with the greatest number and longest duration of collection (1957-987, four of which were sampled in the field in 2011. None of the museum specimens were positive for Bd, but four P. cinereus from field surveys were positive. The overall Bd prevalence from 1957-2011 for 12 Plethodon species sampled across a 757 km transect was 0.2% (95% CI 0.1-0.7%. All 94 samples were negative for Bs and ranavirus. We conclude that known amphibian pathogens are unlikely causes for declines in these Plethodon populations. Furthermore, these exceptionally low levels of Bd, in a region known to harbor Bd, may indicate that Plethodon specific traits limit Bd infection.
Genic regions of a large salamander genome contain long introns and novel genes
Directory of Open Access Journals (Sweden)
Bryant Susan V
2009-01-01
Full Text Available Abstract Background The basis of genome size variation remains an outstanding question because DNA sequence data are lacking for organisms with large genomes. Sixteen BAC clones from the Mexican axolotl (Ambystoma mexicanum: c-value = 32 × 109 bp were isolated and sequenced to characterize the structure of genic regions. Results Annotation of genes within BACs showed that axolotl introns are on average 10× longer than orthologous vertebrate introns and they are predicted to contain more functional elements, including miRNAs and snoRNAs. Loci were discovered within BACs for two novel EST transcripts that are differentially expressed during spinal cord regeneration and skin metamorphosis. Unexpectedly, a third novel gene was also discovered while manually annotating BACs. Analysis of human-axolotl protein-coding sequences suggests there are 2% more lineage specific genes in the axolotl genome than the human genome, but the great majority (86% of genes between axolotl and human are predicted to be 1:1 orthologs. Considering that axolotl genes are on average 5× larger than human genes, the genic component of the salamander genome is estimated to be incredibly large, approximately 2.8 gigabases! Conclusion This study shows that a large salamander genome has a correspondingly large genic component, primarily because genes have incredibly long introns. These intronic sequences may harbor novel coding and non-coding sequences that regulate biological processes that are unique to salamanders.
Zabierek, Kristina C; Gabor, Caitlin R
2016-09-01
Prey may use multiple sensory channels to detect predators, whose cues may differ in altered sensory environments, such as turbid conditions. Depending on the environment, prey may use cues in an additive/complementary manner or in a compensatory manner. First, to determine whether the purely aquatic Barton Springs salamander, Eurycea sosorum, show an antipredator response to visual cues, we examined their activity when exposed to either visual cues of a predatory fish (Lepomis cyanellus) or a non-predatory fish (Etheostoma lepidum). Salamanders decreased activity in response to predator visual cues only. Then, we examined the antipredator response of these salamanders to all matched and mismatched combinations of chemical and visual cues of the same predatory and non-predatory fish in clear and low turbidity conditions. Salamanders decreased activity in response to predator chemical cues matched with predator visual cues or mismatched with non-predator visual cues. Salamanders also increased latency to first move to predator chemical cues mismatched with non-predator visual cues. Salamanders decreased activity and increased latency to first move more in clear as opposed to turbid conditions in all treatment combinations. Our results indicate that salamanders under all conditions and treatments preferentially rely on chemical cues to determine antipredator behavior, although visual cues are potentially utilized in conjunction for latency to first move. Our results also have potential conservation implications, as decreased antipredator behavior was seen in turbid conditions. These results reveal complexity of antipredator behavior in response to multiple cues under different environmental conditions, which is especially important when considering endangered species.
Zabierek, Kristina C; Gabor, Caitlin R
2016-09-01
Prey may use multiple sensory channels to detect predators, whose cues may differ in altered sensory environments, such as turbid conditions. Depending on the environment, prey may use cues in an additive/complementary manner or in a compensatory manner. First, to determine whether the purely aquatic Barton Springs salamander, Eurycea sosorum, show an antipredator response to visual cues, we examined their activity when exposed to either visual cues of a predatory fish (Lepomis cyanellus) or a non-predatory fish (Etheostoma lepidum). Salamanders decreased activity in response to predator visual cues only. Then, we examined the antipredator response of these salamanders to all matched and mismatched combinations of chemical and visual cues of the same predatory and non-predatory fish in clear and low turbidity conditions. Salamanders decreased activity in response to predator chemical cues matched with predator visual cues or mismatched with non-predator visual cues. Salamanders also increased latency to first move to predator chemical cues mismatched with non-predator visual cues. Salamanders decreased activity and increased latency to first move more in clear as opposed to turbid conditions in all treatment combinations. Our results indicate that salamanders under all conditions and treatments preferentially rely on chemical cues to determine antipredator behavior, although visual cues are potentially utilized in conjunction for latency to first move. Our results also have potential conservation implications, as decreased antipredator behavior was seen in turbid conditions. These results reveal complexity of antipredator behavior in response to multiple cues under different environmental conditions, which is especially important when considering endangered species. PMID:27370360
Bayesian seismic AVO inversion
Energy Technology Data Exchange (ETDEWEB)
Buland, Arild
2002-07-01
A new linearized AVO inversion technique is developed in a Bayesian framework. The objective is to obtain posterior distributions for P-wave velocity, S-wave velocity and density. Distributions for other elastic parameters can also be assessed, for example acoustic impedance, shear impedance and P-wave to S-wave velocity ratio. The inversion algorithm is based on the convolutional model and a linearized weak contrast approximation of the Zoeppritz equation. The solution is represented by a Gaussian posterior distribution with explicit expressions for the posterior expectation and covariance, hence exact prediction intervals for the inverted parameters can be computed under the specified model. The explicit analytical form of the posterior distribution provides a computationally fast inversion method. Tests on synthetic data show that all inverted parameters were almost perfectly retrieved when the noise approached zero. With realistic noise levels, acoustic impedance was the best determined parameter, while the inversion provided practically no information about the density. The inversion algorithm has also been tested on a real 3-D dataset from the Sleipner Field. The results show good agreement with well logs but the uncertainty is high. The stochastic model includes uncertainties of both the elastic parameters, the wavelet and the seismic and well log data. The posterior distribution is explored by Markov chain Monte Carlo simulation using the Gibbs sampler algorithm. The inversion algorithm has been tested on a seismic line from the Heidrun Field with two wells located on the line. The uncertainty of the estimated wavelet is low. In the Heidrun examples the effect of including uncertainty of the wavelet and the noise level was marginal with respect to the AVO inversion results. We have developed a 3-D linearized AVO inversion method with spatially coupled model parameters where the objective is to obtain posterior distributions for P-wave velocity, S
Grant, Evan H. Campbell; Muths, Erin L.; Katz, Rachel A.; Canessa, Stefano; Adams, Michael J.; Ballard, Jennifer R.; Berger, Lee; Briggs, Cheryl J.; Coleman, Jeremy; Gray, Matthew J.; Harris, M. Camille; Harris, Reid N.; Hossack, Blake R.; Huyvaert, Kathryn P.; Kolby, Jonathan E.; Lips, Karen R.; Lovich, Robert E.; McCallum, Hamish I.; Mendelson, Joseph R.; Nanjappa, Priya; Olson, Deanna H.; Powers, Jenny G.; Richgels, Katherine L.D.; Russell, Robin E.; Schmidt, Benedikt R.; Spitzen-van der Sluijs, Annemarieka; Watry, Mary Kay; Woodhams, Douglas C.; White, C. LeAnn
2016-01-20
The recently (2013) identified pathogenic chytrid fungus, Batrachochytrium salamandrivorans (Bsal), poses a severe threat to the distribution and abundance of salamanders within the United States and Europe. Development of a response strategy for the potential, and likely, invasion of Bsal into the United States is crucial to protect global salamander biodiversity. A formal working group, led by Amphibian Research and Monitoring Initiative (ARMI) scientists from the U.S. Geological Survey (USGS) Patuxent Wildlife Research Center, Fort Collins Science Center, and Forest and Rangeland Ecosystem Science Center, was held at the USGS Powell Center for Analysis and Synthesis in Fort Collins, Colorado, United States from June 23 to June 25, 2015, to identify crucial Bsal research and monitoring needs that could inform conservation and management strategies for salamanders in the United States. Key findings of the workshop included the following: (1) the introduction of Bsal into the United States is highly probable, if not inevitable, thus requiring development of immediate short-term and long-term intervention strategies to prevent Bsal establishment and biodiversity decline; (2) management actions targeted towards pathogen containment may be ineffective in reducing the long-term spread of Bsal throughout the United States; and (3) early detection of Bsal through surveillance at key amphibian import locations, among high-risk wild populations, and through analysis of archived samples is necessary for developing management responses. Top research priorities during the preinvasion stage included the following: (1) deployment of qualified diagnostic methods for Bsal and establishment of standardized laboratory practices, (2) assessment of susceptibility for amphibian hosts (including anurans), and (3) development and evaluation of short- and long-term pathogen intervention and management strategies. Several outcomes were achieved during the workshop, including development
Bayesian models for comparative analysis integrating phylogenetic uncertainty
Directory of Open Access Journals (Sweden)
Villemereuil Pierre de
2012-06-01
Full Text Available Abstract Background Uncertainty in comparative analyses can come from at least two sources: a phylogenetic uncertainty in the tree topology or branch lengths, and b uncertainty due to intraspecific variation in trait values, either due to measurement error or natural individual variation. Most phylogenetic comparative methods do not account for such uncertainties. Not accounting for these sources of uncertainty leads to false perceptions of precision (confidence intervals will be too narrow and inflated significance in hypothesis testing (e.g. p-values will be too small. Although there is some application-specific software for fitting Bayesian models accounting for phylogenetic error, more general and flexible software is desirable. Methods We developed models to directly incorporate phylogenetic uncertainty into a range of analyses that biologists commonly perform, using a Bayesian framework and Markov Chain Monte Carlo analyses. Results We demonstrate applications in linear regression, quantification of phylogenetic signal, and measurement error models. Phylogenetic uncertainty was incorporated by applying a prior distribution for the phylogeny, where this distribution consisted of the posterior tree sets from Bayesian phylogenetic tree estimation programs. The models were analysed using simulated data sets, and applied to a real data set on plant traits, from rainforest plant species in Northern Australia. Analyses were performed using the free and open source software OpenBUGS and JAGS. Conclusions Incorporating phylogenetic uncertainty through an empirical prior distribution of trees leads to more precise estimation of regression model parameters than using a single consensus tree and enables a more realistic estimation of confidence intervals. In addition, models incorporating measurement errors and/or individual variation, in one or both variables, are easily formulated in the Bayesian framework. We show that BUGS is a useful, flexible
Attention in a bayesian framework
DEFF Research Database (Denmark)
Whiteley, Louise Emma; Sahani, Maneesh
2012-01-01
The behavioral phenomena of sensory attention are thought to reflect the allocation of a limited processing resource, but there is little consensus on the nature of the resource or why it should be limited. Here we argue that a fundamental bottleneck emerges naturally within Bayesian models...... of perception, and use this observation to frame a new computational account of the need for, and action of, attention - unifying diverse attentional phenomena in a way that goes beyond previous inferential, probabilistic and Bayesian models. Attentional effects are most evident in cluttered environments......, and include both selective phenomena, where attention is invoked by cues that point to particular stimuli, and integrative phenomena, where attention is invoked dynamically by endogenous processing. However, most previous Bayesian accounts of attention have focused on describing relatively simple experimental...
Probability biases as Bayesian inference
Directory of Open Access Journals (Sweden)
Andre; C. R. Martins
2006-11-01
Full Text Available In this article, I will show how several observed biases in human probabilistic reasoning can be partially explained as good heuristics for making inferences in an environment where probabilities have uncertainties associated to them. Previous results show that the weight functions and the observed violations of coalescing and stochastic dominance can be understood from a Bayesian point of view. We will review those results and see that Bayesian methods should also be used as part of the explanation behind other known biases. That means that, although the observed errors are still errors under the be understood as adaptations to the solution of real life problems. Heuristics that allow fast evaluations and mimic a Bayesian inference would be an evolutionary advantage, since they would give us an efficient way of making decisions. %XX In that sense, it should be no surprise that humans reason with % probability as it has been observed.
Bayesian Methods and Universal Darwinism
Campbell, John
2010-01-01
Bayesian methods since the time of Laplace have been understood by their practitioners as closely aligned to the scientific method. Indeed a recent champion of Bayesian methods, E. T. Jaynes, titled his textbook on the subject Probability Theory: the Logic of Science. Many philosophers of science including Karl Popper and Donald Campbell have interpreted the evolution of Science as a Darwinian process consisting of a 'copy with selective retention' algorithm abstracted from Darwin's theory of Natural Selection. Arguments are presented for an isomorphism between Bayesian Methods and Darwinian processes. Universal Darwinism, as the term has been developed by Richard Dawkins, Daniel Dennett and Susan Blackmore, is the collection of scientific theories which explain the creation and evolution of their subject matter as due to the operation of Darwinian processes. These subject matters span the fields of atomic physics, chemistry, biology and the social sciences. The principle of Maximum Entropy states that system...
Bayesian modeling using WinBUGS
Ntzoufras, Ioannis
2009-01-01
A hands-on introduction to the principles of Bayesian modeling using WinBUGS Bayesian Modeling Using WinBUGS provides an easily accessible introduction to the use of WinBUGS programming techniques in a variety of Bayesian modeling settings. The author provides an accessible treatment of the topic, offering readers a smooth introduction to the principles of Bayesian modeling with detailed guidance on the practical implementation of key principles. The book begins with a basic introduction to Bayesian inference and the WinBUGS software and goes on to cover key topics, including: Markov Chain Monte Carlo algorithms in Bayesian inference Generalized linear models Bayesian hierarchical models Predictive distribution and model checking Bayesian model and variable evaluation Computational notes and screen captures illustrate the use of both WinBUGS as well as R software to apply the discussed techniques. Exercises at the end of each chapter allow readers to test their understanding of the presented concepts and all ...
Crocker, J.B.; Bank, M.S.; Loftin, C.S.; Jung Brown, R.E.
2007-01-01
We investigated effects of observers and stream flow on Northern Two-Lined Salamander (Eurycea bislineata bislineata) counts in streams in Acadia (ANP) and Shenandoah National Parks (SNP). We counted salamanders in 22 ANP streams during high flow (May to June 2002) and during low flow (July 2002). We also counted salamanders in SNP in nine streams during high flow (summer 2003) and 11 streams during low flow (summers 2001?02, 2004). In 2002, we used a modified cover-controlled active search method with a first and second observer. In succession, observers turned over 100 rocks along five 1-m belt transects across the streambed. The difference between observers in total salamander counts was not significant. We counted fewer E. b. bislineata during high flow conditions, confirming that detection of this species is reduced during high flow periods and that assessment of stream salamander relative abundance is likely more reliable during low or base flow conditions.
Phycas: software for Bayesian phylogenetic analysis.
Lewis, Paul O; Holder, Mark T; Swofford, David L
2015-05-01
Phycas is open source, freely available Bayesian phylogenetics software written primarily in C++ but with a Python interface. Phycas specializes in Bayesian model selection for nucleotide sequence data, particularly the estimation of marginal likelihoods, central to computing Bayes Factors. Marginal likelihoods can be estimated using newer methods (Thermodynamic Integration and Generalized Steppingstone) that are more accurate than the widely used Harmonic Mean estimator. In addition, Phycas supports two posterior predictive approaches to model selection: Gelfand-Ghosh and Conditional Predictive Ordinates. The General Time Reversible family of substitution models, as well as a codon model, are available, and data can be partitioned with all parameters unlinked except tree topology and edge lengths. Phycas provides for analyses in which the prior on tree topologies allows polytomous trees as well as fully resolved trees, and provides for several choices for edge length priors, including a hierarchical model as well as the recently described compound Dirichlet prior, which helps avoid overly informative induced priors on tree length. PMID:25577605
Case studies in Bayesian microbial risk assessments
Directory of Open Access Journals (Sweden)
Turner Joanne
2009-12-01
case study the effective number of inputs was reduced from 30 to 7 in the screening stage, and just 2 inputs were found to explain 82.8% of the output variance. A combined total of 500 runs of the computer code were used. Conclusion These case studies illustrate the use of Bayesian statistics to perform detailed uncertainty and sensitivity analyses, integrating multiple information sources in a way that is both rigorous and efficient.
Bayesian test and Kuhn's paradigm
Institute of Scientific and Technical Information of China (English)
Chen Xiaoping
2006-01-01
Kuhn's theory of paradigm reveals a pattern of scientific progress,in which normal science alternates with scientific revolution.But Kuhn underrated too much the function of scientific test in his pattern,because he focuses all his attention on the hypothetico-deductive schema instead of Bayesian schema.This paper employs Bayesian schema to re-examine Kuhn's theory of paradigm,to uncover its logical and rational components,and to illustrate the tensional structure of logic and belief,rationality and irrationality,in the process of scientific revolution.
Perception, illusions and Bayesian inference.
Nour, Matthew M; Nour, Joseph M
2015-01-01
Descriptive psychopathology makes a distinction between veridical perception and illusory perception. In both cases a perception is tied to a sensory stimulus, but in illusions the perception is of a false object. This article re-examines this distinction in light of new work in theoretical and computational neurobiology, which views all perception as a form of Bayesian statistical inference that combines sensory signals with prior expectations. Bayesian perceptual inference can solve the 'inverse optics' problem of veridical perception and provides a biologically plausible account of a number of illusory phenomena, suggesting that veridical and illusory perceptions are generated by precisely the same inferential mechanisms.
3D Bayesian contextual classifiers
DEFF Research Database (Denmark)
Larsen, Rasmus
2000-01-01
We extend a series of multivariate Bayesian 2-D contextual classifiers to 3-D by specifying a simultaneous Gaussian distribution for the feature vectors as well as a prior distribution of the class variables of a pixel and its 6 nearest 3-D neighbours.......We extend a series of multivariate Bayesian 2-D contextual classifiers to 3-D by specifying a simultaneous Gaussian distribution for the feature vectors as well as a prior distribution of the class variables of a pixel and its 6 nearest 3-D neighbours....
Bayesian methods for proteomic biomarker development
Directory of Open Access Journals (Sweden)
Belinda Hernández
2015-12-01
In this review we provide an introduction to Bayesian inference and demonstrate some of the advantages of using a Bayesian framework. We summarize how Bayesian methods have been used previously in proteomics and other areas of bioinformatics. Finally, we describe some popular and emerging Bayesian models from the statistical literature and provide a worked tutorial including code snippets to show how these methods may be applied for the evaluation of proteomic biomarkers.
Bayesian variable order Markov models: Towards Bayesian predictive state representations
C. Dimitrakakis
2009-01-01
We present a Bayesian variable order Markov model that shares many similarities with predictive state representations. The resulting models are compact and much easier to specify and learn than classical predictive state representations. Moreover, we show that they significantly outperform a more st
Bayesian networks and food security - An introduction
Stein, A.
2004-01-01
This paper gives an introduction to Bayesian networks. Networks are defined and put into a Bayesian context. Directed acyclical graphs play a crucial role here. Two simple examples from food security are addressed. Possible uses of Bayesian networks for implementation and further use in decision sup
Bayesian Model Averaging for Propensity Score Analysis
Kaplan, David; Chen, Jianshen
2013-01-01
The purpose of this study is to explore Bayesian model averaging in the propensity score context. Previous research on Bayesian propensity score analysis does not take into account model uncertainty. In this regard, an internally consistent Bayesian framework for model building and estimation must also account for model uncertainty. The…
A Bayesian Nonparametric Approach to Test Equating
Karabatsos, George; Walker, Stephen G.
2009-01-01
A Bayesian nonparametric model is introduced for score equating. It is applicable to all major equating designs, and has advantages over previous equating models. Unlike the previous models, the Bayesian model accounts for positive dependence between distributions of scores from two tests. The Bayesian model and the previous equating models are…
DeMali, Heather M; Trauth, Stanley E; Bouldin, Jennifer L
2016-06-01
The spotted salamander (Ambystoma maculatum) is indigenous to northern Arkansas, and several breeding sites are known to exist in the region. Spotted salamanders (n = 17) were collected and examined for parasites and only three females harbored nematodes (Physaloptera spp.). Chronic aquatic bioassays were conducted using water collected from eight breeding ponds during different hydroperiod events. No lethal or sublethal effects were measured in Ceriodaphnia dubia; however, decreased growth and survival were seen in Pimephales promelas. Aqueous, sediment, and salamander hepatic samples were analyzed for As, Cd, Cu, Pb, and Ni. Metal analysis revealed possible increased metal exposure following precipitation, with greatest metal concentrations measured in sediment samples. Hepatic metal concentrations were similar in parasitized and non-parasitized individuals, and greatest Pb concentrations were measured following normal precipitation events. Determining environmental stressors of amphibians, especially during their breeding and subsequent larval life stage, is imperative to improve species conservation. PMID:26886425
Bayesian Classification of Image Structures
DEFF Research Database (Denmark)
Goswami, Dibyendu; Kalkan, Sinan; Krüger, Norbert
2009-01-01
In this paper, we describe work on Bayesian classi ers for distinguishing between homogeneous structures, textures, edges and junctions. We build semi-local classiers from hand-labeled images to distinguish between these four different kinds of structures based on the concept of intrinsic dimensi...
Bayesian Agglomerative Clustering with Coalescents
Teh, Yee Whye; Daumé III, Hal; Roy, Daniel
2009-01-01
We introduce a new Bayesian model for hierarchical clustering based on a prior over trees called Kingman's coalescent. We develop novel greedy and sequential Monte Carlo inferences which operate in a bottom-up agglomerative fashion. We show experimentally the superiority of our algorithms over others, and demonstrate our approach in document clustering and phylolinguistics.
Bayesian NL interpretation and learning
H. Zeevat
2011-01-01
Everyday natural language communication is normally successful, even though contemporary computational linguistics has shown that NL is characterised by very high degree of ambiguity and the results of stochastic methods are not good enough to explain the high success rate. Bayesian natural language
Differentiated Bayesian Conjoint Choice Designs
Z. Sándor (Zsolt); M. Wedel (Michel)
2003-01-01
textabstractPrevious conjoint choice design construction procedures have produced a single design that is administered to all subjects. This paper proposes to construct a limited set of different designs. The designs are constructed in a Bayesian fashion, taking into account prior uncertainty about
Bayesian inference for Hawkes processes
DEFF Research Database (Denmark)
Rasmussen, Jakob Gulddahl
The Hawkes process is a practically and theoretically important class of point processes, but parameter-estimation for such a process can pose various problems. In this paper we explore and compare two approaches to Bayesian inference. The first approach is based on the so-called conditional...
Bayesian stable isotope mixing models
In this paper we review recent advances in Stable Isotope Mixing Models (SIMMs) and place them into an over-arching Bayesian statistical framework which allows for several useful extensions. SIMMs are used to quantify the proportional contributions of various sources to a mixtur...
Bayesian inference for Hawkes processes
DEFF Research Database (Denmark)
Rasmussen, Jakob Gulddahl
2013-01-01
The Hawkes process is a practically and theoretically important class of point processes, but parameter-estimation for such a process can pose various problems. In this paper we explore and compare two approaches to Bayesian inference. The first approach is based on the so-called conditional...
3-D contextual Bayesian classifiers
DEFF Research Database (Denmark)
Larsen, Rasmus
In this paper we will consider extensions of a series of Bayesian 2-D contextual classification pocedures proposed by Owen (1984) Hjort & Mohn (1984) and Welch & Salter (1971) and Haslett (1985) to 3 spatial dimensions. It is evident that compared to classical pixelwise classification further...
Bayesian image restoration, using configurations
DEFF Research Database (Denmark)
Thorarinsdottir, Thordis
configurations are expressed in terms of the mean normal measure of the random set. These probabilities are used as prior probabilities in a Bayesian image restoration approach. Estimation of the remaining parameters in the model is outlined for salt and pepper noise. The inference in the model is discussed...
Bayesian image restoration, using configurations
DEFF Research Database (Denmark)
Thorarinsdottir, Thordis Linda
2006-01-01
configurations are expressed in terms of the mean normal measure of the random set. These probabilities are used as prior probabilities in a Bayesian image restoration approach. Estimation of the remaining parameters in the model is outlined for the salt and pepper noise. The inference in the model is discussed...
Bayesian Analysis of Experimental Data
Directory of Open Access Journals (Sweden)
Lalmohan Bhar
2013-10-01
Full Text Available Analysis of experimental data from Bayesian point of view has been considered. Appropriate methodology has been developed for application into designed experiments. Normal-Gamma distribution has been considered for prior distribution. Developed methodology has been applied to real experimental data taken from long term fertilizer experiments.
Topics in Bayesian statistics and maximum entropy
International Nuclear Information System (INIS)
Notions of Bayesian decision theory and maximum entropy methods are reviewed with particular emphasis on probabilistic inference and Bayesian modeling. The axiomatic approach is considered as the best justification of Bayesian analysis and maximum entropy principle applied in natural sciences. Particular emphasis is put on solving the inverse problem in digital image restoration and Bayesian modeling of neural networks. Further topics addressed briefly include language modeling, neutron scattering, multiuser detection and channel equalization in digital communications, genetic information, and Bayesian court decision-making. (author)
Institute of Scientific and Technical Information of China (English)
徐伟良; 陈德经; 魏泓; 刘宇
2015-01-01
The study focuses on antioxidant performance and safety evaluation of acute toxicity of sala-mander skin mucus.The study first uses pyrogallol autoxidation and DPPH method to determine salamander mucus to superoxide anion radical( O-·2 ) scavenging and DPPH radical scavenging.Then it experiments with giant salamander breeding mice fed to test acute toxicity of Andrias davidianus skin mucus and analyses toxic constituents of mucus temperament by using GC-MS chromatography.The results show that the clearance rate of Salamander mucus flour to superoxide anion radical and to DPPH radical scavenging is 6.77%and 90.25%respectively, and that LD50 value of Andrias mucus powder is 4.64 g/kg and toxic ingredient is imethyl disul-fide ( C2 H6 S2 ) .It concludes that Andrias mucus is antioxidant and low in toxicity, and that it can be devel-oped for health care products after detoxification.%为研究大鲵皮肤黏液的抗氧化性及急毒性安全性评价，利用邻苯三酚自氧化法和DPPH法，测定了大鲵黏液对超氧阴离子自由基（ O－·2）及DPPH自由基的清除率；通过对小鼠灌胃饲养实验检测大鲵皮肤黏液的急毒性，并采用气质联用色谱分析黏液中的毒性成分。结果显示：大鲵黏液对超氧阴离子自由基的清除率为6．77％，对 DPPH 自由基的清除率为90．25％；大鲵黏液全粉的LD50值为4．64 g／kg，毒性成分为二甲基二硫醚（ C2 H6 S2）。表明大鲵黏液具有抗氧化性和低毒性，经脱毒后可开发为保健产品。
Institute of Scientific and Technical Information of China (English)
徐伟良; 陈德经; 魏泓; 刘宇
2015-01-01
为研究大鲵皮肤黏液的抗氧化性及急毒性安全性评价，利用邻苯三酚自氧化法和DPPH法，测定了大鲵黏液对超氧阴离子自由基（ O－·2）及DPPH自由基的清除率；通过对小鼠灌胃饲养实验检测大鲵皮肤黏液的急毒性，并采用气质联用色谱分析黏液中的毒性成分。结果显示：大鲵黏液对超氧阴离子自由基的清除率为6．77％，对 DPPH 自由基的清除率为90．25％；大鲵黏液全粉的LD50值为4．64 g／kg，毒性成分为二甲基二硫醚（ C2 H6 S2）。表明大鲵黏液具有抗氧化性和低毒性，经脱毒后可开发为保健产品。%The study focuses on antioxidant performance and safety evaluation of acute toxicity of sala-mander skin mucus.The study first uses pyrogallol autoxidation and DPPH method to determine salamander mucus to superoxide anion radical( O-·2 ) scavenging and DPPH radical scavenging.Then it experiments with giant salamander breeding mice fed to test acute toxicity of Andrias davidianus skin mucus and analyses toxic constituents of mucus temperament by using GC-MS chromatography.The results show that the clearance rate of Salamander mucus flour to superoxide anion radical and to DPPH radical scavenging is 6.77%and 90.25%respectively, and that LD50 value of Andrias mucus powder is 4.64 g/kg and toxic ingredient is imethyl disul-fide ( C2 H6 S2 ) .It concludes that Andrias mucus is antioxidant and low in toxicity, and that it can be devel-oped for health care products after detoxification.
Bayesian analysis of rare events
Straub, Daniel; Papaioannou, Iason; Betz, Wolfgang
2016-06-01
In many areas of engineering and science there is an interest in predicting the probability of rare events, in particular in applications related to safety and security. Increasingly, such predictions are made through computer models of physical systems in an uncertainty quantification framework. Additionally, with advances in IT, monitoring and sensor technology, an increasing amount of data on the performance of the systems is collected. This data can be used to reduce uncertainty, improve the probability estimates and consequently enhance the management of rare events and associated risks. Bayesian analysis is the ideal method to include the data into the probabilistic model. It ensures a consistent probabilistic treatment of uncertainty, which is central in the prediction of rare events, where extrapolation from the domain of observation is common. We present a framework for performing Bayesian updating of rare event probabilities, termed BUS. It is based on a reinterpretation of the classical rejection-sampling approach to Bayesian analysis, which enables the use of established methods for estimating probabilities of rare events. By drawing upon these methods, the framework makes use of their computational efficiency. These methods include the First-Order Reliability Method (FORM), tailored importance sampling (IS) methods and Subset Simulation (SuS). In this contribution, we briefly review these methods in the context of the BUS framework and investigate their applicability to Bayesian analysis of rare events in different settings. We find that, for some applications, FORM can be highly efficient and is surprisingly accurate, enabling Bayesian analysis of rare events with just a few model evaluations. In a general setting, BUS implemented through IS and SuS is more robust and flexible.
Can the eastern red-backed salamander (Plethodon cinereus) persist in an acidified landscape?
Bondi, Cheryl A; Beier, Colin M.; Ducey, Peter K; Lawrence, Gregory B.; Bailey, Scott W.
2016-01-01
Hardwood forests of eastern North America have experienced decades of acidic deposition, leading to soil acidification where base cation supply was insufficient to neutralize acid inputs. Negative impacts of soil acidity on amphibians include disrupted embryonic development, lower growth rates, and habitat loss. However, some amphibians exhibit intraspecific variation in acid tolerance, suggesting the potential for local adaptation in areas where soils are naturally acidic. The eastern red-backed salamander (Plethodon cinereus) is a highly abundant top predator of the northern hardwood forest floor. Early research found that P. cinereus was sensitive to acidic soils, avoiding substrates with pH health (body size and condition), and microhabitat selection, based on surveys of 34 hardwood forests in northeastern United States that encompass a regional soil pH gradient. We found no associations between soil pH and P. cinereus abundance or health, and observed that this salamander used substrates with pH similar to that available, suggesting that pH does not mediate their fine-scale distributions. The strongest negative predictor of P. cinereus abundance was the presence of dusky salamanders (Desmognathus spp.), which were most abundant in the western Adirondacks. Our results indicate that P. cinereus occupies a wider range of soil pH than has been previously thought, which has implications for their functional role in forest food webs and nutrient cycles in acid-impaired ecosystems. Tolerance of P. cinereus for more acidic habitats, including anthropogenically acidified forests, may be due to local adaptation in reproductively isolated populations and/or generalist life history traits that allow them to exploit a wider resource niche.
Bayesian methods for measures of agreement
Broemeling, Lyle D
2009-01-01
Using WinBUGS to implement Bayesian inferences of estimation and testing hypotheses, Bayesian Methods for Measures of Agreement presents useful methods for the design and analysis of agreement studies. It focuses on agreement among the various players in the diagnostic process.The author employs a Bayesian approach to provide statistical inferences based on various models of intra- and interrater agreement. He presents many examples that illustrate the Bayesian mode of reasoning and explains elements of a Bayesian application, including prior information, experimental information, the likelihood function, posterior distribution, and predictive distribution. The appendices provide the necessary theoretical foundation to understand Bayesian methods as well as introduce the fundamentals of programming and executing the WinBUGS software.Taking a Bayesian approach to inference, this hands-on book explores numerous measures of agreement, including the Kappa coefficient, the G coefficient, and intraclass correlation...
Plug & Play object oriented Bayesian networks
DEFF Research Database (Denmark)
Bangsø, Olav; Flores, J.; Jensen, Finn Verner
2003-01-01
Object oriented Bayesian networks have proven themselves useful in recent years. The idea of applying an object oriented approach to Bayesian networks has extended their scope to larger domains that can be divided into autonomous but interrelated entities. Object oriented Bayesian networks have...... been shown to be quite suitable for dynamic domains as well. However, processing object oriented Bayesian networks in practice does not take advantage of their modular structure. Normally the object oriented Bayesian network is transformed into a Bayesian network and, inference is performed...... by constructing a junction tree from this network. In this paper we propose a method for translating directly from object oriented Bayesian networks to junction trees, avoiding the intermediate translation. We pursue two main purposes: firstly, to maintain the original structure organized in an instance tree...
Kenison, Erin K; Litt, Andrea R.; Pilliod, David; McMahon, Tom E
2016-01-01
Predation by nonnative fishes has reduced abundance and increased extinction risk for amphibian populations worldwide. Although rare, fish and palatable amphibians have been observed to coexist where aquatic vegetation and structural complexity provide suitable refugia. We examined whether larval long-toed salamanders (Ambystoma macrodactylum Baird, 1849) increased use of vegetation cover in lakes with trout and whether adding vegetation structure could reduce predation risk and nonconsumptive effects (NCEs), such as reductions in body size and delayed metamorphosis. We compared use of vegetation cover by larval salamanders in lakes with and without trout and conducted a field experiment to investigate the influence of added vegetation structure on salamander body morphology and life history. The probability of catching salamanders in traps in lakes with trout was positively correlated with the proportion of submerged vegetation and surface cover. Growth rates of salamanders in enclosures with trout cues decreased as much as 85% and the probability of metamorphosis decreased by 56%. We did not find evidence that adding vegetation reduced NCEs in experimental enclosures, but salamanders in lakes with trout utilized more highly-vegetated areas which suggests that adding vegetation structure at the scale of the whole lake may facilitate coexistence between salamanders and introduced trout.
Flexible Bayesian Nonparametric Priors and Bayesian Computational Methods
Zhu, Weixuan
2016-01-01
The definition of vectors of dependent random probability measures is a topic of interest in Bayesian nonparametrics. They represent dependent nonparametric prior distributions that are useful for modelling observables for which specific covariate values are known. Our first contribution is the introduction of novel multivariate vectors of two-parameter Poisson-Dirichlet process. The dependence is induced by applying a L´evy copula to the marginal L´evy intensities. Our attenti...
Bayesian versus 'plain-vanilla Bayesian' multitarget statistics
Mahler, Ronald P. S.
2004-08-01
Finite-set statistics (FISST) is a direct generalization of single-sensor, single-target Bayes statistics to the multisensor-multitarget realm, based on random set theory. Various aspects of FISST are being investigated by several research teams around the world. In recent years, however, a few partisans have claimed that a "plain-vanilla Bayesian approach" suffices as down-to-earth, "straightforward," and general "first principles" for multitarget problems. Therefore, FISST is mere mathematical "obfuscation." In this and a companion paper I demonstrate the speciousness of these claims. In this paper I summarize general Bayes statistics, what is required to use it in multisensor-multitarget problems, and why FISST is necessary to make it practical. Then I demonstrate that the "plain-vanilla Bayesian approach" is so heedlessly formulated that it is erroneous, not even Bayesian denigrates FISST concepts while unwittingly assuming them, and has resulted in a succession of algorithms afflicted by inherent -- but less than candidly acknowledged -- computational "logjams."
Bayesian inference on proportional elections.
Brunello, Gabriel Hideki Vatanabe; Nakano, Eduardo Yoshio
2015-01-01
Polls for majoritarian voting systems usually show estimates of the percentage of votes for each candidate. However, proportional vote systems do not necessarily guarantee the candidate with the most percentage of votes will be elected. Thus, traditional methods used in majoritarian elections cannot be applied on proportional elections. In this context, the purpose of this paper was to perform a Bayesian inference on proportional elections considering the Brazilian system of seats distribution. More specifically, a methodology to answer the probability that a given party will have representation on the chamber of deputies was developed. Inferences were made on a Bayesian scenario using the Monte Carlo simulation technique, and the developed methodology was applied on data from the Brazilian elections for Members of the Legislative Assembly and Federal Chamber of Deputies in 2010. A performance rate was also presented to evaluate the efficiency of the methodology. Calculations and simulations were carried out using the free R statistical software. PMID:25786259
Bayesian approach to rough set
Marwala, Tshilidzi
2007-01-01
This paper proposes an approach to training rough set models using Bayesian framework trained using Markov Chain Monte Carlo (MCMC) method. The prior probabilities are constructed from the prior knowledge that good rough set models have fewer rules. Markov Chain Monte Carlo sampling is conducted through sampling in the rough set granule space and Metropolis algorithm is used as an acceptance criteria. The proposed method is tested to estimate the risk of HIV given demographic data. The results obtained shows that the proposed approach is able to achieve an average accuracy of 58% with the accuracy varying up to 66%. In addition the Bayesian rough set give the probabilities of the estimated HIV status as well as the linguistic rules describing how the demographic parameters drive the risk of HIV.
Bayesian priors for transiting planets
Kipping, David M
2016-01-01
As astronomers push towards discovering ever-smaller transiting planets, it is increasingly common to deal with low signal-to-noise ratio (SNR) events, where the choice of priors plays an influential role in Bayesian inference. In the analysis of exoplanet data, the selection of priors is often treated as a nuisance, with observers typically defaulting to uninformative distributions. Such treatments miss a key strength of the Bayesian framework, especially in the low SNR regime, where even weak a priori information is valuable. When estimating the parameters of a low-SNR transit, two key pieces of information are known: (i) the planet has the correct geometric alignment to transit and (ii) the transit event exhibits sufficient signal-to-noise to have been detected. These represent two forms of observational bias. Accordingly, when fitting transits, the model parameter priors should not follow the intrinsic distributions of said terms, but rather those of both the intrinsic distributions and the observational ...
Bayesian Source Separation and Localization
Knuth, K H
1998-01-01
The problem of mixed signals occurs in many different contexts; one of the most familiar being acoustics. The forward problem in acoustics consists of finding the sound pressure levels at various detectors resulting from sound signals emanating from the active acoustic sources. The inverse problem consists of using the sound recorded by the detectors to separate the signals and recover the original source waveforms. In general, the inverse problem is unsolvable without additional information. This general problem is called source separation, and several techniques have been developed that utilize maximum entropy, minimum mutual information, and maximum likelihood. In previous work, it has been demonstrated that these techniques can be recast in a Bayesian framework. This paper demonstrates the power of the Bayesian approach, which provides a natural means for incorporating prior information into a source model. An algorithm is developed that utilizes information regarding both the statistics of the amplitudes...
Bayesian Inference for Radio Observations
Lochner, Michelle; Zwart, Jonathan T L; Smirnov, Oleg; Bassett, Bruce A; Oozeer, Nadeem; Kunz, Martin
2015-01-01
(Abridged) New telescopes like the Square Kilometre Array (SKA) will push into a new sensitivity regime and expose systematics, such as direction-dependent effects, that could previously be ignored. Current methods for handling such systematics rely on alternating best estimates of instrumental calibration and models of the underlying sky, which can lead to inaccurate uncertainty estimates and biased results because such methods ignore any correlations between parameters. These deconvolution algorithms produce a single image that is assumed to be a true representation of the sky, when in fact it is just one realisation of an infinite ensemble of images compatible with the noise in the data. In contrast, here we report a Bayesian formalism that simultaneously infers both systematics and science. Our technique, Bayesian Inference for Radio Observations (BIRO), determines all parameters directly from the raw data, bypassing image-making entirely, by sampling from the joint posterior probability distribution. Thi...
Directory of Open Access Journals (Sweden)
Jason Munshi-South
2013-04-01
Full Text Available Urbanization is a major cause of amphibian decline. Stream-dwelling plethodontid salamanders are particularly susceptible to urbanization due to declining water quality and hydrological changes, but few studies have examined these taxa in cities. The northern dusky salamander (Desmognathus fuscus was once common in the New York City metropolitan area, but has substantially declined throughout the region in recent decades. We used five tetranucleotide microsatellite loci to examine population differentiation, genetic variation, and bottlenecks among five remnant urban populations of dusky salamanders in NYC. These genetic measures provide information on isolation, prevalence of inbreeding, long-term prospects for population persistence, and potential for evolutionary responses to future environmental change. All populations were genetically differentiated from each other, and the most isolated populations in Manhattan have maintained very little genetic variation (i.e. <20% heterozygosity. A majority of the populations also exhibited evidence of genetic bottlenecks. These findings contrast with published estimates of high genetic variation within and lack of structure between populations of other desmognathine salamanders sampled over similar or larger spatial scales. Declines in genetic variation likely resulted from population extirpations and the degradation of stream and terrestrial paths for dispersal in NYC. Loss of genetic variability in populations isolated by human development may be an underappreciated cause and/or consequence of the decline of this species in urbanized areas of the northeast USA.
Arntzen, J.W.; Beukema, W.; Galis, F.; Ivanović, A.
2015-01-01
In vertebrates, the relative proportion of the number of trunk and caudal vertebrae is an important determinant of body shape. While among amphibians frogs and toads show low variation in vertebrae numbers, in salamanders the numbers of trunk and caudal vertebrae vary widely, giving rise to phenotyp
Non-additive response of larval ringed salamanders to intraspecific density.
Ousterhout, Brittany H; Semlitsch, Raymond D
2016-04-01
Conditions experienced in early developmental stages can have long-term consequences for individual fitness. High intraspecific density during the natal period can affect juvenile and eventually adult growth rates, metabolism, immune function, survival, and fecundity. Despite the important ecological and evolutionary effects of early developmental density, the form of the relationship between natal density and resulting juvenile phenotype is poorly understood. To test competing hypotheses explaining responses to intraspecific density, we experimentally manipulated the initial larval density of ringed salamanders (Ambystoma annulatum), a pond-breeding amphibian, over 11 densities. We modeled the functional form of the relationship between natal density and juvenile traits, and compared the relative support for the various hypotheses based on their goodness of fit. These functional form models were then used to parameterize a simple simulation model of population growth. Our data support non-additive density dependence and presents an alternate hypothesis to additive density dependence, self-thinning and Allee effects in larval amphibians. We posit that ringed salamander larvae may be under selective pressure for tolerance to high density and increased efficiency in resource utilization. Additionally, we demonstrate that models of population dynamics are sensitive to assumptions of the functional form of density dependence. PMID:26683834
Blooi, M; Pasmans, F; Rouffaer, L; Haesebrouck, F; Vercammen, F; Martel, A
2015-06-30
Chytridiomycosis caused by the chytrid fungus Batrachochytrium salamandrivorans (Bsal) poses a serious threat to urodelan diversity worldwide. Antimycotic treatment of this disease using protocols developed for the related fungus Batrachochytrium dendrobatidis (Bd), results in therapeutic failure. Here, we reveal that this therapeutic failure is partly due to different minimum inhibitory concentrations (MICs) of antimycotics against Bsal and Bd. In vitro growth inhibition of Bsal occurs after exposure to voriconazole, polymyxin E, itraconazole and terbinafine but not to florfenicol. Synergistic effects between polymyxin E and voriconazole or itraconazole significantly decreased the combined MICs necessary to inhibit Bsal growth. Topical treatment of infected fire salamanders (Salamandra salamandra), with voriconazole or itraconazole alone (12.5 μg/ml and 0.6 μg/ml respectively) or in combination with polymyxin E (2000 IU/ml) at an ambient temperature of 15 °C during 10 days decreased fungal loads but did not clear Bsal infections. However, topical treatment of Bsal infected animals with a combination of polymyxin E (2000 IU/ml) and voriconazole (12.5 μg/ml) at an ambient temperature of 20 °C resulted in clearance of Bsal infections. This treatment protocol was validated in 12 fire salamanders infected with Bsal during a field outbreak and resulted in clearance of infection in all animals.
Memory of conspecifics in male salamanders Plethodon cinereus: Implications for territorial defense
Institute of Scientific and Technical Information of China (English)
Nancy R.KOHN; Jennifer M.DEITLOFF; Schuyler F.DARTEZ; Michelle M.WILCOX; Robert G.JAEGER
2013-01-01
We investigated how exposure duration (time that two individuals initially interact) and separation interval (time between the initial interaction and a subsequent interaction) affect recognition memory of conspecifics in male red-backed salamanders Plethodon cinereus.Previous studies have demonstrated that this species aggressively defends territories.We recorded aggressive behavior to assess recognition memory,because aggression is more intense toward previously unencountered individuals compared to previously encountered individuals in this species.We found that with 15-min exposures and 5-day separation intervals,focal males did not spend significantly more time threatening ‘unfamiliar' intruders than ‘familiar' intruders.After either 8-hour exposures and 5-day separation intervals and 5-day exposures and 5-day separation intervals,focal males spent significantly more time threatening unfamiliar intruders than familiar intruders.These results suggest that male red-backed salamanders can remember familiar conspecifics (e.g.,territorial neighbors) after at least an 8-hour exposure duration and that memory persists at least as long as 5 days.After 5-day exposure and 15-day separation intervals,we found no significant difference in aggressive behavior toward familiar and unfamiliar intruders.Long separation intervals (15 days) may lead either to loss of memory of previously familiar individuals or,alternatively,aggressive reassessment of individuals as only a change in behavior indicates positively that memory has occurred.Thus,variance in territorial defense within an individual may depend on its ability to recognize conspecific males.
Directory of Open Access Journals (Sweden)
Nathan F Bendik
Full Text Available Despite recognition that nearly one-third of the 6300 amphibian species are threatened with extinction, our understanding of the general ecology and population status of many amphibians is relatively poor. A widely-used method for monitoring amphibians involves injecting captured individuals with unique combinations of colored visible implant elastomer (VIE. We compared VIE identification to a less-invasive method - computer-assisted photographic identification (photoID - in endangered Jollyville Plateau salamanders (Eurycea tonkawae, a species with a known range limited to eight stream drainages in central Texas. We based photoID on the unique pigmentation patterns on the dorsal head region of 1215 individual salamanders using identification software Wild-ID. We compared the performance of photoID methods to VIEs using both 'high-quality' and 'low-quality' images, which were taken using two different camera types and technologies. For high-quality images, the photoID method had a false rejection rate of 0.76% compared to 1.90% for VIEs. Using a comparable dataset of lower-quality images, the false rejection rate was much higher (15.9%. Photo matching scores were negatively correlated with time between captures, suggesting that evolving natural marks could increase misidentification rates in longer term capture-recapture studies. Our study demonstrates the utility of large-scale capture-recapture using photo identification methods for Eurycea and other species with stable natural marks that can be reliably photographed.
Harshbarger, J C; Chang, S C; DeLanney, L E; Rose, F L; Green, D E
1999-01-01
Spontaneous mastocytomas studied in 18 axolotls (Ambystoma mexicanum) and six tiger salamanders (Ambystoma tigrinum) were gray-white, uni- to multilobular cutaneous protrusions from 2 mm to 2 cm in diameter. Tumors were moderately cellular unencapsulated masses that usually infiltrated the dermis and hypodermis with the destruction of intervening tissues. Some tumors were invading superficial bundles of the underlying skeletal muscle. Tumors consisted of mitotically active cells derived from a single lineage but showing a range of differentiation. Immature cells had nearly smooth to lightly cleft or folded basophilic nuclei bordered by a band of cytoplasm with few cytoplasmic processes and containing a few small uniform eccentric granules. Mature cells had basophilic nuclei with deep clefts or folds and abundant eosinophilic cytoplasm with multiple long intertwining cytoplasmic extensions packed with metachromatic granules. The axolotls were old individuals from an inbred laboratory colony. The tiger salamanders were wild animals from a single polluted pond. They could have been old and inbred. Both groups were neotenic. These are the first mastocytomas discovered in cold-blooded animals.
Harshbarger, J.C.; Chang, S.C.; DeLanney, L.E.; Rose, F.L.; Green, D.E.
1999-01-01
Spontaneous mastocytomas studied in 18 axolotls (Ambystoma mexicanum) and six tiger salamanders (Ambystoma tigrinum) were gray-white, uni- to multilobular cutaneous protrusions from 2mm to 2cm in diameter. Tumors were moderately cellular unencapsulated masses that usually infiltrated the dermis and hypodermis with the destruction of intervening tissues. Some tumors were invading superficial bundles of the underlying skeletal muscle. Tumors consisted of mitotically active cells derived from a single lineage but showing a range of differentiation. Immature cells had nearly smooth to lightly cleft or folded basophilic nuclei bordered by a band of cytoplasm with few cytoplasmic processes and containing a few small uniform eccentric granules. Mature cells had basophilic nuclei with deep clefts or folds and abundant eosinophilic cytoplasm with multiple long intertwining cytoplasmic extensions packed with metachromatic granules. The axolotls were old individuals from an inbred laboratory colony. The tiger salamanders were wild animals from a single polluted pond. They could have been old and inbred. Both groups were neotenic. These are the first mastocytomas discovered in cold-blooded animals.
Townsend, Jason M; Driscoll, Charles T; Rimmer, Christopher C; McFarland, Kent P
2014-01-01
High-elevation ecosystems of the northeastern United States are vulnerable to deposition and environmental accumulation of atmospheric pollutants, yet little work has been done to assess mercury (Hg) concentrations in organisms occupying montane ecosystems. The authors present data on Hg concentrations in ground-foraging insectivorous songbirds, a terrestrial salamander, and forest floor horizons sampled along a forested elevational gradient from 185 m to 1273 m in the Catskill Mountains, New York, USA. Mean Hg concentrations in Catharus thrushes and the salamander Plethodon cinereus increased with elevation, as did Hg concentrations in all forest floor horizons. Mean Hg concentrations in organic soils at approximately 1200 m elevation (503.5 ± 17.7 ng/g, dry wt) were 4.4-fold greater than those at approximately 200 m. Montane ecosystems of the northeastern United States, and probably elsewhere, are exposed to higher levels of atmospheric Hg deposition as reflected in accumulation patterns in the forest floor and associated high-elevation fauna. This information can be used to parameterize and test Hg transport and bioaccumulation models of landscape-specific patterns and may serve as a monitoring tool for decision makers considering future controls on Hg emissions. Further investigation is needed into the potential effects of increased Hg concentrations on high-elevation fauna.
A Bayesian Nonparametric IRT Model
Karabatsos, George
2015-01-01
This paper introduces a flexible Bayesian nonparametric Item Response Theory (IRT) model, which applies to dichotomous or polytomous item responses, and which can apply to either unidimensional or multidimensional scaling. This is an infinite-mixture IRT model, with person ability and item difficulty parameters, and with a random intercept parameter that is assigned a mixing distribution, with mixing weights a probit function of other person and item parameters. As a result of its flexibility...
Elements of Bayesian experimental design
Energy Technology Data Exchange (ETDEWEB)
Sivia, D.S. [Rutherford Appleton Lab., Oxon (United Kingdom)
1997-09-01
We consider some elements of the Bayesian approach that are important for optimal experimental design. While the underlying principles used are very general, and are explained in detail in a recent tutorial text, they are applied here to the specific case of characterising the inferential value of different resolution peakshapes. This particular issue was considered earlier by Silver, Sivia and Pynn (1989, 1990a, 1990b), and the following presentation confirms and extends the conclusions of their analysis.
Bayesian kinematic earthquake source models
Minson, S. E.; Simons, M.; Beck, J. L.; Genrich, J. F.; Galetzka, J. E.; Chowdhury, F.; Owen, S. E.; Webb, F.; Comte, D.; Glass, B.; Leiva, C.; Ortega, F. H.
2009-12-01
Most coseismic, postseismic, and interseismic slip models are based on highly regularized optimizations which yield one solution which satisfies the data given a particular set of regularizing constraints. This regularization hampers our ability to answer basic questions such as whether seismic and aseismic slip overlap or instead rupture separate portions of the fault zone. We present a Bayesian methodology for generating kinematic earthquake source models with a focus on large subduction zone earthquakes. Unlike classical optimization approaches, Bayesian techniques sample the ensemble of all acceptable models presented as an a posteriori probability density function (PDF), and thus we can explore the entire solution space to determine, for example, which model parameters are well determined and which are not, or what is the likelihood that two slip distributions overlap in space. Bayesian sampling also has the advantage that all a priori knowledge of the source process can be used to mold the a posteriori ensemble of models. Although very powerful, Bayesian methods have up to now been of limited use in geophysical modeling because they are only computationally feasible for problems with a small number of free parameters due to what is called the "curse of dimensionality." However, our methodology can successfully sample solution spaces of many hundreds of parameters, which is sufficient to produce finite fault kinematic earthquake models. Our algorithm is a modification of the tempered Markov chain Monte Carlo (tempered MCMC or TMCMC) method. In our algorithm, we sample a "tempered" a posteriori PDF using many MCMC simulations running in parallel and evolutionary computation in which models which fit the data poorly are preferentially eliminated in favor of models which better predict the data. We present results for both synthetic test problems as well as for the 2007 Mw 7.8 Tocopilla, Chile earthquake, the latter of which is constrained by InSAR, local high
Bayesian Stable Isotope Mixing Models
Parnell, Andrew C.; Phillips, Donald L.; Bearhop, Stuart; Semmens, Brice X.; Ward, Eric J.; Moore, Jonathan W.; Andrew L Jackson; Inger, Richard
2012-01-01
In this paper we review recent advances in Stable Isotope Mixing Models (SIMMs) and place them into an over-arching Bayesian statistical framework which allows for several useful extensions. SIMMs are used to quantify the proportional contributions of various sources to a mixture. The most widely used application is quantifying the diet of organisms based on the food sources they have been observed to consume. At the centre of the multivariate statistical model we propose is a compositional m...
Bayesian Network--Response Regression
WANG, LU; Durante, Daniele; Dunson, David B.
2016-01-01
There is an increasing interest in learning how human brain networks vary with continuous traits (e.g., personality, cognitive abilities, neurological disorders), but flexible procedures to accomplish this goal are limited. We develop a Bayesian semiparametric model, which combines low-rank factorizations and Gaussian process priors to allow flexible shifts of the conditional expectation for a network-valued random variable across the feature space, while including subject-specific random eff...
Bayesian segmentation of hyperspectral images
Mohammadpour, Adel; Mohammad-Djafari, Ali
2007-01-01
In this paper we consider the problem of joint segmentation of hyperspectral images in the Bayesian framework. The proposed approach is based on a Hidden Markov Modeling (HMM) of the images with common segmentation, or equivalently with common hidden classification label variables which is modeled by a Potts Markov Random Field. We introduce an appropriate Markov Chain Monte Carlo (MCMC) algorithm to implement the method and show some simulation results.
Bayesian segmentation of hyperspectral images
Mohammadpour, Adel; Féron, Olivier; Mohammad-Djafari, Ali
2004-11-01
In this paper we consider the problem of joint segmentation of hyperspectral images in the Bayesian framework. The proposed approach is based on a Hidden Markov Modeling (HMM) of the images with common segmentation, or equivalently with common hidden classification label variables which is modeled by a Potts Markov Random Field. We introduce an appropriate Markov Chain Monte Carlo (MCMC) algorithm to implement the method and show some simulation results.
Bayesian analysis of contingency tables
Gómez Villegas, Miguel A.; González Pérez, Beatriz
2005-01-01
The display of the data by means of contingency tables is used in different approaches to statistical inference, for example, to broach the test of homogeneity of independent multinomial distributions. We develop a Bayesian procedure to test simple null hypotheses versus bilateral alternatives in contingency tables. Given independent samples of two binomial distributions and taking a mixed prior distribution, we calculate the posterior probability that the proportion of successes in the first...
Bayesian estimation of turbulent motion
Héas, P.; Herzet, C.; Mémin, E.; Heitz, D.; P. D. Mininni
2013-01-01
International audience Based on physical laws describing the multi-scale structure of turbulent flows, this article proposes a regularizer for fluid motion estimation from an image sequence. Regularization is achieved by imposing some scale invariance property between histograms of motion increments computed at different scales. By reformulating this problem from a Bayesian perspective, an algorithm is proposed to jointly estimate motion, regularization hyper-parameters, and to select the ...
Bayesian Kernel Mixtures for Counts
Canale, Antonio; David B Dunson
2011-01-01
Although Bayesian nonparametric mixture models for continuous data are well developed, there is a limited literature on related approaches for count data. A common strategy is to use a mixture of Poissons, which unfortunately is quite restrictive in not accounting for distributions having variance less than the mean. Other approaches include mixing multinomials, which requires finite support, and using a Dirichlet process prior with a Poisson base measure, which does not allow smooth deviatio...
Bayesian network as a modelling tool for risk management in agriculture
DEFF Research Database (Denmark)
Rasmussen, Svend; Madsen, Anders L.; Lund, Mogens
The importance of risk management increases as farmers become more exposed to risk. But risk management is a difficult topic because income risk is the result of the complex interaction of multiple risk factors combined with the effect of an increasing array of possible risk management tools....... In this paper we use Bayesian networks as an integrated modelling approach for representing uncertainty and analysing risk management in agriculture. It is shown how historical farm account data may be efficiently used to estimate conditional probabilities, which are the core elements in Bayesian network models....... We further show how the Bayesian network model RiBay is used for stochastic simulation of farm income, and we demonstrate how RiBay can be used to simulate risk management at the farm level. It is concluded that the key strength of a Bayesian network is the transparency of assumptions...
Bayesian second law of thermodynamics.
Bartolotta, Anthony; Carroll, Sean M; Leichenauer, Stefan; Pollack, Jason
2016-08-01
We derive a generalization of the second law of thermodynamics that uses Bayesian updates to explicitly incorporate the effects of a measurement of a system at some point in its evolution. By allowing an experimenter's knowledge to be updated by the measurement process, this formulation resolves a tension between the fact that the entropy of a statistical system can sometimes fluctuate downward and the information-theoretic idea that knowledge of a stochastically evolving system degrades over time. The Bayesian second law can be written as ΔH(ρ_{m},ρ)+〈Q〉_{F|m}≥0, where ΔH(ρ_{m},ρ) is the change in the cross entropy between the original phase-space probability distribution ρ and the measurement-updated distribution ρ_{m} and 〈Q〉_{F|m} is the expectation value of a generalized heat flow out of the system. We also derive refined versions of the second law that bound the entropy increase from below by a non-negative number, as well as Bayesian versions of integral fluctuation theorems. We demonstrate the formalism using simple analytical and numerical examples. PMID:27627241
Bayesian second law of thermodynamics
Bartolotta, Anthony; Carroll, Sean M.; Leichenauer, Stefan; Pollack, Jason
2016-08-01
We derive a generalization of the second law of thermodynamics that uses Bayesian updates to explicitly incorporate the effects of a measurement of a system at some point in its evolution. By allowing an experimenter's knowledge to be updated by the measurement process, this formulation resolves a tension between the fact that the entropy of a statistical system can sometimes fluctuate downward and the information-theoretic idea that knowledge of a stochastically evolving system degrades over time. The Bayesian second law can be written as Δ H (ρm,ρ ) + F |m≥0 , where Δ H (ρm,ρ ) is the change in the cross entropy between the original phase-space probability distribution ρ and the measurement-updated distribution ρm and F |m is the expectation value of a generalized heat flow out of the system. We also derive refined versions of the second law that bound the entropy increase from below by a non-negative number, as well as Bayesian versions of integral fluctuation theorems. We demonstrate the formalism using simple analytical and numerical examples.
Embracing Uncertainty: The Interface of Bayesian Statistics and Cognitive Psychology
Directory of Open Access Journals (Sweden)
Judith L. Anderson
1998-06-01
Full Text Available Ecologists working in conservation and resource management are discovering the importance of using Bayesian analytic methods to deal explicitly with uncertainty in data analyses and decision making. However, Bayesian procedures require, as inputs and outputs, an idea that is problematic for the human brain: the probability of a hypothesis ("single-event probability". I describe several cognitive concepts closely related to single-event probabilities, and discuss how their interchangeability in the human mind results in "cognitive illusions," apparent deficits in reasoning about uncertainty. Each cognitive illusion implies specific possible pitfalls for the use of single-event probabilities in ecology and resource management. I then discuss recent research in cognitive psychology showing that simple tactics of communication, suggested by an evolutionary perspective on human cognition, help people to process uncertain information more effectively as they read and talk about probabilities. In addition, I suggest that carefully considered standards for methodology and conventions for presentation may also make Bayesian analyses easier to understand.
12th Brazilian Meeting on Bayesian Statistics
Louzada, Francisco; Rifo, Laura; Stern, Julio; Lauretto, Marcelo
2015-01-01
Through refereed papers, this volume focuses on the foundations of the Bayesian paradigm; their comparison to objectivistic or frequentist Statistics counterparts; and the appropriate application of Bayesian foundations. This research in Bayesian Statistics is applicable to data analysis in biostatistics, clinical trials, law, engineering, and the social sciences. EBEB, the Brazilian Meeting on Bayesian Statistics, is held every two years by the ISBrA, the International Society for Bayesian Analysis, one of the most active chapters of the ISBA. The 12th meeting took place March 10-14, 2014 in Atibaia. Interest in foundations of inductive Statistics has grown recently in accordance with the increasing availability of Bayesian methodological alternatives. Scientists need to deal with the ever more difficult choice of the optimal method to apply to their problem. This volume shows how Bayes can be the answer. The examination and discussion on the foundations work towards the goal of proper application of Bayesia...
Compiling Relational Bayesian Networks for Exact Inference
DEFF Research Database (Denmark)
Jaeger, Manfred; Chavira, Mark; Darwiche, Adnan
2004-01-01
We describe a system for exact inference with relational Bayesian networks as defined in the publicly available \\primula\\ tool. The system is based on compiling propositional instances of relational Bayesian networks into arithmetic circuits and then performing online inference by evaluating...... and differentiating these circuits in time linear in their size. We report on experimental results showing the successful compilation, and efficient inference, on relational Bayesian networks whose {\\primula}--generated propositional instances have thousands of variables, and whose jointrees have clusters...
Bayesian Posterior Distributions Without Markov Chains
Cole, Stephen R.; Chu, Haitao; Greenland, Sander; Hamra, Ghassan; Richardson, David B.
2012-01-01
Bayesian posterior parameter distributions are often simulated using Markov chain Monte Carlo (MCMC) methods. However, MCMC methods are not always necessary and do not help the uninitiated understand Bayesian inference. As a bridge to understanding Bayesian inference, the authors illustrate a transparent rejection sampling method. In example 1, they illustrate rejection sampling using 36 cases and 198 controls from a case-control study (1976–1983) assessing the relation between residential ex...
Iskandar, Ismed; Satria Gondokaryono, Yudi
2016-02-01
In reliability theory, the most important problem is to determine the reliability of a complex system from the reliability of its components. The weakness of most reliability theories is that the systems are described and explained as simply functioning or failed. In many real situations, the failures may be from many causes depending upon the age and the environment of the system and its components. Another problem in reliability theory is one of estimating the parameters of the assumed failure models. The estimation may be based on data collected over censored or uncensored life tests. In many reliability problems, the failure data are simply quantitatively inadequate, especially in engineering design and maintenance system. The Bayesian analyses are more beneficial than the classical one in such cases. The Bayesian estimation analyses allow us to combine past knowledge or experience in the form of an apriori distribution with life test data to make inferences of the parameter of interest. In this paper, we have investigated the application of the Bayesian estimation analyses to competing risk systems. The cases are limited to the models with independent causes of failure by using the Weibull distribution as our model. A simulation is conducted for this distribution with the objectives of verifying the models and the estimators and investigating the performance of the estimators for varying sample size. The simulation data are analyzed by using Bayesian and the maximum likelihood analyses. The simulation results show that the change of the true of parameter relatively to another will change the value of standard deviation in an opposite direction. For a perfect information on the prior distribution, the estimation methods of the Bayesian analyses are better than those of the maximum likelihood. The sensitivity analyses show some amount of sensitivity over the shifts of the prior locations. They also show the robustness of the Bayesian analysis within the range
Variational bayesian method of estimating variance components.
Arakawa, Aisaku; Taniguchi, Masaaki; Hayashi, Takeshi; Mikawa, Satoshi
2016-07-01
We developed a Bayesian analysis approach by using a variational inference method, a so-called variational Bayesian method, to determine the posterior distributions of variance components. This variational Bayesian method and an alternative Bayesian method using Gibbs sampling were compared in estimating genetic and residual variance components from both simulated data and publically available real pig data. In the simulated data set, we observed strong bias toward overestimation of genetic variance for the variational Bayesian method in the case of low heritability and low population size, and less bias was detected with larger population sizes in both methods examined. The differences in the estimates of variance components between the variational Bayesian and the Gibbs sampling were not found in the real pig data. However, the posterior distributions of the variance components obtained with the variational Bayesian method had shorter tails than those obtained with the Gibbs sampling. Consequently, the posterior standard deviations of the genetic and residual variances of the variational Bayesian method were lower than those of the method using Gibbs sampling. The computing time required was much shorter with the variational Bayesian method than with the method using Gibbs sampling.
SYNTHESIZED EXPECTED BAYESIAN METHOD OF PARAMETRIC ESTIMATE
Institute of Scientific and Technical Information of China (English)
Ming HAN; Yuanyao DING
2004-01-01
This paper develops a new method of parametric estimate, which is named as "synthesized expected Bayesian method". When samples of products are tested and no failure events occur, thedefinition of expected Bayesian estimate is introduced and the estimates of failure probability and failure rate are provided. After some failure information is introduced by making an extra-test, a synthesized expected Bayesian method is defined and used to estimate failure probability, failure rateand some other parameters in exponential distribution and Weibull distribution of populations. Finally,calculations are performed according to practical problems, which show that the synthesized expected Bayesian method is feasible and easy to operate.
Xu, Chengcheng; Wang, Wei; Liu, Pan; Li, Zhibin
2015-12-01
This study aimed to develop a real-time crash risk model with limited data in China by using Bayesian meta-analysis and Bayesian inference approach. A systematic review was first conducted by using three different Bayesian meta-analyses, including the fixed effect meta-analysis, the random effect meta-analysis, and the meta-regression. The meta-analyses provided a numerical summary of the effects of traffic variables on crash risks by quantitatively synthesizing results from previous studies. The random effect meta-analysis and the meta-regression produced a more conservative estimate for the effects of traffic variables compared with the fixed effect meta-analysis. Then, the meta-analyses results were used as informative priors for developing crash risk models with limited data. Three different meta-analyses significantly affect model fit and prediction accuracy. The model based on meta-regression can increase the prediction accuracy by about 15% as compared to the model that was directly developed with limited data. Finally, the Bayesian predictive densities analysis was used to identify the outliers in the limited data. It can further improve the prediction accuracy by 5.0%.
Jessica Wooten; Leslie Rissler
2011-01-01
The discovery and subsequent description of cryptic biodiversity is often challenging, especially for groups that have undergone rapid lineage accumulation in the relatively recent past. Even without formal descriptions, understanding genetic diversity patterns as they relate to underlying ecological or historical processes can be important for conservation. The dusky salamanders of the genus Desmognathus, with 20 described species, comprise the second largest genus of plethodontid salamander...
Directory of Open Access Journals (Sweden)
Ildikó Ungvári
Full Text Available Genetic studies indicate high number of potential factors related to asthma. Based on earlier linkage analyses we selected the 11q13 and 14q22 asthma susceptibility regions, for which we designed a partial genome screening study using 145 SNPs in 1201 individuals (436 asthmatic children and 765 controls. The results were evaluated with traditional frequentist methods and we applied a new statistical method, called bayesian network based bayesian multilevel analysis of relevance (BN-BMLA. This method uses bayesian network representation to provide detailed characterization of the relevance of factors, such as joint significance, the type of dependency, and multi-target aspects. We estimated posteriors for these relations within the bayesian statistical framework, in order to estimate the posteriors whether a variable is directly relevant or its association is only mediated.With frequentist methods one SNP (rs3751464 in the FRMD6 gene provided evidence for an association with asthma (OR = 1.43(1.2-1.8; p = 3×10(-4. The possible role of the FRMD6 gene in asthma was also confirmed in an animal model and human asthmatics.In the BN-BMLA analysis altogether 5 SNPs in 4 genes were found relevant in connection with asthma phenotype: PRPF19 on chromosome 11, and FRMD6, PTGER2 and PTGDR on chromosome 14. In a subsequent step a partial dataset containing rhinitis and further clinical parameters was used, which allowed the analysis of relevance of SNPs for asthma and multiple targets. These analyses suggested that SNPs in the AHNAK and MS4A2 genes were indirectly associated with asthma. This paper indicates that BN-BMLA explores the relevant factors more comprehensively than traditional statistical methods and extends the scope of strong relevance based methods to include partial relevance, global characterization of relevance and multi-target relevance.
Bayesian Methods and Universal Darwinism
Campbell, John
2009-12-01
Bayesian methods since the time of Laplace have been understood by their practitioners as closely aligned to the scientific method. Indeed a recent Champion of Bayesian methods, E. T. Jaynes, titled his textbook on the subject Probability Theory: the Logic of Science. Many philosophers of science including Karl Popper and Donald Campbell have interpreted the evolution of Science as a Darwinian process consisting of a `copy with selective retention' algorithm abstracted from Darwin's theory of Natural Selection. Arguments are presented for an isomorphism between Bayesian Methods and Darwinian processes. Universal Darwinism, as the term has been developed by Richard Dawkins, Daniel Dennett and Susan Blackmore, is the collection of scientific theories which explain the creation and evolution of their subject matter as due to the Operation of Darwinian processes. These subject matters span the fields of atomic physics, chemistry, biology and the social sciences. The principle of Maximum Entropy states that Systems will evolve to states of highest entropy subject to the constraints of scientific law. This principle may be inverted to provide illumination as to the nature of scientific law. Our best cosmological theories suggest the universe contained much less complexity during the period shortly after the Big Bang than it does at present. The scientific subject matter of atomic physics, chemistry, biology and the social sciences has been created since that time. An explanation is proposed for the existence of this subject matter as due to the evolution of constraints in the form of adaptations imposed on Maximum Entropy. It is argued these adaptations were discovered and instantiated through the Operations of a succession of Darwinian processes.
Directory of Open Access Journals (Sweden)
Valorie Titus
2014-12-01
Full Text Available Most amphibians use both wetland and upland habitats, but the extent of their movement in forested habitats is poorly known. We used radiotelemetry to observe the movements of adult and juvenile eastern tiger salamanders over a 4-year period. Females tended to move farther from the breeding ponds into upland forested habitat than males, while the distance a juvenile moved appeared to be related to body size, with the largest individuals moving as far as the adult females. Individuals chose refugia in native pitch pine—oak forested habitat and avoided open fields, roads, and developed areas. We also observed a difference in potential predation pressures in relation to the distance an individual moved from the edge of the pond. Our results support delineating forested wetland buffer zones on a case-by-case basis to reduce the impacts of concentrated predation, to increase and protect the availability of pitch pine—oak forests near the breeding pond, and to focus primarily on the habitat needs of the adult females and larger juveniles, which in turn will encompass habitat needs of adult males and smaller juveniles.
Numeracy, frequency, and Bayesian reasoning
Directory of Open Access Journals (Sweden)
Gretchen B. Chapman
2009-02-01
Full Text Available Previous research has demonstrated that Bayesian reasoning performance is improved if uncertainty information is presented as natural frequencies rather than single-event probabilities. A questionnaire study of 342 college students replicated this effect but also found that the performance-boosting benefits of the natural frequency presentation occurred primarily for participants who scored high in numeracy. This finding suggests that even comprehension and manipulation of natural frequencies requires a certain threshold of numeracy abilities, and that the beneficial effects of natural frequency presentation may not be as general as previously believed.
Bayesian Query-Focused Summarization
Daumé, Hal
2009-01-01
We present BayeSum (for ``Bayesian summarization''), a model for sentence extraction in query-focused summarization. BayeSum leverages the common case in which multiple documents are relevant to a single query. Using these documents as reinforcement for query terms, BayeSum is not afflicted by the paucity of information in short queries. We show that approximate inference in BayeSum is possible on large data sets and results in a state-of-the-art summarization system. Furthermore, we show how BayeSum can be understood as a justified query expansion technique in the language modeling for IR framework.
Bayesian Sampling using Condition Indicators
DEFF Research Database (Denmark)
Faber, Michael H.; Sørensen, John Dalsgaard
2002-01-01
The problem of control quality of components is considered for the special case where the acceptable failure rate is low, the test costs are high and where it may be difficult or impossible to test the condition of interest directly. Based on the classical control theory and the concept...... of condition indicators introduced by Benjamin and Cornell (1970) a Bayesian approach to quality control is formulated. The formulation is then extended to the case where the quality control is based on sampling of indirect information about the condition of the components, i.e. condition indicators...
parallelMCMCcombine: an R package for bayesian methods for big data and analytics.
Directory of Open Access Journals (Sweden)
Alexey Miroshnikov
Full Text Available Recent advances in big data and analytics research have provided a wealth of large data sets that are too big to be analyzed in their entirety, due to restrictions on computer memory or storage size. New Bayesian methods have been developed for data sets that are large only due to large sample sizes. These methods partition big data sets into subsets and perform independent Bayesian Markov chain Monte Carlo analyses on the subsets. The methods then combine the independent subset posterior samples to estimate a posterior density given the full data set. These approaches were shown to be effective for Bayesian models including logistic regression models, Gaussian mixture models and hierarchical models. Here, we introduce the R package parallelMCMCcombine which carries out four of these techniques for combining independent subset posterior samples. We illustrate each of the methods using a Bayesian logistic regression model for simulation data and a Bayesian Gamma model for real data; we also demonstrate features and capabilities of the R package. The package assumes the user has carried out the Bayesian analysis and has produced the independent subposterior samples outside of the package. The methods are primarily suited to models with unknown parameters of fixed dimension that exist in continuous parameter spaces. We envision this tool will allow researchers to explore the various methods for their specific applications and will assist future progress in this rapidly developing field.
parallelMCMCcombine: an R package for bayesian methods for big data and analytics.
Miroshnikov, Alexey; Conlon, Erin M
2014-01-01
Recent advances in big data and analytics research have provided a wealth of large data sets that are too big to be analyzed in their entirety, due to restrictions on computer memory or storage size. New Bayesian methods have been developed for data sets that are large only due to large sample sizes. These methods partition big data sets into subsets and perform independent Bayesian Markov chain Monte Carlo analyses on the subsets. The methods then combine the independent subset posterior samples to estimate a posterior density given the full data set. These approaches were shown to be effective for Bayesian models including logistic regression models, Gaussian mixture models and hierarchical models. Here, we introduce the R package parallelMCMCcombine which carries out four of these techniques for combining independent subset posterior samples. We illustrate each of the methods using a Bayesian logistic regression model for simulation data and a Bayesian Gamma model for real data; we also demonstrate features and capabilities of the R package. The package assumes the user has carried out the Bayesian analysis and has produced the independent subposterior samples outside of the package. The methods are primarily suited to models with unknown parameters of fixed dimension that exist in continuous parameter spaces. We envision this tool will allow researchers to explore the various methods for their specific applications and will assist future progress in this rapidly developing field.
Using Bayesian Networks to Improve Knowledge Assessment
Millan, Eva; Descalco, Luis; Castillo, Gladys; Oliveira, Paula; Diogo, Sandra
2013-01-01
In this paper, we describe the integration and evaluation of an existing generic Bayesian student model (GBSM) into an existing computerized testing system within the Mathematics Education Project (PmatE--Projecto Matematica Ensino) of the University of Aveiro. This generic Bayesian student model had been previously evaluated with simulated…
Bayesian analysis of exoplanet and binary orbits
Schulze-Hartung, Tim; Launhardt, Ralf; Henning, Thomas
2012-01-01
We introduce BASE (Bayesian astrometric and spectroscopic exoplanet detection and characterisation tool), a novel program for the combined or separate Bayesian analysis of astrometric and radial-velocity measurements of potential exoplanet hosts and binary stars. The capabilities of BASE are demonstrated using all publicly available data of the binary Mizar A.
Bayesian credible interval construction for Poisson statistics
Institute of Scientific and Technical Information of China (English)
ZHU Yong-Sheng
2008-01-01
The construction of the Bayesian credible (confidence) interval for a Poisson observable including both the signal and background with and without systematic uncertainties is presented.Introducing the conditional probability satisfying the requirement of the background not larger than the observed events to construct the Bayesian credible interval is also discussed.A Fortran routine,BPOCI,has been developed to implement the calculation.
Modeling Diagnostic Assessments with Bayesian Networks
Almond, Russell G.; DiBello, Louis V.; Moulder, Brad; Zapata-Rivera, Juan-Diego
2007-01-01
This paper defines Bayesian network models and examines their applications to IRT-based cognitive diagnostic modeling. These models are especially suited to building inference engines designed to be synchronous with the finer grained student models that arise in skills diagnostic assessment. Aspects of the theory and use of Bayesian network models…
Advances in Bayesian Modeling in Educational Research
Levy, Roy
2016-01-01
In this article, I provide a conceptually oriented overview of Bayesian approaches to statistical inference and contrast them with frequentist approaches that currently dominate conventional practice in educational research. The features and advantages of Bayesian approaches are illustrated with examples spanning several statistical modeling…
Learning dynamic Bayesian networks with mixed variables
DEFF Research Database (Denmark)
Bøttcher, Susanne Gammelgaard
This paper considers dynamic Bayesian networks for discrete and continuous variables. We only treat the case, where the distribution of the variables is conditional Gaussian. We show how to learn the parameters and structure of a dynamic Bayesian network and also how the Markov order can be learned...
The Bayesian Revolution Approaches Psychological Development
Shultz, Thomas R.
2007-01-01
This commentary reviews five articles that apply Bayesian ideas to psychological development, some with psychology experiments, some with computational modeling, and some with both experiments and modeling. The reviewed work extends the current Bayesian revolution into tasks often studied in children, such as causal learning and word learning, and…
Bayesian Network for multiple hypthesis tracking
W.P. Zajdel; B.J.A. Kröse
2002-01-01
For a flexible camera-to-camera tracking of multiple objects we model the objects behavior with a Bayesian network and combine it with the multiple hypohesis framework that associates observations with objects. Bayesian networks offer a possibility to factor complex, joint distributions into a produ
Institute of Scientific and Technical Information of China (English)
Weizhao YANG; Jie WANG; Jianping JIANG; Cheng LI; Feng XIE
2014-01-01
Echinotriton chinhaiensis is a critically endangered salamander and its distribution is restricted to Ningbo, Zhejiang Province of China. In this study, we developed and characterized iffteen polymorphic microsatellite loci forE. chinhaiensis from dinucleotide- and tetranucleotide- enriched library. The number of alleles ranges from 4 to 12 with an average of 7.27 alleles per locus. The observed and expected heterozygosities values were from 0.250 to 0.844 and 0.511 to 0.872 with an average value of 0.596 and 0.722; respectively. The polymorphic microsatellite loci described in this paper are useful in the further study on genetic diversity and gene lfow, which would be helpful to formulate effective conservation strategies for theE. chinhaiensis.
Nakao, Minoru
2015-10-01
The Ezo salamander, Hynobius retardatus, is endemic only to Hokkaido, the northernmost island of Japan. Gravid flukes of the family Gorgoderidae were discovered from the urinary bladder of H. retardatus. The parasites were identified as a new species named Phyllodistomum kanae sp. nov. In the neighboring Honshu island another bladder fluke, Phyllodistomum patellare, has already been found from the Japanese newt. The new species clearly differs from P. patellare in having a spherical ovary and very weakly lobed testes. The discovery of species of Phyllodistomum from urodelan amphibians is very uncommon in Eurasia. A molecular phylogeny based on 28S ribosomal DNA suggests that sphaeriid bivalves may serve as the first intermediate host for the new species. PMID:25892565
Directory of Open Access Journals (Sweden)
Gareth J Voss
Full Text Available Very little is known about the factors that cause variation in regenerative potential within and between species. Here, we used a genetic approach to identify heritable genetic factors that explain variation in tail regenerative outgrowth. A hybrid ambystomatid salamander (Ambystoma mexicanum x A. andersoni was crossed to an A. mexicanum and 217 offspring were induced to undergo metamorphosis and attain terrestrial adult morphology using thyroid hormone. Following metamorphosis, each salamander's tail tip was amputated and allowed to regenerate, and then amputated a second time and allowed to regenerate. Also, DNA was isolated from all individuals and genotypes were determined for 187 molecular markers distributed throughout the genome. The area of tissue that regenerated after the first and second amputations was highly positively correlated across males and females. Males presented wider tails and regenerated more tail tissue during both episodes of regeneration. Approximately 66-68% of the variation in regenerative outgrowth was explained by tail width, while tail length and genetic sex did not explain a significant amount of variation. A small effect QTL was identified as having a sex-independent effect on tail regeneration, but this QTL was only identified for the first episode of regeneration. Several molecular markers significantly affected regenerative outgrowth during both episodes of regeneration, but the effect sizes were small (<4% and correlated with tail width. The results show that ambysex and minor effect QTL explain variation in adult tail morphology and importantly, tail width. In turn, tail width at the amputation plane largely determines the rate of regenerative outgrowth. Because amputations in this study were made at approximately the same position of the tail, our results resolve an outstanding question in regenerative biology: regenerative outgrowth positively co-varies as a function of tail width at the amputation site.
Palmer, Catherine A; Watts, Richard A; Hastings, Amy P; Houck, Lynne D; Arnold, Stevan J
2010-05-01
Sexual communication in plethodontid salamanders is mediated by a proteinaceous pheromone that a male delivers to a female during courtship, boosting her receptivity. The pheromone consists of three proteins from three unrelated protein families. These proteins are among a small group of pheromones known to affect female receptivity in vertebrates. Previously, we showed that the genes of two of these proteins (PRF and SPF) are prone to incessant evolution driven by positive selection, presumably as a consequence of coevolution with female receptors. In this report, we focus on the evolution of the third pheromone protein gene family, plethodontid modulating factor (PMF), to determine whether it shows the same pattern of diversification. We used RT-PCR in mental gland cDNA to survey PMF sequences from three genera of plethodontid salamanders (27 spp.) to measure rates of evolution, level of gene diversification, modes of selection, and types of amino acid substitution. Like PRF and SPF, PMF is produced by a multigene family characterized by gene duplication and high levels of polymorphism. PMF evolution is rapid, incessant, and driven by positive selection. PMF is more extreme in these dimensions than both PRF and SPF. Nestled within this extraordinary variation, however, is a signature of purifying selection, acting to preserve important structural and biochemical features of the PMF protein (i.e., secretion signal, cysteine residues, and pI). Although a pattern of persistent diversification exists at the molecular level, the morphological and behavioral aspects of the pheromone delivery system show evolutionary stasis over millions of years.
Palmer, Catherine A; Watts, Richard A; Hastings, Amy P; Houck, Lynne D; Arnold, Stevan J
2010-05-01
Sexual communication in plethodontid salamanders is mediated by a proteinaceous pheromone that a male delivers to a female during courtship, boosting her receptivity. The pheromone consists of three proteins from three unrelated protein families. These proteins are among a small group of pheromones known to affect female receptivity in vertebrates. Previously, we showed that the genes of two of these proteins (PRF and SPF) are prone to incessant evolution driven by positive selection, presumably as a consequence of coevolution with female receptors. In this report, we focus on the evolution of the third pheromone protein gene family, plethodontid modulating factor (PMF), to determine whether it shows the same pattern of diversification. We used RT-PCR in mental gland cDNA to survey PMF sequences from three genera of plethodontid salamanders (27 spp.) to measure rates of evolution, level of gene diversification, modes of selection, and types of amino acid substitution. Like PRF and SPF, PMF is produced by a multigene family characterized by gene duplication and high levels of polymorphism. PMF evolution is rapid, incessant, and driven by positive selection. PMF is more extreme in these dimensions than both PRF and SPF. Nestled within this extraordinary variation, however, is a signature of purifying selection, acting to preserve important structural and biochemical features of the PMF protein (i.e., secretion signal, cysteine residues, and pI). Although a pattern of persistent diversification exists at the molecular level, the morphological and behavioral aspects of the pheromone delivery system show evolutionary stasis over millions of years. PMID:20407892
From biomedicine to natural history research: EST resources for ambystomatid salamanders
Directory of Open Access Journals (Sweden)
Bryant Susan V
2004-08-01
Full Text Available Abstract Background Establishing genomic resources for closely related species will provide comparative insights that are crucial for understanding diversity and variability at multiple levels of biological organization. We developed ESTs for Mexican axolotl (Ambystoma mexicanum and Eastern tiger salamander (A. tigrinum tigrinum, species with deep and diverse research histories. Results Approximately 40,000 quality cDNA sequences were isolated for these species from various tissues, including regenerating limb and tail. These sequences and an existing set of 16,030 cDNA sequences for A. mexicanum were processed to yield 35,413 and 20,599 high quality ESTs for A. mexicanum and A. t. tigrinum, respectively. Because the A. t. tigrinum ESTs were obtained primarily from a normalized library, an approximately equal number of contigs were obtained for each species, with 21,091 unique contigs identified overall. The 10,592 contigs that showed significant similarity to sequences from the human RefSeq database reflected a diverse array of molecular functions and biological processes, with many corresponding to genes expressed during spinal cord injury in rat and fin regeneration in zebrafish. To demonstrate the utility of these EST resources, we searched databases to identify probes for regeneration research, characterized intra- and interspecific nucleotide polymorphism, saturated a human – Ambystoma synteny group with marker loci, and extended PCR primer sets designed for A. mexicanum / A. t. tigrinum orthologues to a related tiger salamander species. Conclusions Our study highlights the value of developing resources in traditional model systems where the likelihood of information transfer to multiple, closely related taxa is high, thus simultaneously enabling both laboratory and natural history research.
2nd Bayesian Young Statisticians Meeting
Bitto, Angela; Kastner, Gregor; Posekany, Alexandra
2015-01-01
The Second Bayesian Young Statisticians Meeting (BAYSM 2014) and the research presented here facilitate connections among researchers using Bayesian Statistics by providing a forum for the development and exchange of ideas. WU Vienna University of Business and Economics hosted BAYSM 2014 from September 18th to 19th. The guidance of renowned plenary lecturers and senior discussants is a critical part of the meeting and this volume, which follows publication of contributions from BAYSM 2013. The meeting's scientific program reflected the variety of fields in which Bayesian methods are currently employed or could be introduced in the future. Three brilliant keynote lectures by Chris Holmes (University of Oxford), Christian Robert (Université Paris-Dauphine), and Mike West (Duke University), were complemented by 24 plenary talks covering the major topics Dynamic Models, Applications, Bayesian Nonparametrics, Biostatistics, Bayesian Methods in Economics, and Models and Methods, as well as a lively poster session ...
BAYESIAN BICLUSTERING FOR PATIENT STRATIFICATION.
Khakabimamaghani, Sahand; Ester, Martin
2016-01-01
The move from Empirical Medicine towards Personalized Medicine has attracted attention to Stratified Medicine (SM). Some methods are provided in the literature for patient stratification, which is the central task of SM, however, there are still significant open issues. First, it is still unclear if integrating different datatypes will help in detecting disease subtypes more accurately, and, if not, which datatype(s) are most useful for this task. Second, it is not clear how we can compare different methods of patient stratification. Third, as most of the proposed stratification methods are deterministic, there is a need for investigating the potential benefits of applying probabilistic methods. To address these issues, we introduce a novel integrative Bayesian biclustering method, called B2PS, for patient stratification and propose methods for evaluating the results. Our experimental results demonstrate the superiority of B2PS over a popular state-of-the-art method and the benefits of Bayesian approaches. Our results agree with the intuition that transcriptomic data forms a better basis for patient stratification than genomic data.
BAYESIAN BICLUSTERING FOR PATIENT STRATIFICATION.
Khakabimamaghani, Sahand; Ester, Martin
2016-01-01
The move from Empirical Medicine towards Personalized Medicine has attracted attention to Stratified Medicine (SM). Some methods are provided in the literature for patient stratification, which is the central task of SM, however, there are still significant open issues. First, it is still unclear if integrating different datatypes will help in detecting disease subtypes more accurately, and, if not, which datatype(s) are most useful for this task. Second, it is not clear how we can compare different methods of patient stratification. Third, as most of the proposed stratification methods are deterministic, there is a need for investigating the potential benefits of applying probabilistic methods. To address these issues, we introduce a novel integrative Bayesian biclustering method, called B2PS, for patient stratification and propose methods for evaluating the results. Our experimental results demonstrate the superiority of B2PS over a popular state-of-the-art method and the benefits of Bayesian approaches. Our results agree with the intuition that transcriptomic data forms a better basis for patient stratification than genomic data. PMID:26776199
Halo detection via large-scale Bayesian inference
Merson, Alexander I.; Jasche, Jens; Abdalla, Filipe B.; Lahav, Ofer; Wandelt, Benjamin; Jones, D. Heath; Colless, Matthew
2016-08-01
We present a proof-of-concept of a novel and fully Bayesian methodology designed to detect haloes of different masses in cosmological observations subject to noise and systematic uncertainties. Our methodology combines the previously published Bayesian large-scale structure inference algorithm, HAmiltonian Density Estimation and Sampling algorithm (HADES), and a Bayesian chain rule (the Blackwell-Rao estimator), which we use to connect the inferred density field to the properties of dark matter haloes. To demonstrate the capability of our approach, we construct a realistic galaxy mock catalogue emulating the wide-area 6-degree Field Galaxy Survey, which has a median redshift of approximately 0.05. Application of HADES to the catalogue provides us with accurately inferred three-dimensional density fields and corresponding quantification of uncertainties inherent to any cosmological observation. We then use a cosmological simulation to relate the amplitude of the density field to the probability of detecting a halo with mass above a specified threshold. With this information, we can sum over the HADES density field realisations to construct maps of detection probabilities and demonstrate the validity of this approach within our mock scenario. We find that the probability of successful detection of haloes in the mock catalogue increases as a function of the signal to noise of the local galaxy observations. Our proposed methodology can easily be extended to account for more complex scientific questions and is a promising novel tool to analyse the cosmic large-scale structure in observations.
Templeton, A. R.; Routman, E.; Phillips, C. A.
1995-01-01
Nonrandom associations of alleles or haplotypes with geographical location can arise from restricted gene flow, historical events (fragmentation, range expansion, colonization), or any mixture of these factors. In this paper, we show how a nested cladistic analysis of geographical distances can be used to test the null hypothesis of no geographical association of haplotypes, test the hypothesis that significant associations are due to restricted gene flow, and identify patterns of significant association that are due to historical events. In this last case, criteria are given to discriminate among contiguous range expansion, long-distance colonization, and population fragmentation. The ability to make these discriminations depends critically upon an adequate geographical sampling design. These points are illustrated with a worked example: mitochondrial DNA haplotypes in the salamander Ambystoma tigrinum. For this example, prior information exists about restricted gene flow and likely historical events, and the nested cladistic analyses were completely concordant with this prior information. This concordance establishes the plausibility of this nested cladistic approach, but much future work will be necessary to demonstrate robustness and to explore the power and accuracy of this procedure. PMID:7498753
Bayesian Estimation of Small Effects in Exercise and Sports Science
Mengersen, Kerrie L.; Drovandi, Christopher C.; Robert, Christian P.; Pyne, David B.; Gore, Christopher J.
2016-01-01
The aim of this paper is to provide a Bayesian formulation of the so-called magnitude-based inference approach to quantifying and interpreting effects, and in a case study example provide accurate probabilistic statements that correspond to the intended magnitude-based inferences. The model is described in the context of a published small-scale athlete study which employed a magnitude-based inference approach to compare the effect of two altitude training regimens (live high-train low (LHTL), and intermittent hypoxic exposure (IHE)) on running performance and blood measurements of elite triathletes. The posterior distributions, and corresponding point and interval estimates, for the parameters and associated effects and comparisons of interest, were estimated using Markov chain Monte Carlo simulations. The Bayesian analysis was shown to provide more direct probabilistic comparisons of treatments and able to identify small effects of interest. The approach avoided asymptotic assumptions and overcame issues such as multiple testing. Bayesian analysis of unscaled effects showed a probability of 0.96 that LHTL yields a substantially greater increase in hemoglobin mass than IHE, a 0.93 probability of a substantially greater improvement in running economy and a greater than 0.96 probability that both IHE and LHTL yield a substantially greater improvement in maximum blood lactate concentration compared to a Placebo. The conclusions are consistent with those obtained using a ‘magnitude-based inference’ approach that has been promoted in the field. The paper demonstrates that a fully Bayesian analysis is a simple and effective way of analysing small effects, providing a rich set of results that are straightforward to interpret in terms of probabilistic statements. PMID:27073897
Bayesian Estimation of Small Effects in Exercise and Sports Science.
Mengersen, Kerrie L; Drovandi, Christopher C; Robert, Christian P; Pyne, David B; Gore, Christopher J
2016-01-01
The aim of this paper is to provide a Bayesian formulation of the so-called magnitude-based inference approach to quantifying and interpreting effects, and in a case study example provide accurate probabilistic statements that correspond to the intended magnitude-based inferences. The model is described in the context of a published small-scale athlete study which employed a magnitude-based inference approach to compare the effect of two altitude training regimens (live high-train low (LHTL), and intermittent hypoxic exposure (IHE)) on running performance and blood measurements of elite triathletes. The posterior distributions, and corresponding point and interval estimates, for the parameters and associated effects and comparisons of interest, were estimated using Markov chain Monte Carlo simulations. The Bayesian analysis was shown to provide more direct probabilistic comparisons of treatments and able to identify small effects of interest. The approach avoided asymptotic assumptions and overcame issues such as multiple testing. Bayesian analysis of unscaled effects showed a probability of 0.96 that LHTL yields a substantially greater increase in hemoglobin mass than IHE, a 0.93 probability of a substantially greater improvement in running economy and a greater than 0.96 probability that both IHE and LHTL yield a substantially greater improvement in maximum blood lactate concentration compared to a Placebo. The conclusions are consistent with those obtained using a 'magnitude-based inference' approach that has been promoted in the field. The paper demonstrates that a fully Bayesian analysis is a simple and effective way of analysing small effects, providing a rich set of results that are straightforward to interpret in terms of probabilistic statements.
Bayesian Estimation of Small Effects in Exercise and Sports Science.
Mengersen, Kerrie L; Drovandi, Christopher C; Robert, Christian P; Pyne, David B; Gore, Christopher J
2016-01-01
The aim of this paper is to provide a Bayesian formulation of the so-called magnitude-based inference approach to quantifying and interpreting effects, and in a case study example provide accurate probabilistic statements that correspond to the intended magnitude-based inferences. The model is described in the context of a published small-scale athlete study which employed a magnitude-based inference approach to compare the effect of two altitude training regimens (live high-train low (LHTL), and intermittent hypoxic exposure (IHE)) on running performance and blood measurements of elite triathletes. The posterior distributions, and corresponding point and interval estimates, for the parameters and associated effects and comparisons of interest, were estimated using Markov chain Monte Carlo simulations. The Bayesian analysis was shown to provide more direct probabilistic comparisons of treatments and able to identify small effects of interest. The approach avoided asymptotic assumptions and overcame issues such as multiple testing. Bayesian analysis of unscaled effects showed a probability of 0.96 that LHTL yields a substantially greater increase in hemoglobin mass than IHE, a 0.93 probability of a substantially greater improvement in running economy and a greater than 0.96 probability that both IHE and LHTL yield a substantially greater improvement in maximum blood lactate concentration compared to a Placebo. The conclusions are consistent with those obtained using a 'magnitude-based inference' approach that has been promoted in the field. The paper demonstrates that a fully Bayesian analysis is a simple and effective way of analysing small effects, providing a rich set of results that are straightforward to interpret in terms of probabilistic statements. PMID:27073897
Bayesian analysis of genetic differentiation between populations.
Corander, Jukka; Waldmann, Patrik; Sillanpää, Mikko J
2003-01-01
We introduce a Bayesian method for estimating hidden population substructure using multilocus molecular markers and geographical information provided by the sampling design. The joint posterior distribution of the substructure and allele frequencies of the respective populations is available in an analytical form when the number of populations is small, whereas an approximation based on a Markov chain Monte Carlo simulation approach can be obtained for a moderate or large number of populations. Using the joint posterior distribution, posteriors can also be derived for any evolutionary population parameters, such as the traditional fixation indices. A major advantage compared to most earlier methods is that the number of populations is treated here as an unknown parameter. What is traditionally considered as two genetically distinct populations, either recently founded or connected by considerable gene flow, is here considered as one panmictic population with a certain probability based on marker data and prior information. Analyses of previously published data on the Moroccan argan tree (Argania spinosa) and of simulated data sets suggest that our method is capable of estimating a population substructure, while not artificially enforcing a substructure when it does not exist. The software (BAPS) used for the computations is freely available from http://www.rni.helsinki.fi/~mjs. PMID:12586722
Gandhi, Jaina S; Cecala, Kristen K
2016-09-01
The objective of the present study was to evaluate the potential interactive effects of stream temperatures and environmentally relevant glyphosate-based herbicide concentrations on movement and antipredator behaviors of larval Eurycea wilderae (Blue Ridge two-lined salamander). Larval salamanders were exposed to 1 of 4 environmentally relevant glyphosate concentrations (0.00 µg acid equivalent [a.e.]/L, 0.73 µg a.e./L, 1.46 µg a.e./L, and 2.92 µg a.e./L) at either ambient (12 °C) or elevated (23 °C) water temperature. Behaviors observed included the exploration of a novel habitat, use of refuge, habitat selection relative to a potential predator, and burst movement distance. In the absence of glyphosate, temperature consistently affected movement and refuge-use behavior, with individuals moving longer distances more frequently and using refuge less at warm temperatures; however, when glyphosate was added, the authors observed inconsistent effects of temperature that may have resulted from differential toxicity at various temperatures. Larval salamanders made shorter, more frequent movements and demonstrated reduced burst distance at higher glyphosate concentrations. The authors also found that lower glyphosate concentrations sometimes had stronger effects than higher concentrations (i.e., nonmonotonic dose responses), suggesting that standard safety tests conducted only at higher glyphosate concentrations might overlook important sublethal effects on salamander behavior. These data demonstrate that sublethal effects of glyphosate-based herbicides on natural behaviors of amphibians can occur with short-term exposure to environmentally relevant concentrations. Environ Toxicol Chem 2016;35:2297-2303. © 2016 SETAC.
Bayesian analysis of spatial point processes in the neighbourhood of Voronoi networks
DEFF Research Database (Denmark)
Skare, Øivind; Møller, Jesper; Vedel Jensen, Eva B.
A model for an inhomogeneous Poisson process with high intensity near the edges of a Voronoi tessellation in 2D or 3D is proposed. The model is analysed in a Bayesian setting with priors on nuclei of the Voronoi tessellation and other model parameters. An MCMC algorithm is constructed to sample...
Bayesian analysis of spatial point processes in the neighbourhood of Voronoi networks
DEFF Research Database (Denmark)
Skare, Øivind; Møller, Jesper; Jensen, Eva B. Vedel
2007-01-01
A model for an inhomogeneous Poisson process with high intensity near the edges of a Voronoi tessellation in 2D or 3D is proposed. The model is analysed in a Bayesian setting with priors on nuclei of the Voronoi tessellation and other model parameters. An MCMC algorithm is constructed to sample...
In this paper, we present methods for estimating Freundlich isotherm fitting parameters (K and N) and their joint uncertainty, which have been implemented into the freeware software platforms R and WinBUGS. These estimates were determined by both Frequentist and Bayesian analyse...
Directory of Open Access Journals (Sweden)
Nalin eHarischandra
2011-11-01
Full Text Available Here, we use a three-dimensional, neuro-musculo-mechanical model of a salamander with realistic physical parameters in order to investigate the role of sensory feedback in gait generation and transition. Activation of limb and axial muscles were driven by neural output patterns obtained from a central pattern generator (CPG which is composed of simulated spiking neurons with adaptation. The CPG consists of a body CPG and four limb CPGs that are interconnected via synapses both ipsilateraly and contralaterally. We use the model both with and without sensory modulation and for different combinations of ipsilateral and contralateral coupling between the limb CPGs. We found that the proprioceptive sensory inputs are essential in obtaining a coordinated walking gait. The sensory feedback includes the signals coming from the stretch receptor like intraspinal neurons located in the girdle regions and the limb stretch receptors residing in the hip and scapula regions of the salamander. On the other hand, coordinated motor output patterns for the trotting gait were obtainable without the sensory inputs. We found that the gait transition from walking to trotting can be induced by increased activity of the descending drive coming from the mesencephalic locomotor region (MLR and is helped by the sensory inputs at the hip and scapula regions detecting the late stance phase. More neurophysiological experiments are required to identify the precise type of mechanoreceptors in the salamander and the neural mechanisms mediating the sensory modulation.
Yun, Maximina H.; Gates, Phillip B.; Brockes, Jeremy P.
2014-01-01
Summary In regeneration-competent vertebrates, such as salamanders, regeneration depends on the ability of various differentiated adult cell types to undergo natural reprogramming. This ability is rarely observed in regeneration-incompetent species such as mammals, providing an explanation for their poor regenerative potential. To date, little is known about the molecular mechanisms mediating natural reprogramming during regeneration. Here, we have identified the extent of extracellular signal-regulated kinase (ERK) activation as a key component of such mechanisms. We show that sustained ERK activation following serum induction is required for re-entry into the cell cycle of postmitotic salamander muscle cells, partially by promoting the downregulation of p53 activity. Moreover, ERK activation induces epigenetic modifications and downregulation of muscle-specific genes such as Sox6. Remarkably, while long-term ERK activation is found in salamander myotubes, only transient activation is seen in their mammalian counterparts, suggesting that the extent of ERK activation could underlie differences in regenerative competence between species. PMID:25068118
A Bayesian Reflection on Surfaces
Directory of Open Access Journals (Sweden)
David R. Wolf
1999-10-01
Full Text Available Abstract: The topic of this paper is a novel Bayesian continuous-basis field representation and inference framework. Within this paper several problems are solved: The maximally informative inference of continuous-basis fields, that is where the basis for the field is itself a continuous object and not representable in a finite manner; the tradeoff between accuracy of representation in terms of information learned, and memory or storage capacity in bits; the approximation of probability distributions so that a maximal amount of information about the object being inferred is preserved; an information theoretic justification for multigrid methodology. The maximally informative field inference framework is described in full generality and denoted the Generalized Kalman Filter. The Generalized Kalman Filter allows the update of field knowledge from previous knowledge at any scale, and new data, to new knowledge at any other scale. An application example instance, the inference of continuous surfaces from measurements (for example, camera image data, is presented.
Quantum Bayesianism at the Perimeter
Fuchs, Christopher A
2010-01-01
The author summarizes the Quantum Bayesian viewpoint of quantum mechanics, developed originally by C. M. Caves, R. Schack, and himself. It is a view crucially dependent upon the tools of quantum information theory. Work at the Perimeter Institute for Theoretical Physics continues the development and is focused on the hard technical problem of a finding a good representation of quantum mechanics purely in terms of probabilities, without amplitudes or Hilbert-space operators. The best candidate representation involves a mysterious entity called a symmetric informationally complete quantum measurement. Contemplation of it gives a way of thinking of the Born Rule as an addition to the rules of probability theory, applicable when one gambles on the consequences of interactions with physical systems. The article ends by outlining some directions for future work.
Hedging Strategies for Bayesian Optimization
Brochu, Eric; de Freitas, Nando
2010-01-01
Bayesian optimization with Gaussian processes has become an increasingly popular tool in the machine learning community. It is efficient and can be used when very little is known about the objective function, making it popular in expensive black-box optimization scenarios. It is able to do this by sampling the objective using an acquisition function which incorporates the model's estimate of the objective and the uncertainty at any given point. However, there are several different parameterized acquisition functions in the literature, and it is often unclear which one to use. Instead of using a single acquisition function, we adopt a portfolio of acquisition functions governed by an online multi-armed bandit strategy. We describe the method, which we call GP-Hedge, and show that this method almost always outperforms the best individual acquisition function.
Bayesian Networks and Influence Diagrams
DEFF Research Database (Denmark)
Kjærulff, Uffe Bro; Madsen, Anders Læsø
under uncertainty. The theory and methods presented are illustrated through more than 140 examples, and exercises are included for the reader to check his or her level of understanding. The techniques and methods presented on model construction and verification, modeling techniques and tricks, learning......Bayesian Networks and Influence Diagrams: A Guide to Construction and Analysis, Second Edition, provides a comprehensive guide for practitioners who wish to understand, construct, and analyze intelligent systems for decision support based on probabilistic networks. This new edition contains six new...... sections, in addition to fully-updated examples, tables, figures, and a revised appendix. Intended primarily for practitioners, this book does not require sophisticated mathematical skills or deep understanding of the underlying theory and methods nor does it discuss alternative technologies for reasoning...
State Information in Bayesian Games
Cuff, Paul
2009-01-01
Two-player zero-sum repeated games are well understood. Computing the value of such a game is straightforward. Additionally, if the payoffs are dependent on a random state of the game known to one, both, or neither of the players, the resulting value of the game has been analyzed under the framework of Bayesian games. This investigation considers the optimal performance in a game when a helper is transmitting state information to one of the players. Encoding information for an adversarial setting (game) requires a different result than rate-distortion theory provides. Game theory has accentuated the importance of randomization (mixed strategy), which does not find a significant role in most communication modems and source coding codecs. Higher rates of communication, used in the right way, allow the message to include the necessary random component useful in games.
Multiview Bayesian Correlated Component Analysis
DEFF Research Database (Denmark)
Kamronn, Simon Due; Poulsen, Andreas Trier; Hansen, Lars Kai
2015-01-01
Correlated component analysis as proposed by Dmochowski, Sajda, Dias, and Parra (2012) is a tool for investigating brain process similarity in the responses to multiple views of a given stimulus. Correlated components are identified under the assumption that the involved spatial networks...... are identical. Here we propose a hierarchical probabilistic model that can infer the level of universality in such multiview data, from completely unrelated representations, corresponding to canonical correlation analysis, to identical representations as in correlated component analysis. This new model, which...... we denote Bayesian correlated component analysis, evaluates favorably against three relevant algorithms in simulated data. A well-established benchmark EEG data set is used to further validate the new model and infer the variability of spatial representations across multiple subjects....
Elvira, Clément; Dobigeon, Nicolas
2015-01-01
Sparse representations have proven their efficiency in solving a wide class of inverse problems encountered in signal and image processing. Conversely, enforcing the information to be spread uniformly over representation coefficients exhibits relevant properties in various applications such as digital communications. Anti-sparse regularization can be naturally expressed through an $\\ell_{\\infty}$-norm penalty. This paper derives a probabilistic formulation of such representations. A new probability distribution, referred to as the democratic prior, is first introduced. Its main properties as well as three random variate generators for this distribution are derived. Then this probability distribution is used as a prior to promote anti-sparsity in a Gaussian linear inverse problem, yielding a fully Bayesian formulation of anti-sparse coding. Two Markov chain Monte Carlo (MCMC) algorithms are proposed to generate samples according to the posterior distribution. The first one is a standard Gibbs sampler. The seco...
Nonparametric Bayesian inference in biostatistics
Müller, Peter
2015-01-01
As chapters in this book demonstrate, BNP has important uses in clinical sciences and inference for issues like unknown partitions in genomics. Nonparametric Bayesian approaches (BNP) play an ever expanding role in biostatistical inference from use in proteomics to clinical trials. Many research problems involve an abundance of data and require flexible and complex probability models beyond the traditional parametric approaches. As this book's expert contributors show, BNP approaches can be the answer. Survival Analysis, in particular survival regression, has traditionally used BNP, but BNP's potential is now very broad. This applies to important tasks like arrangement of patients into clinically meaningful subpopulations and segmenting the genome into functionally distinct regions. This book is designed to both review and introduce application areas for BNP. While existing books provide theoretical foundations, this book connects theory to practice through engaging examples and research questions. Chapters c...
Bayesian Kernel Mixtures for Counts.
Canale, Antonio; Dunson, David B
2011-12-01
Although Bayesian nonparametric mixture models for continuous data are well developed, there is a limited literature on related approaches for count data. A common strategy is to use a mixture of Poissons, which unfortunately is quite restrictive in not accounting for distributions having variance less than the mean. Other approaches include mixing multinomials, which requires finite support, and using a Dirichlet process prior with a Poisson base measure, which does not allow smooth deviations from the Poisson. As a broad class of alternative models, we propose to use nonparametric mixtures of rounded continuous kernels. An efficient Gibbs sampler is developed for posterior computation, and a simulation study is performed to assess performance. Focusing on the rounded Gaussian case, we generalize the modeling framework to account for multivariate count data, joint modeling with continuous and categorical variables, and other complications. The methods are illustrated through applications to a developmental toxicity study and marketing data. This article has supplementary material online. PMID:22523437
Bayesian networks in educational assessment
Almond, Russell G; Steinberg, Linda S; Yan, Duanli; Williamson, David M
2015-01-01
Bayesian inference networks, a synthesis of statistics and expert systems, have advanced reasoning under uncertainty in medicine, business, and social sciences. This innovative volume is the first comprehensive treatment exploring how they can be applied to design and analyze innovative educational assessments. Part I develops Bayes nets’ foundations in assessment, statistics, and graph theory, and works through the real-time updating algorithm. Part II addresses parametric forms for use with assessment, model-checking techniques, and estimation with the EM algorithm and Markov chain Monte Carlo (MCMC). A unique feature is the volume’s grounding in Evidence-Centered Design (ECD) framework for assessment design. This “design forward” approach enables designers to take full advantage of Bayes nets’ modularity and ability to model complex evidentiary relationships that arise from performance in interactive, technology-rich assessments such as simulations. Part III describes ECD, situates Bayes nets as ...
Bayesian models a statistical primer for ecologists
Hobbs, N Thompson
2015-01-01
Bayesian modeling has become an indispensable tool for ecological research because it is uniquely suited to deal with complexity in a statistically coherent way. This textbook provides a comprehensive and accessible introduction to the latest Bayesian methods-in language ecologists can understand. Unlike other books on the subject, this one emphasizes the principles behind the computations, giving ecologists a big-picture understanding of how to implement this powerful statistical approach. Bayesian Models is an essential primer for non-statisticians. It begins with a definition of probabili
Compiling Relational Bayesian Networks for Exact Inference
DEFF Research Database (Denmark)
Jaeger, Manfred; Darwiche, Adnan; Chavira, Mark
2006-01-01
We describe in this paper a system for exact inference with relational Bayesian networks as defined in the publicly available PRIMULA tool. The system is based on compiling propositional instances of relational Bayesian networks into arithmetic circuits and then performing online inference...... by evaluating and differentiating these circuits in time linear in their size. We report on experimental results showing successful compilation and efficient inference on relational Bayesian networks, whose PRIMULA--generated propositional instances have thousands of variables, and whose jointrees have clusters...
The Diagnosis of Reciprocating Machinery by Bayesian Networks
Institute of Scientific and Technical Information of China (English)
无
2003-01-01
A Bayesian Network is a reasoning tool based on probability theory and has many advantages that other reasoning tools do not have. This paper discusses the basic theory of Bayesian networks and studies the problems in constructing Bayesian networks. The paper also constructs a Bayesian diagnosis network of a reciprocating compressor. The example helps us to draw a conclusion that Bayesian diagnosis networks can diagnose reciprocating machinery effectively.
International Nuclear Information System (INIS)
The Tohoku hynobiid salamanders, Hynobius lichenatus, were chronically irradiated with γ-rays from embryonic to juvenile stages for 450 days. At 490 μGy h−1 or lower dose rates, growth and survival were not significantly affected by irradiation, and any morphological aberrations and histological damages were not observed. At 4600 μGy h−1, growth was severely inhibited, and all the individuals died mostly at the juvenile stage. Chronic LD50 was 42 Gy as a total dose. In the liver, the number of hematopoietic cells was significantly reduced in the living juveniles, and these cells disappeared in the dead juveniles. In the spleen, mature lymphocytes were depleted in the living larvae, and almost all the heamtopoietic cells disappeared in the dead juveniles. These results suggest that this salamander died due to acute radiation syndrome, i.e., hematopoietic damage and subsequent sepsis caused by immune depression. The death would be also attributed to skin damage inducing infection. At 18,000 μGy h−1, morphological aberrations and severe growth inhibition were observed. All the individuals died at the larval stage due to a multiple organ failure. Chronic LD50 was 28 Gy as a total dose. Assuming that chronic LD50 was 42 Gy at lower dose rates than 4600 μGy h−1, a chronic median lethal dose rate could be estimated to be <340 μGy h−1 for the whole life (>14 years). These results suggest that, among guidance dose rates, i.e., 4–400 μGy h−1, proposed by various organisations and research programmes for protection of amphibians and taxonomic groups or ecosystems including amphibians, most of them would protect this salamander but the highest value may not on the whole life scale. - Highlights: • The salamanders, Hynobius lichenatus, were chronically γ-irradiated for 450 days. • At 490 μGy h−1 or lower, irradiation did not significantly affect growth and survival. • All the individuals died at 4600 or 18,000 μGy h−1. • A median lethal dose
Learning Bayesian networks for discrete data
Liang, Faming
2009-02-01
Bayesian networks have received much attention in the recent literature. In this article, we propose an approach to learn Bayesian networks using the stochastic approximation Monte Carlo (SAMC) algorithm. Our approach has two nice features. Firstly, it possesses the self-adjusting mechanism and thus avoids essentially the local-trap problem suffered by conventional MCMC simulation-based approaches in learning Bayesian networks. Secondly, it falls into the class of dynamic importance sampling algorithms; the network features can be inferred by dynamically weighted averaging the samples generated in the learning process, and the resulting estimates can have much lower variation than the single model-based estimates. The numerical results indicate that our approach can mix much faster over the space of Bayesian networks than the conventional MCMC simulation-based approaches. © 2008 Elsevier B.V. All rights reserved.
A Bayesian approach to model uncertainty
International Nuclear Information System (INIS)
A Bayesian approach to model uncertainty is taken. For the case of a finite number of alternative models, the model uncertainty is equivalent to parameter uncertainty. A derivation based on Savage's partition problem is given
Bayesian Control for Concentrating Mixed Nuclear Waste
Welch, Robert L.; Smith, Clayton
2013-01-01
A control algorithm for batch processing of mixed waste is proposed based on conditional Gaussian Bayesian networks. The network is compiled during batch staging for real-time response to sensor input.
An Intuitive Dashboard for Bayesian Network Inference
International Nuclear Information System (INIS)
Current Bayesian network software packages provide good graphical interface for users who design and develop Bayesian networks for various applications. However, the intended end-users of these networks may not necessarily find such an interface appealing and at times it could be overwhelming, particularly when the number of nodes in the network is large. To circumvent this problem, this paper presents an intuitive dashboard, which provides an additional layer of abstraction, enabling the end-users to easily perform inferences over the Bayesian networks. Unlike most software packages, which display the nodes and arcs of the network, the developed tool organises the nodes based on the cause-and-effect relationship, making the user-interaction more intuitive and friendly. In addition to performing various types of inferences, the users can conveniently use the tool to verify the behaviour of the developed Bayesian network. The tool has been developed using QT and SMILE libraries in C++
An Intuitive Dashboard for Bayesian Network Inference
Reddy, Vikas; Charisse Farr, Anna; Wu, Paul; Mengersen, Kerrie; Yarlagadda, Prasad K. D. V.
2014-03-01
Current Bayesian network software packages provide good graphical interface for users who design and develop Bayesian networks for various applications. However, the intended end-users of these networks may not necessarily find such an interface appealing and at times it could be overwhelming, particularly when the number of nodes in the network is large. To circumvent this problem, this paper presents an intuitive dashboard, which provides an additional layer of abstraction, enabling the end-users to easily perform inferences over the Bayesian networks. Unlike most software packages, which display the nodes and arcs of the network, the developed tool organises the nodes based on the cause-and-effect relationship, making the user-interaction more intuitive and friendly. In addition to performing various types of inferences, the users can conveniently use the tool to verify the behaviour of the developed Bayesian network. The tool has been developed using QT and SMILE libraries in C++.
Nomograms for Visualization of Naive Bayesian Classifier
Možina, Martin; Demšar, Janez; Michael W Kattan; Zupan, Blaz
2004-01-01
Besides good predictive performance, the naive Bayesian classifier can also offer a valuable insight into the structure of the training data and effects of the attributes on the class probabilities. This structure may be effectively revealed through visualization of the classifier. We propose a new way to visualize the naive Bayesian model in the form of a nomogram. The advantages of the proposed method are simplicity of presentation, clear display of the effects of individual attribute value...
Subjective Bayesian Analysis: Principles and Practice
Goldstein, Michael
2006-01-01
We address the position of subjectivism within Bayesian statistics. We argue, first, that the subjectivist Bayes approach is the only feasible method for tackling many important practical problems. Second, we describe the essential role of the subjectivist approach in scientific analysis. Third, we consider possible modifications to the Bayesian approach from a subjectivist viewpoint. Finally, we address the issue of pragmatism in implementing the subjectivist approach.
Bayesian Analysis of Multivariate Probit Models
Siddhartha Chib; Edward Greenberg
1996-01-01
This paper provides a unified simulation-based Bayesian and non-Bayesian analysis of correlated binary data using the multivariate probit model. The posterior distribution is simulated by Markov chain Monte Carlo methods, and maximum likelihood estimates are obtained by a Markov chain Monte Carlo version of the E-M algorithm. Computation of Bayes factors from the simulation output is also considered. The methods are applied to a bivariate data set, to a 534-subject, four-year longitudinal dat...
Fitness inheritance in the Bayesian optimization algorithm
Pelikan, Martin; Sastry, Kumara
2004-01-01
This paper describes how fitness inheritance can be used to estimate fitness for a proportion of newly sampled candidate solutions in the Bayesian optimization algorithm (BOA). The goal of estimating fitness for some candidate solutions is to reduce the number of fitness evaluations for problems where fitness evaluation is expensive. Bayesian networks used in BOA to model promising solutions and generate the new ones are extended to allow not only for modeling and sampling candidate solutions...
Kernel Bayesian Inference with Posterior Regularization
Song, Yang; Jun ZHU; Ren, Yong
2016-01-01
We propose a vector-valued regression problem whose solution is equivalent to the reproducing kernel Hilbert space (RKHS) embedding of the Bayesian posterior distribution. This equivalence provides a new understanding of kernel Bayesian inference. Moreover, the optimization problem induces a new regularization for the posterior embedding estimator, which is faster and has comparable performance to the squared regularization in kernel Bayes' rule. This regularization coincides with a former th...
Bayesian Classification in Medicine: The Transferability Question *
Zagoria, Ronald J.; Reggia, James A.; Price, Thomas R.; Banko, Maryann
1981-01-01
Using probabilities derived from a geographically distant patient population, we applied Bayesian classification to categorize stroke patients by etiology. Performance was assessed both by error rate and with a new linear accuracy coefficient. This approach to patient classification was found to be surprisingly accurate when compared to classification by two neurologists and to classification by the Bayesian method using “low cost” local and subjective probabilities. We conclude that for some...
Bayesian target tracking based on particle filter
Institute of Scientific and Technical Information of China (English)
无
2005-01-01
For being able to deal with the nonlinear or non-Gaussian problems, particle filters have been studied by many researchers. Based on particle filter, the extended Kalman filter (EKF) proposal function is applied to Bayesian target tracking. Markov chain Monte Carlo (MCMC) method, the resampling step, etc novel techniques are also introduced into Bayesian target tracking. And the simulation results confirm the improved particle filter with these techniques outperforms the basic one.
Bayesian Variable Selection in Spatial Autoregressive Models
Jesus Crespo Cuaresma; Philipp Piribauer
2015-01-01
This paper compares the performance of Bayesian variable selection approaches for spatial autoregressive models. We present two alternative approaches which can be implemented using Gibbs sampling methods in a straightforward way and allow us to deal with the problem of model uncertainty in spatial autoregressive models in a flexible and computationally efficient way. In a simulation study we show that the variable selection approaches tend to outperform existing Bayesian model averaging tech...
Fuzzy Functional Dependencies and Bayesian Networks
Institute of Scientific and Technical Information of China (English)
LIU WeiYi(刘惟一); SONG Ning(宋宁)
2003-01-01
Bayesian networks have become a popular technique for representing and reasoning with probabilistic information. The fuzzy functional dependency is an important kind of data dependencies in relational databases with fuzzy values. The purpose of this paper is to set up a connection between these data dependencies and Bayesian networks. The connection is done through a set of methods that enable people to obtain the most information of independent conditions from fuzzy functional dependencies.
Bayesian Models of Brain and Behaviour
Penny, William
2012-01-01
This paper presents a review of Bayesian models of brain and behaviour. We first review the basic principles of Bayesian inference. This is followed by descriptions of sampling and variational methods for approximate inference, and forward and backward recursions in time for inference in dynamical models. The review of behavioural models covers work in visual processing, sensory integration, sensorimotor integration, and collective decision making. The review of brain models covers a range of...
Bayesian Modeling of a Human MMORPG Player
Synnaeve, Gabriel
2010-01-01
This paper describes an application of Bayesian programming to the control of an autonomous avatar in a multiplayer role-playing game (the example is based on World of Warcraft). We model a particular task, which consists of choosing what to do and to select which target in a situation where allies and foes are present. We explain the model in Bayesian programming and show how we could learn the conditional probabilities from data gathered during human-played sessions.
Bayesian Modeling of a Human MMORPG Player
Synnaeve, Gabriel; Bessière, Pierre
2011-03-01
This paper describes an application of Bayesian programming to the control of an autonomous avatar in a multiplayer role-playing game (the example is based on World of Warcraft). We model a particular task, which consists of choosing what to do and to select which target in a situation where allies and foes are present. We explain the model in Bayesian programming and show how we could learn the conditional probabilities from data gathered during human-played sessions.
Bayesian Inference of Reticulate Phylogenies under the Multispecies Network Coalescent.
Wen, Dingqiao; Yu, Yun; Nakhleh, Luay
2016-05-01
The multispecies coalescent (MSC) is a statistical framework that models how gene genealogies grow within the branches of a species tree. The field of computational phylogenetics has witnessed an explosion in the development of methods for species tree inference under MSC, owing mainly to the accumulating evidence of incomplete lineage sorting in phylogenomic analyses. However, the evolutionary history of a set of genomes, or species, could be reticulate due to the occurrence of evolutionary processes such as hybridization or horizontal gene transfer. We report on a novel method for Bayesian inference of genome and species phylogenies under the multispecies network coalescent (MSNC). This framework models gene evolution within the branches of a phylogenetic network, thus incorporating reticulate evolutionary processes, such as hybridization, in addition to incomplete lineage sorting. As phylogenetic networks with different numbers of reticulation events correspond to points of different dimensions in the space of models, we devise a reversible-jump Markov chain Monte Carlo (RJMCMC) technique for sampling the posterior distribution of phylogenetic networks under MSNC. We implemented the methods in the publicly available, open-source software package PhyloNet and studied their performance on simulated and biological data. The work extends the reach of Bayesian inference to phylogenetic networks and enables new evolutionary analyses that account for reticulation. PMID:27144273
Bayesian inference for OPC modeling
Burbine, Andrew; Sturtevant, John; Fryer, David; Smith, Bruce W.
2016-03-01
The use of optical proximity correction (OPC) demands increasingly accurate models of the photolithographic process. Model building and inference techniques in the data science community have seen great strides in the past two decades which make better use of available information. This paper aims to demonstrate the predictive power of Bayesian inference as a method for parameter selection in lithographic models by quantifying the uncertainty associated with model inputs and wafer data. Specifically, the method combines the model builder's prior information about each modelling assumption with the maximization of each observation's likelihood as a Student's t-distributed random variable. Through the use of a Markov chain Monte Carlo (MCMC) algorithm, a model's parameter space is explored to find the most credible parameter values. During parameter exploration, the parameters' posterior distributions are generated by applying Bayes' rule, using a likelihood function and the a priori knowledge supplied. The MCMC algorithm used, an affine invariant ensemble sampler (AIES), is implemented by initializing many walkers which semiindependently explore the space. The convergence of these walkers to global maxima of the likelihood volume determine the parameter values' highest density intervals (HDI) to reveal champion models. We show that this method of parameter selection provides insights into the data that traditional methods do not and outline continued experiments to vet the method.
Bayesian analysis of volcanic eruptions
Ho, Chih-Hsiang
1990-10-01
The simple Poisson model generally gives a good fit to many volcanoes for volcanic eruption forecasting. Nonetheless, empirical evidence suggests that volcanic activity in successive equal time-periods tends to be more variable than a simple Poisson with constant eruptive rate. An alternative model is therefore examined in which eruptive rate(λ) for a given volcano or cluster(s) of volcanoes is described by a gamma distribution (prior) rather than treated as a constant value as in the assumptions of a simple Poisson model. Bayesian analysis is performed to link two distributions together to give the aggregate behavior of the volcanic activity. When the Poisson process is expanded to accomodate a gamma mixing distribution on λ, a consequence of this mixed (or compound) Poisson model is that the frequency distribution of eruptions in any given time-period of equal length follows the negative binomial distribution (NBD). Applications of the proposed model and comparisons between the generalized model and simple Poisson model are discussed based on the historical eruptive count data of volcanoes Mauna Loa (Hawaii) and Etna (Italy). Several relevant facts lead to the conclusion that the generalized model is preferable for practical use both in space and time.
BAYESIAN APPROACH OF DECISION PROBLEMS
Directory of Open Access Journals (Sweden)
DRAGOŞ STUPARU
2010-01-01
Full Text Available Management is nowadays a basic vector of economic development, a concept frequently used in our country as well as all over the world. Indifferently of the hierarchical level at which the managerial process is manifested, decision represents its essential moment, the supreme act of managerial activity. Its can be met in all fields of activity, practically having an unlimited degree of coverage, and in all the functions of management. It is common knowledge that the activity of any type of manger, no matter the hierarchical level he occupies, represents a chain of interdependent decisions, their aim being the elimination or limitation of the influence of disturbing factors that may endanger the achievement of predetermined objectives, and the quality of managerial decisions condition the progress and viability of any enterprise. Therefore, one of the principal characteristics of a successful manager is his ability to adopt the most optimal decisions of high quality. The quality of managerial decisions are conditioned by the manager’s general level of education and specialization, the manner in which they are preoccupied to assimilate the latest information and innovations in the domain of management’s theory and practice and the applying of modern managerial methods and techniques in the activity of management. We are presenting below the analysis of decision problems in hazardous conditions in terms of Bayesian theory – a theory that uses the probabilistic calculus.
Bayesian demography 250 years after Bayes.
Bijak, Jakub; Bryant, John
2016-01-01
Bayesian statistics offers an alternative to classical (frequentist) statistics. It is distinguished by its use of probability distributions to describe uncertain quantities, which leads to elegant solutions to many difficult statistical problems. Although Bayesian demography, like Bayesian statistics more generally, is around 250 years old, only recently has it begun to flourish. The aim of this paper is to review the achievements of Bayesian demography, address some misconceptions, and make the case for wider use of Bayesian methods in population studies. We focus on three applications: demographic forecasts, limited data, and highly structured or complex models. The key advantages of Bayesian methods are the ability to integrate information from multiple sources and to describe uncertainty coherently. Bayesian methods also allow for including additional (prior) information next to the data sample. As such, Bayesian approaches are complementary to many traditional methods, which can be productively re-expressed in Bayesian terms. PMID:26902889
Bayesian demography 250 years after Bayes.
Bijak, Jakub; Bryant, John
2016-01-01
Bayesian statistics offers an alternative to classical (frequentist) statistics. It is distinguished by its use of probability distributions to describe uncertain quantities, which leads to elegant solutions to many difficult statistical problems. Although Bayesian demography, like Bayesian statistics more generally, is around 250 years old, only recently has it begun to flourish. The aim of this paper is to review the achievements of Bayesian demography, address some misconceptions, and make the case for wider use of Bayesian methods in population studies. We focus on three applications: demographic forecasts, limited data, and highly structured or complex models. The key advantages of Bayesian methods are the ability to integrate information from multiple sources and to describe uncertainty coherently. Bayesian methods also allow for including additional (prior) information next to the data sample. As such, Bayesian approaches are complementary to many traditional methods, which can be productively re-expressed in Bayesian terms.
Directory of Open Access Journals (Sweden)
Feldhoff Pamela W
2006-03-01
Full Text Available Abstract Background The mental gland pheromone of male Plethodon salamanders contains two main protein components: a 22 kDa protein named Plethodon Receptivity Factor (PRF and a 7 kDa protein named Plethodon Modulating Factor (PMF, respectively. Each protein component individually has opposing effects on female courtship behavior, with PRF shortening and PMF lengthening courtship. In this study, we test the hypothesis that PRF or PMF individually activate vomeronasal neurons. The agmatine-uptake technique was used to visualize chemosensory neurons that were activated by each protein component individually. Results Vomeronasal neurons exposed to agmatine in saline did not demonstrate significant labeling. However, a population of vomeronasal neurons was labeled following exposure to either PRF or PMF. When expressed as a percent of control level labeled cells, PRF labeled more neurons than did PMF. These percentages for PRF and PMF, added together, parallel the percentage of labeled vomeronasal neurons when females are exposed to the whole pheromone. Conclusion This study suggests that two specific populations of female vomeronasal neurons are responsible for responding to each of the two components of the male pheromone mixture. These two neural populations, therefore, could express different receptors which, in turn, transmit different information to the brain, thus accounting for the different female behavior elicited by each pheromone component.
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Bonett Ronald M
2006-03-01
Full Text Available Abstract Background Habitat variation strongly influences the evolution of developmentally flexible traits, and may drive speciation and diversification. The plethodontid salamander Eurycea tynerensis is endemic to the geologically diverse Ozark Plateau of south-central North America, and comprises both strictly aquatic paedomorphic populations (achieving reproductive maturity while remaining in the larval form and more terrestrial metamorphic populations. The switch between developmental modes has occurred many times, but populations typically exhibit a single life history mode. This unique system offers an opportunity to study the specific ecological circumstances under which alternate developmental and life history modes evolve. We use phylogenetic independent contrasts to test for relationships between a key microhabitat feature (streambed sediment and this major life history polymorphism. Results We find streambed microstructure (sediment particle size, type and degree of sorting to be highly correlated with life-history mode. Eurycea tynerensis is paedomorphic in streams containing large chert gravel, but metamorphoses in nearby streams containing poorly sorted, clastic material such as sandstone or siltstone. Conclusion Deposits of large chert gravel create loosely associated streambeds, which provide access to subsurface water during dry summer months. Conversely, streambeds composed of more densely packed sandstone and siltstone sediments leave no subterranean refuge when surface water dries, presumably necessitating metamorphosis and use of terrestrial habitats. This represents a clear example of the relationship between microhabitat structure and evolution of a major developmental and life history trait, and has broad implications for the role of localized ecological conditions on larger-scale evolutionary processes.
Beta-ionone activates and bleaches visual pigment in salamander photoreceptors.
Isayama, Tomoki; McCabe England, S L; Crouch, R K; Zimmerman, A L; Makino, C L
2009-01-01
Vision begins with photoisomerization of 11-cis retinal to the all-trans conformation within the chromophore-binding pocket of opsin, leading to activation of a biochemical cascade. Release of all-trans retinal from the binding pocket curtails but does not fully quench the ability of opsin to activate transducin. All-trans retinal and some other analogs, such as beta-ionone, enhance opsin's activity, presumably on binding the empty chromophore-binding pocket. By recording from isolated salamander photoreceptors and from patches of rod outer segment membrane, we now show that high concentrations of beta-ionone suppressed circulating current in dark-adapted green-sensitive rods by inhibiting the cyclic nucleotide-gated channels. There were also decreases in circulating current and flash sensitivity, and accelerated flash response kinetics in dark-adapted blue-sensitive (BS) rods and cones, and in ultraviolet-sensitive cones, at concentrations too low to inhibit the channels. These effects persisted in BS rods even after incubation with 9-cis retinal to ensure complete regeneration of their visual pigment. After long exposures to high concentrations of beta-ionone, recovery was incomplete unless 9-cis retinal was given, indicating that visual pigment had been bleached. Therefore, we propose that beta-ionone activates and bleaches some types of visual pigments, mimicking the effects of light.
Temporal response of the tiger salamander (Ambystoma tigrinum to 3,000 years of climatic variation
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Long Webb
2005-09-01
Full Text Available Abstract Background Amphibians are sensitive indicators of environmental conditions and show measurable responses, such as changes in phenology, abundance and range limits to local changes in precipitation and temperature regimes. Amphibians offer unique opportunities to study the important ecological and evolutionary implications of responses in life history characteristics to climatic change. We analyzed a late-Holocene fossil record of the Tiger Salamander (Ambystoma tigrinum for evidence of population-level changes in body size and paedomorphosis to climatic change over the last 3000 years. Results We found a significant difference in body size index between paedomorphic and metamorphic individuals during the time interval dominated by the Medieval Warm Period. There is a consistent ratio of paedomorphic to metamorphic specimens through the entire 3000 years, demonstrating that not all life history characteristics of the population were significantly altered by changes in climate on this timescale. Conclusion The fossil record of Ambystoma tigrinum we used spans an ecologically relevant timescale appropriate for understanding population and community response to projected climatic change. The population-level responses we documented are concordant with expectations based on modern environmental studies, and yield insight into population-level patterns across hundreds of generations, especially the independence of different life history characteristics. These conclusions lead us to offer general predictions about the future response of this species based on likely scenarios of climatic warming in the Rocky Mountain region.
Soteropoulos, Diana L; Lance, Stacey L; Flynn, R Wesley; Scott, David E
2014-07-01
The creation of wetlands, such as urban and industrial ponds, has increased in recent decades, and these wetlands often become enriched in pollutants over time. One metal contaminant trapped in created wetlands is copper (Cu(2+)). Copper concentrations in sediments and overlying water may affect amphibian species that breed in created wetlands. The authors analyzed the Cu concentration in dried sediments from a contaminated wetland and the levels of aqueous Cu released after flooding the sediments with different volumes of water, mimicking low, medium, and high pond-filling events. Eggs and larvae of Ambystoma opacum Gravenhorst, a salamander that lays eggs on the sediments in dry pond beds that hatch on pond-filling, were exposed to a range of Cu concentrations that bracketed potential aqueous Cu levels in created wetlands. Embryo survival varied among clutches, but increased Cu levels did not affect embryo survival. At Cu concentrations of 500 µg/L or greater, however, embryos hatched earlier, and the aquatic larvae died shortly after hatching. Because Cu concentrations in sediments increase over time in created wetlands, even relatively tolerant species such as A. opacum may be affected by Cu levels in the posthatching environment. PMID:24729474
Physiological and morphological characterization of ganglion cells in the salamander retina.
Wang, Jing; Jacoby, Roy; Wu, Samuel M
2016-02-01
Retinal ganglion cells (RGCs) integrate visual information from the retina and transmit collective signals to the brain. A systematic investigation of functional and morphological characteristics of various types of RGCs is important to comprehensively understand how the visual system encodes and transmits information via various RGC pathways. This study evaluated both physiological and morphological properties of 67 RGCs in dark-adapted flat-mounted salamander retina by examining light-evoked cation and chloride current responses via voltage-clamp recordings and visualizing morphology by Lucifer yellow fluorescence with a confocal microscope. Six groups of RGCs were described: asymmetrical ON-OFF RGCs, symmetrical ON RGCs, OFF RGCs, and narrow-, medium- and wide-field ON-OFF RGCs. Dendritic field diameters of RGCs ranged 102-490 μm: narrow field (300 μm, 24%). Dendritic ramification patterns of RGCs agree with the sublamina A/B rule. 34% of RGCs were monostratified, 24% bistratified and 42% diffusely stratified. 70% of ON RGCs and OFF RGCs were monostratified. Wide-field RGCs were diffusely stratified. 82% of RGCs generated light-evoked ON-OFF responses, while 11% generated ON responses and 7% OFF responses. Response sensitivity analysis suggested that some RGCs obtained separated rod/cone bipolar cell inputs whereas others obtained mixed bipolar cell inputs. 25% of neurons in the RGC layer were displaced amacrine cells. Although more types may be defined by more refined classification criteria, this report is to incorporate more physiological properties into RGC classification. PMID:26731645
Cryptic sex? Estimates of genome exchange in unisexual mole salamanders (Ambystoma sp.).
Gibbs, H Lisle; Denton, Robert D
2016-06-01
Cryptic sex has been argued to explain the exceptional longevity of certain parthenogenetic vertebrate lineages, yet direct measurements of genetic exchange between sexual and apparently parthenogenetic forms are rare. Female unisexual mole salamanders (Ambystoma sp.) are the oldest known unisexual vertebrate lineage (~5 million years), and one hypothesis for their persistence is that allopolyploid female unisexuals periodically exchange haploid genomes 'genome exchange' during gynogenetic reproduction with males from sympatric sexual species. We test this hypothesis by using genome-specific microsatellite DNA markers to estimate the rates of genome exchange between sexual males and unisexual females in two ponds in NE Ohio. We also test the prediction that levels of gene flow should be higher for 'sympatric' (sexual males present) genomes in unisexuals compared to 'allopatric' (sexual males absent) unisexual genomes. We used a model testing framework in the coalescent-based program MIGRATE-N to compare models where unidirectional gene flow is present and absent between sexual species and unisexuals. As predicted, our results show higher levels of gene flow between sexuals and sympatric unisexual genomes compared to lower (likely artefactual) levels of gene flow between sexuals and allopatric unisexual genomes. Our results provide direct evidence that genome exchange between sexual and unisexual Ambystoma occurs and demonstrate that the magnitude depends on which sexual species are present. The relatively high levels of gene flow suggest that unisexuals must be at a selective advantage over sexual forms so as to avoid extinction due to genetic swamping through genome exchange. PMID:27100619
Bayesian tomographic reconstruction of microsystems
Salem, Sofia Fekih; Vabre, Alexandre; Mohammad-Djafari, Ali
2007-11-01
The microtomography by X ray transmission plays an increasingly dominating role in the study and the understanding of microsystems. Within this framework, an experimental setup of high resolution X ray microtomography was developed at CEA-List to quantify the physical parameters related to the fluids flow in microsystems. Several difficulties rise from the nature of experimental data collected on this setup: enhanced error measurements due to various physical phenomena occurring during the image formation (diffusion, beam hardening), and specificities of the setup (limited angle, partial view of the object, weak contrast). To reconstruct the object we must solve an inverse problem. This inverse problem is known to be ill-posed. It therefore needs to be regularized by introducing prior information. The main prior information we account for is that the object is composed of a finite known number of different materials distributed in compact regions. This a priori information is introduced via a Gauss-Markov field for the contrast distributions with a hidden Potts-Markov field for the class materials in the Bayesian estimation framework. The computations are done by using an appropriate Markov Chain Monte Carlo (MCMC) technique. In this paper, we present first the basic steps of the proposed algorithms. Then we focus on one of the main steps in any iterative reconstruction method which is the computation of forward and adjoint operators (projection and backprojection). A fast implementation of these two operators is crucial for the real application of the method. We give some details on the fast computation of these steps and show some preliminary results of simulations.
Computationally efficient Bayesian inference for inverse problems.
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Marzouk, Youssef M.; Najm, Habib N.; Rahn, Larry A.
2007-10-01
Bayesian statistics provides a foundation for inference from noisy and incomplete data, a natural mechanism for regularization in the form of prior information, and a quantitative assessment of uncertainty in the inferred results. Inverse problems - representing indirect estimation of model parameters, inputs, or structural components - can be fruitfully cast in this framework. Complex and computationally intensive forward models arising in physical applications, however, can render a Bayesian approach prohibitive. This difficulty is compounded by high-dimensional model spaces, as when the unknown is a spatiotemporal field. We present new algorithmic developments for Bayesian inference in this context, showing strong connections with the forward propagation of uncertainty. In particular, we introduce a stochastic spectral formulation that dramatically accelerates the Bayesian solution of inverse problems via rapid evaluation of a surrogate posterior. We also explore dimensionality reduction for the inference of spatiotemporal fields, using truncated spectral representations of Gaussian process priors. These new approaches are demonstrated on scalar transport problems arising in contaminant source inversion and in the inference of inhomogeneous material or transport properties. We also present a Bayesian framework for parameter estimation in stochastic models, where intrinsic stochasticity may be intermingled with observational noise. Evaluation of a likelihood function may not be analytically tractable in these cases, and thus several alternative Markov chain Monte Carlo (MCMC) schemes, operating on the product space of the observations and the parameters, are introduced.
Tactile length contraction as Bayesian inference.
Tong, Jonathan; Ngo, Vy; Goldreich, Daniel
2016-08-01
To perceive, the brain must interpret stimulus-evoked neural activity. This is challenging: The stochastic nature of the neural response renders its interpretation inherently uncertain. Perception would be optimized if the brain used Bayesian inference to interpret inputs in light of expectations derived from experience. Bayesian inference would improve perception on average but cause illusions when stimuli violate expectation. Intriguingly, tactile, auditory, and visual perception are all prone to length contraction illusions, characterized by the dramatic underestimation of the distance between punctate stimuli delivered in rapid succession; the origin of these illusions has been mysterious. We previously proposed that length contraction illusions occur because the brain interprets punctate stimulus sequences using Bayesian inference with a low-velocity expectation. A novel prediction of our Bayesian observer model is that length contraction should intensify if stimuli are made more difficult to localize. Here we report a tactile psychophysical study that tested this prediction. Twenty humans compared two distances on the forearm: a fixed reference distance defined by two taps with 1-s temporal separation and an adjustable comparison distance defined by two taps with temporal separation t ≤ 1 s. We observed significant length contraction: As t was decreased, participants perceived the two distances as equal only when the comparison distance was made progressively greater than the reference distance. Furthermore, the use of weaker taps significantly enhanced participants' length contraction. These findings confirm the model's predictions, supporting the view that the spatiotemporal percept is a best estimate resulting from a Bayesian inference process. PMID:27121574
Dimensionality reduction in Bayesian estimation algorithms
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G. W. Petty
2013-03-01
Full Text Available An idealized synthetic database loosely resembling 3-channel passive microwave observations of precipitation against a variable background is employed to examine the performance of a conventional Bayesian retrieval algorithm. For this dataset, algorithm performance is found to be poor owing to an irreconcilable conflict between the need to find matches in the dependent database versus the need to exclude inappropriate matches. It is argued that the likelihood of such conflicts increases sharply with the dimensionality of the observation space of real satellite sensors, which may utilize 9 to 13 channels to retrieve precipitation, for example. An objective method is described for distilling the relevant information content from N real channels into a much smaller number (M of pseudochannels while also regularizing the background (geophysical plus instrument noise component. The pseudochannels are linear combinations of the original N channels obtained via a two-stage principal component analysis of the dependent dataset. Bayesian retrievals based on a single pseudochannel applied to the independent dataset yield striking improvements in overall performance. The differences between the conventional Bayesian retrieval and reduced-dimensional Bayesian retrieval suggest that a major potential problem with conventional multichannel retrievals – whether Bayesian or not – lies in the common but often inappropriate assumption of diagonal error covariance. The dimensional reduction technique described herein avoids this problem by, in effect, recasting the retrieval problem in a coordinate system in which the desired covariance is lower-dimensional, diagonal, and unit magnitude.
Tactile length contraction as Bayesian inference.
Tong, Jonathan; Ngo, Vy; Goldreich, Daniel
2016-08-01
To perceive, the brain must interpret stimulus-evoked neural activity. This is challenging: The stochastic nature of the neural response renders its interpretation inherently uncertain. Perception would be optimized if the brain used Bayesian inference to interpret inputs in light of expectations derived from experience. Bayesian inference would improve perception on average but cause illusions when stimuli violate expectation. Intriguingly, tactile, auditory, and visual perception are all prone to length contraction illusions, characterized by the dramatic underestimation of the distance between punctate stimuli delivered in rapid succession; the origin of these illusions has been mysterious. We previously proposed that length contraction illusions occur because the brain interprets punctate stimulus sequences using Bayesian inference with a low-velocity expectation. A novel prediction of our Bayesian observer model is that length contraction should intensify if stimuli are made more difficult to localize. Here we report a tactile psychophysical study that tested this prediction. Twenty humans compared two distances on the forearm: a fixed reference distance defined by two taps with 1-s temporal separation and an adjustable comparison distance defined by two taps with temporal separation t ≤ 1 s. We observed significant length contraction: As t was decreased, participants perceived the two distances as equal only when the comparison distance was made progressively greater than the reference distance. Furthermore, the use of weaker taps significantly enhanced participants' length contraction. These findings confirm the model's predictions, supporting the view that the spatiotemporal percept is a best estimate resulting from a Bayesian inference process.
Individual organisms as units of analysis: Bayesian-clustering alternatives in population genetics.
Mank, Judith E; Avise, John C
2004-12-01
Population genetic analyses traditionally focus on the frequencies of alleles or genotypes in 'populations' that are delimited a priori. However, there are potential drawbacks of amalgamating genetic data into such composite attributes of assemblages of specimens: genetic information on individual specimens is lost or submerged as an inherent part of the analysis. A potential also exists for circular reasoning when a population's initial identification and subsequent genetic characterization are coupled. In principle, these problems are circumvented by some newer methods of population identification and individual assignment based on statistical clustering of specimen genotypes. Here we evaluate a recent method in this genre--Bayesian clustering--using four genotypic data sets involving different types of molecular markers in non-model organisms from nature. As expected, measures of population genetic structure (F(ST) and phiST) tended to be significantly greater in Bayesian a posteriori data treatments than in analyses where populations were delimited a priori. In the four biological contexts examined, which involved both geographic population structures and hybrid zones, Bayesian clustering was able to recover differentiated populations, and Bayesian assignments were able to identify likely population sources of specific individuals.
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Ahmed A. Siddig
2015-05-01
Full Text Available Herpetologists and conservation biologists frequently use convenient and cost-effective, but less accurate, abundance indices (e.g., number of individuals collected under artificial cover boards or during natural objects surveys in lieu of more accurate, but costly and destructive, population size estimators to detect and monitor size, state, and trends of amphibian populations. Although there are advantages and disadvantages to each approach, reliable use of abundance indices requires that they be calibrated with accurate population estimators. Such calibrations, however, are rare. The red back salamander, Plethodon cinereus, is an ecologically useful indicator species of forest dynamics, and accurate calibration of indices of salamander abundance could increase the reliability of abundance indices used in monitoring programs. We calibrated abundance indices derived from surveys of P. cinereus under artificial cover boards or natural objects with a more accurate estimator of their population size in a New England forest. Average densities/m2 and capture probabilities of P. cinereus under natural objects or cover boards in independent, replicate sites at the Harvard Forest (Petersham, Massachusetts, USA were similar in stands dominated by Tsuga canadensis (eastern hemlock and deciduous hardwood species (predominantly Quercus rubra [red oak] and Acer rubrum [red maple]. The abundance index based on salamanders surveyed under natural objects was significantly associated with density estimates of P. cinereus derived from depletion (removal surveys, but underestimated true density by 50%. In contrast, the abundance index based on cover-board surveys overestimated true density by a factor of 8 and the association between the cover-board index and the density estimates was not statistically significant. We conclude that when calibrated and used appropriately, some abundance indices may provide cost-effective and reliable measures of P. cinereus
Levis, Nicholas A; Johnson, Jarrett R
2015-07-01
Glyphosate-based herbicides are the number one pesticide in the United States and are used commonly around the world. Understanding the affects of glyphosate-based herbicides on non-target wildlife, for example amphibians, is critical for evaluation of regulations pertaining to the use of such herbicides. Additionally, it is important to understand how variation in biotic and abiotic environmental conditions, such as UV-B light regime, could potentially affect how glyphosate-based herbicides interact with non-target species. This study used artificial pond mesocosms to identify the effects of generic glyphosate-based herbicide (GLY-4 Plus) on mortality, cellular immune response, body size, and morphological plasticity of larvae of the spotted salamander (Ambystoma maculatum) under conditions that reflect moderate (UV(M)) and low (UV(L)) UV-B light regimes. Survival within a given UV-B level was unaffected by herbicide presence or absence. However, when herbicide was present, survival varied between UV-B levels with higher survival in UV(M) conditions. Herbicide presence in the UV(M) treatments also decreased body size and reduced cellular immune response. In the UV(L) treatments, the presence of herbicide increased body size and affected tail morphology. Finally, in the absence of herbicide, body size and cellular immune response were higher in UV(M) treatments compared to UV(L) treatments. Thus, the effects of herbicide on salamander fitness were dependent on UV-B level. As anthropogenic habitat modifications continue to alter landscapes that contain amphibian breeding ponds, salamanders may increasingly find themselves in locations with reduced canopy cover and increased levels of UV light. Our findings suggest that the probability of surviving exposure to the glyphosate-based herbicide used in this study may be elevated in more open canopy ponds, but the effects on other components of fitness may be varied and unexpected. PMID:25794558
JULIO A LEMOS-ESPINAL; Smith, Geoffrey R.; Guillermo A. Woolrich-Piña; Raymundo Montoya-Ayala
2015-01-01
Several species of salamander in the genus Ambystoma occur in the mountains surrounding Mexico City and are considered at risk of extinction. However, little is known about their ecology and natural history. The Toluca Stream Siredon (Ambystoma rivulare) is classified as “Data Deficient” by the IUCN, and considered “Threatened” under Mexican law. From October 2013 to September 2014, we examined the diet of larval A. rivulare from a stream on the Volcán Nevado de Toluca in Mexico to provide in...
Bayesian Methods for Radiation Detection and Dosimetry
Groer, Peter G
2002-01-01
We performed work in three areas: radiation detection, external and internal radiation dosimetry. In radiation detection we developed Bayesian techniques to estimate the net activity of high and low activity radioactive samples. These techniques have the advantage that the remaining uncertainty about the net activity is described by probability densities. Graphs of the densities show the uncertainty in pictorial form. Figure 1 below demonstrates this point. We applied stochastic processes for a method to obtain Bayesian estimates of 222Rn-daughter products from observed counting rates. In external radiation dosimetry we studied and developed Bayesian methods to estimate radiation doses to an individual with radiation induced chromosome aberrations. We analyzed chromosome aberrations after exposure to gammas and neutrons and developed a method for dose-estimation after criticality accidents. The research in internal radiation dosimetry focused on parameter estimation for compartmental models from observed comp...
Adaptive approximate Bayesian computation for complex models
Lenormand, Maxime; Deffuant, Guillaume
2011-01-01
Approximate Bayesian computation (ABC) is a family of computational techniques in Bayesian statistics. These techniques allow to fit a model to data without relying on the computation of the model likelihood. They instead require to simulate a large number of times the model to be fitted. A number of refinements to the original rejection-based ABC scheme have been proposed, including the sequential improvement of posterior distributions. This technique allows to decrease the number of model simulations required, but it still presents several shortcomings which are particularly problematic for costly to simulate complex models. We here provide a new algorithm to perform adaptive approximate Bayesian computation, which is shown to perform better on both a toy example and a complex social model.
Learning Bayesian Networks from Correlated Data
Bae, Harold; Monti, Stefano; Montano, Monty; Steinberg, Martin H.; Perls, Thomas T.; Sebastiani, Paola
2016-05-01
Bayesian networks are probabilistic models that represent complex distributions in a modular way and have become very popular in many fields. There are many methods to build Bayesian networks from a random sample of independent and identically distributed observations. However, many observational studies are designed using some form of clustered sampling that introduces correlations between observations within the same cluster and ignoring this correlation typically inflates the rate of false positive associations. We describe a novel parameterization of Bayesian networks that uses random effects to model the correlation within sample units and can be used for structure and parameter learning from correlated data without inflating the Type I error rate. We compare different learning metrics using simulations and illustrate the method in two real examples: an analysis of genetic and non-genetic factors associated with human longevity from a family-based study, and an example of risk factors for complications of sickle cell anemia from a longitudinal study with repeated measures.
Bayesian Fusion of Multi-Band Images
Wei, Qi; Tourneret, Jean-Yves
2013-01-01
In this paper, a Bayesian fusion technique for remotely sensed multi-band images is presented. The observed images are related to the high spectral and high spatial resolution image to be recovered through physical degradations, e.g., spatial and spectral blurring and/or subsampling defined by the sensor characteristics. The fusion problem is formulated within a Bayesian estimation framework. An appropriate prior distribution exploiting geometrical consideration is introduced. To compute the Bayesian estimator of the scene of interest from its posterior distribution, a Markov chain Monte Carlo algorithm is designed to generate samples asymptotically distributed according to the target distribution. To efficiently sample from this high-dimension distribution, a Hamiltonian Monte Carlo step is introduced in the Gibbs sampling strategy. The efficiency of the proposed fusion method is evaluated with respect to several state-of-the-art fusion techniques. In particular, low spatial resolution hyperspectral and mult...
Bayesian Image Reconstruction Based on Voronoi Diagrams
Cabrera, G F; Hitschfeld, N
2007-01-01
We present a Bayesian Voronoi image reconstruction technique (VIR) for interferometric data. Bayesian analysis applied to the inverse problem allows us to derive the a-posteriori probability of a novel parameterization of interferometric images. We use a variable Voronoi diagram as our model in place of the usual fixed pixel grid. A quantization of the intensity field allows us to calculate the likelihood function and a-priori probabilities. The Voronoi image is optimized including the number of polygons as free parameters. We apply our algorithm to deconvolve simulated interferometric data. Residuals, restored images and chi^2 values are used to compare our reconstructions with fixed grid models. VIR has the advantage of modeling the image with few parameters, obtaining a better image from a Bayesian point of view.
Variational Bayesian Inference of Line Spectra
DEFF Research Database (Denmark)
Badiu, Mihai Alin; Hansen, Thomas Lundgaard; Fleury, Bernard Henri
2016-01-01
In this paper, we address the fundamental problem of line spectral estimation in a Bayesian framework. We target model order and parameter estimation via variational inference in a probabilistic model in which the frequencies are continuous-valued, i.e., not restricted to a grid; and the coeffici......In this paper, we address the fundamental problem of line spectral estimation in a Bayesian framework. We target model order and parameter estimation via variational inference in a probabilistic model in which the frequencies are continuous-valued, i.e., not restricted to a grid......; and the coefficients are governed by a Bernoulli-Gaussian prior model turning model order selection into binary sequence detection. Unlike earlier works which retain only point estimates of the frequencies, we undertake a more complete Bayesian treatment by estimating the posterior probability density functions (pdfs...
Event generator tuning using Bayesian optimization
Ilten, Philip; Yang, Yunjie
2016-01-01
Monte Carlo event generators contain a large number of parameters that must be determined by comparing the output of the generator with experimental data. Generating enough events with a fixed set of parameter values to enable making such a comparison is extremely CPU intensive, which prohibits performing a simple brute-force grid-based tuning of the parameters. Bayesian optimization is a powerful method designed for such black-box tuning applications. In this article, we show that Monte Carlo event generator parameters can be accurately obtained using Bayesian optimization and minimal expert-level physics knowledge. A tune of the PYTHIA 8 event generator using $e^+e^-$ events, where 20 parameters are optimized, can be run on a modern laptop in just two days. Combining the Bayesian optimization approach with expert knowledge should enable producing better tunes in the future, by making it faster and easier to study discrepancies between Monte Carlo and experimental data.
Hessian PDF reweighting meets the Bayesian methods
Paukkunen, Hannu
2014-01-01
We discuss the Hessian PDF reweighting - a technique intended to estimate the effects that new measurements have on a set of PDFs. The method stems straightforwardly from considering new data in a usual $\\chi^2$-fit and it naturally incorporates also non-zero values for the tolerance, $\\Delta\\chi^2>1$. In comparison to the contemporary Bayesian reweighting techniques, there is no need to generate large ensembles of PDF Monte-Carlo replicas, and the observables need to be evaluated only with the central and the error sets of the original PDFs. In spite of the apparently rather different methodologies, we find that the Hessian and the Bayesian techniques are actually equivalent if the $\\Delta\\chi^2$ criterion is properly included to the Bayesian likelihood function that is a simple exponential.
A Large Sample Study of the Bayesian Bootstrap
Lo, Albert Y.
1987-01-01
An asymptotic justification of the Bayesian bootstrap is given. Large-sample Bayesian bootstrap probability intervals for the mean, the variance and bands for the distribution, the smoothed density and smoothed rate function are also provided.
AIC, BIC, Bayesian evidence against the interacting dark energy model
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Szydłowski, Marek, E-mail: marek.szydlowski@uj.edu.pl [Astronomical Observatory, Jagiellonian University, Orla 171, 30-244, Kraków (Poland); Mark Kac Complex Systems Research Centre, Jagiellonian University, Reymonta 4, 30-059, Kraków (Poland); Krawiec, Adam, E-mail: adam.krawiec@uj.edu.pl [Institute of Economics, Finance and Management, Jagiellonian University, Łojasiewicza 4, 30-348, Kraków (Poland); Mark Kac Complex Systems Research Centre, Jagiellonian University, Reymonta 4, 30-059, Kraków (Poland); Kurek, Aleksandra, E-mail: alex@oa.uj.edu.pl [Astronomical Observatory, Jagiellonian University, Orla 171, 30-244, Kraków (Poland); Kamionka, Michał, E-mail: kamionka@astro.uni.wroc.pl [Astronomical Institute, University of Wrocław, ul. Kopernika 11, 51-622, Wrocław (Poland)
2015-01-14
Recent astronomical observations have indicated that the Universe is in a phase of accelerated expansion. While there are many cosmological models which try to explain this phenomenon, we focus on the interacting ΛCDM model where an interaction between the dark energy and dark matter sectors takes place. This model is compared to its simpler alternative—the ΛCDM model. To choose between these models the likelihood ratio test was applied as well as the model comparison methods (employing Occam’s principle): the Akaike information criterion (AIC), the Bayesian information criterion (BIC) and the Bayesian evidence. Using the current astronomical data: type Ia supernova (Union2.1), h(z), baryon acoustic oscillation, the Alcock–Paczynski test, and the cosmic microwave background data, we evaluated both models. The analyses based on the AIC indicated that there is less support for the interacting ΛCDM model when compared to the ΛCDM model, while those based on the BIC indicated that there is strong evidence against it in favor of the ΛCDM model. Given the weak or almost non-existing support for the interacting ΛCDM model and bearing in mind Occam’s razor we are inclined to reject this model.
AIC, BIC, Bayesian evidence against the interacting dark energy model
Energy Technology Data Exchange (ETDEWEB)
Szydlowski, Marek [Jagiellonian University, Astronomical Observatory, Krakow (Poland); Jagiellonian University, Mark Kac Complex Systems Research Centre, Krakow (Poland); Krawiec, Adam [Jagiellonian University, Institute of Economics, Finance and Management, Krakow (Poland); Jagiellonian University, Mark Kac Complex Systems Research Centre, Krakow (Poland); Kurek, Aleksandra [Jagiellonian University, Astronomical Observatory, Krakow (Poland); Kamionka, Michal [University of Wroclaw, Astronomical Institute, Wroclaw (Poland)
2015-01-01
Recent astronomical observations have indicated that the Universe is in a phase of accelerated expansion. While there are many cosmological models which try to explain this phenomenon, we focus on the interacting ΛCDM model where an interaction between the dark energy and dark matter sectors takes place. This model is compared to its simpler alternative - the ΛCDM model. To choose between these models the likelihood ratio test was applied as well as the model comparison methods (employing Occam's principle): the Akaike information criterion (AIC), the Bayesian information criterion (BIC) and the Bayesian evidence. Using the current astronomical data: type Ia supernova (Union2.1), h(z), baryon acoustic oscillation, the Alcock- Paczynski test, and the cosmic microwave background data, we evaluated both models. The analyses based on the AIC indicated that there is less support for the interacting ΛCDM model when compared to the ΛCDM model, while those based on the BIC indicated that there is strong evidence against it in favor of the ΛCDM model. Given the weak or almost non-existing support for the interacting ΛCDM model and bearing in mind Occam's razor we are inclined to reject this model. (orig.)
Bayesian statistic methods and theri application in probabilistic simulation models
Directory of Open Access Journals (Sweden)
Sergio Iannazzo
2007-03-01
Full Text Available Bayesian statistic methods are facing a rapidly growing level of interest and acceptance in the field of health economics. The reasons of this success are probably to be found on the theoretical fundaments of the discipline that make these techniques more appealing to decision analysis. To this point should be added the modern IT progress that has developed different flexible and powerful statistical software framework. Among them probably one of the most noticeably is the BUGS language project and its standalone application for MS Windows WinBUGS. Scope of this paper is to introduce the subject and to show some interesting applications of WinBUGS in developing complex economical models based on Markov chains. The advantages of this approach reside on the elegance of the code produced and in its capability to easily develop probabilistic simulations. Moreover an example of the integration of bayesian inference models in a Markov model is shown. This last feature let the analyst conduce statistical analyses on the available sources of evidence and exploit them directly as inputs in the economic model.
Bayesian approach in MN low dose of radiation counting
International Nuclear Information System (INIS)
The Micronucleus assay in lymphocytes is a well established technique for the assessment of genetic damage induced by ionizing radiation. Due to the presence of a natural background of MN the net MN is obtained by subtracting this value to the gross value. When very low doses of radiation are given the induced MN is close even lower than the predetermined background value. Furthermore, the damage distribution induced by the radiation follows a Poisson probability distribution. These two facts pose a difficult task to obtain the net counting rate in the exposed situations. It is possible to overcome this problem using a bayesian approach, in which the selection of a priori distributions for the background and net counting rate plays an important role. In the present work we make a detailed analysed using bayesian theory to infer the net counting rate in two different situations: a) when the background is known for an individual sample, using exact value value for the background and Jeffreys prior for the net counting rate, and b) when the background is not known and we make use of a population background distribution as background prior function and constant prior for the net counting rate. (Author)
Length Scales in Bayesian Automatic Adaptive Quadrature
Directory of Open Access Journals (Sweden)
Adam Gh.
2016-01-01
Full Text Available Two conceptual developments in the Bayesian automatic adaptive quadrature approach to the numerical solution of one-dimensional Riemann integrals [Gh. Adam, S. Adam, Springer LNCS 7125, 1–16 (2012] are reported. First, it is shown that the numerical quadrature which avoids the overcomputing and minimizes the hidden floating point loss of precision asks for the consideration of three classes of integration domain lengths endowed with specific quadrature sums: microscopic (trapezoidal rule, mesoscopic (Simpson rule, and macroscopic (quadrature sums of high algebraic degrees of precision. Second, sensitive diagnostic tools for the Bayesian inference on macroscopic ranges, coming from the use of Clenshaw-Curtis quadrature, are derived.
Bayesian estimation and tracking a practical guide
Haug, Anton J
2012-01-01
A practical approach to estimating and tracking dynamic systems in real-worl applications Much of the literature on performing estimation for non-Gaussian systems is short on practical methodology, while Gaussian methods often lack a cohesive derivation. Bayesian Estimation and Tracking addresses the gap in the field on both accounts, providing readers with a comprehensive overview of methods for estimating both linear and nonlinear dynamic systems driven by Gaussian and non-Gaussian noices. Featuring a unified approach to Bayesian estimation and tracking, the book emphasizes the derivation
Bayesian Optimisation Algorithm for Nurse Scheduling
Li, Jingpeng
2008-01-01
Our research has shown that schedules can be built mimicking a human scheduler by using a set of rules that involve domain knowledge. This chapter presents a Bayesian Optimization Algorithm (BOA) for the nurse scheduling problem that chooses such suitable scheduling rules from a set for each nurses assignment. Based on the idea of using probabilistic models, the BOA builds a Bayesian network for the set of promising solutions and samples these networks to generate new candidate solutions. Computational results from 52 real data instances demonstrate the success of this approach. It is also suggested that the learning mechanism in the proposed algorithm may be suitable for other scheduling problems.
A Bayesian Analysis of Spectral ARMA Model
Directory of Open Access Journals (Sweden)
Manoel I. Silvestre Bezerra
2012-01-01
Full Text Available Bezerra et al. (2008 proposed a new method, based on Yule-Walker equations, to estimate the ARMA spectral model. In this paper, a Bayesian approach is developed for this model by using the noninformative prior proposed by Jeffreys (1967. The Bayesian computations, simulation via Markov Monte Carlo (MCMC is carried out and characteristics of marginal posterior distributions such as Bayes estimator and confidence interval for the parameters of the ARMA model are derived. Both methods are also compared with the traditional least squares and maximum likelihood approaches and a numerical illustration with two examples of the ARMA model is presented to evaluate the performance of the procedures.
A Bayesian Concept Learning Approach to Crowdsourcing
DEFF Research Database (Denmark)
Viappiani, Paolo Renato; Zilles, Sandra; Hamilton, Howard J.;
2011-01-01
We develop a Bayesian approach to concept learning for crowdsourcing applications. A probabilistic belief over possible concept definitions is maintained and updated according to (noisy) observations from experts, whose behaviors are modeled using discrete types. We propose recommendation...... techniques, inference methods, and query selection strategies to assist a user charged with choosing a configuration that satisfies some (partially known) concept. Our model is able to simultaneously learn the concept definition and the types of the experts. We evaluate our model with simulations, showing...... that our Bayesian strategies are effective even in large concept spaces with many uninformative experts....
International Nuclear Information System (INIS)
Disease is among the suspected causes of amphibian population declines, and an iridovirus and a chytrid fungus are the primary pathogens associated with amphibian mortalities. Ambystoma tigrinum virus (ATV) and a closely related strain, Regina ranavirus (RRV), are implicated in salamander die-offs in Arizona and Canada, respectively. We report the complete sequence of the ATV genome and partial sequence of the RRV genome. Sequence analysis of the ATV/RRV genomes showed marked similarity to other ranaviruses, including tiger frog virus (TFV) and frog virus 3 (FV3), the type virus of the genus Ranavirus (family Iridoviridae), as well as more distant relationships to lymphocystis disease virus, Chilo iridescent virus, and infectious spleen and kidney necrosis virus. Putative open reading frames (ORFs) in the ATV sequence identified 24 genes that appear to control virus replication and block antiviral responses. In addition, >50 other putative genes, homologous to ORFs in other iridoviral genomes but of unknown function, were also identified. Sequence comparison performed by dot plot analysis between ATV and itself revealed a conserved 14-bp palindromic repeat within most intragenic regions. Dot plot analysis of ATV vs RRV sequences identified several polymorphisms between the two isolates. Finally, a comparison of ATV and TFV genomic sequences identified genomic rearrangements consistent with the high recombination frequency of iridoviruses. Given the adverse effects that ranavirus infections have on amphibian and fish populations, ATV/RRV sequence information will allow the design of better diagnostic probes for identifying ranavirus infections and extend our understanding of molecular events in ranavirus-infected cells
Dynamics and thermal sensitivity of ballistic and non-ballistic feeding in salamanders.
Deban, Stephen M; Scales, Jeffrey A
2016-02-01
Low temperature reduces the performance of muscle-powered movements, but in movements powered by elastic recoil mechanisms, this effect can be mitigated and performance can be increased. To better understand the morphological basis of high performance and thermal robustness of elastically powered movements, we compared feeding dynamics at a range of temperatures (5-25°C) in two species of terrestrial plethodontid salamanders, Plethodon metcalfi and Ensatina eschscholtzii, which differ in tongue muscle architecture and the mechanism of tongue projection. We found that Ensatina is capable of ballistic projection with a mean muscle mass-specific power of 2100 W kg(-1), revealing an elastic mechanism. Plethodon, in contrast, projected its tongue non-ballistically with a mean power of only 18 W kg(-1), indicating it is muscle powered. Ensatina projected its tongue significantly farther than Plethodon and with dynamics that had significantly lower thermal sensitivity at temperatures below 15°C. These performance differences were correlated with morphological differences, namely elongated collagenous aponeuroses in the projector muscle of Ensatina as compared with Plethodon, which are likely the site of energy storage, and the absence in Ensatina of projector muscle fibers attaching to the tongue skeleton that allows projection to be truly ballistic. These findings demonstrate that, in these otherwise similar species, the presence in one species of elaborated connective tissue in series with myofibers confers not only 10-fold greater absolute performance but also greater thermal robustness of performance. We conclude that changes in muscle and connective tissue architecture are sufficient to alter significantly the mechanics, performance and thermal robustness of musculoskeletal systems.
Comparison of the Bayesian and Frequentist Approach to the Statistics
Hakala, Michal
2015-01-01
The Thesis deals with introduction to Bayesian statistics and comparing Bayesian approach with frequentist approach to statistics. Bayesian statistics is modern branch of statistics which provides an alternative comprehensive theory to the frequentist approach. Bayesian concepts provides solution for problems not being solvable by frequentist theory. In the thesis are compared definitions, concepts and quality of statistical inference. The main interest is focused on a point estimation, an in...
A Fast Iterative Bayesian Inference Algorithm for Sparse Channel Estimation
DEFF Research Database (Denmark)
Pedersen, Niels Lovmand; Manchón, Carles Navarro; Fleury, Bernard Henri
2013-01-01
representation of the Bessel K probability density function; a highly efficient, fast iterative Bayesian inference method is then applied to the proposed model. The resulting estimator outperforms other state-of-the-art Bayesian and non-Bayesian estimators, either by yielding lower mean squared estimation error...
A default Bayesian hypothesis test for ANOVA designs
R. Wetzels; R.P.P.P. Grasman; E.J. Wagenmakers
2012-01-01
This article presents a Bayesian hypothesis test for analysis of variance (ANOVA) designs. The test is an application of standard Bayesian methods for variable selection in regression models. We illustrate the effect of various g-priors on the ANOVA hypothesis test. The Bayesian test for ANOVA desig
A Gentle Introduction to Bayesian Analysis : Applications to Developmental Research
Van de Schoot, Rens; Kaplan, David; Denissen, Jaap; Asendorpf, Jens B.; Neyer, Franz J.; van Aken, Marcel A G
2014-01-01
Bayesian statistical methods are becoming ever more popular in applied and fundamental research. In this study a gentle introduction to Bayesian analysis is provided. It is shown under what circumstances it is attractive to use Bayesian estimation, and how to interpret properly the results. First, t
Bayesian Just-So Stories in Psychology and Neuroscience
Bowers, Jeffrey S.; Davis, Colin J.
2012-01-01
According to Bayesian theories in psychology and neuroscience, minds and brains are (near) optimal in solving a wide range of tasks. We challenge this view and argue that more traditional, non-Bayesian approaches are more promising. We make 3 main arguments. First, we show that the empirical evidence for Bayesian theories in psychology is weak.…
Directory of Open Access Journals (Sweden)
Josep Fortuny
Full Text Available Biting is an integral feature of the feeding mechanism for aquatic and terrestrial salamanders to capture, fix or immobilize elusive or struggling prey. However, little information is available on how it works and the functional implications of this biting system in amphibians although such approaches might be essential to understand feeding systems performed by early tetrapods. Herein, the skull biomechanics of the Chinese giant salamander, Andrias davidianus is investigated using 3D finite element analysis. The results reveal that the prey contact position is crucial for the structural performance of the skull, which is probably related to the lack of a bony bridge between the posterior end of the maxilla and the anterior quadrato-squamosal region. Giant salamanders perform asymmetrical strikes. These strikes are unusual and specialized behavior but might indeed be beneficial in such sit-and-wait or ambush-predators to capture laterally approaching prey. However, once captured by an asymmetrical strike, large, elusive and struggling prey have to be brought to the anterior jaw region to be subdued by a strong bite. Given their basal position within extant salamanders and their "conservative" morphology, cryptobranchids may be useful models to reconstruct the feeding ecology and biomechanics of different members of early tetrapods and amphibians, with similar osteological and myological constraints.
Sun, Jingyan; Geng, Xiaofang; Guo, Jianlin; Zang, Xiayan; Li, Pengfei; Li, Deming; Xu, Cunshuan
2016-09-01
Animal skin that directly interfaces with the external environment has developed diverse adaptive functions to a variety of ecological conditions laden with pathogenic infection and physical harm. Amphibians exhibit various adaptations related to their "incomplete" shift from the aquatic to the terrestrial habitat. Therefore, it is very necessary to explore the molecular basis of skin function and adaptation in amphibians. Currently, the studies on the molecular mechanisms of skin functions in anuran amphibians have been reported, but in urodele amphibians are rare. This study identified the skin proteomes of Chinese fire-bellied newt Cynops orientalis by a proteomic method, and compared the results to the skin proteomes of Chinese giant salamander Andrias davidianus obtained previously. A total of 452 proteins were identified in the newt skin by MALDI-TOF/MS, and functional annotation results by DAVID analysis showed that special functions such as wound healing, immune response, defense and respiration, were significantly enriched. Comparison results showed that the two species had a great difference in the aspects of protein kinds and abundance, and the highly expressed proteins may tightly correlate with living conditions. Moreover, the newt skin might have stronger immunity, but weaker respiration than the giant salamander skin to adapt to various living environments. This research provides a molecular basis for further studies on amphibian skin function and adaptation.
Baxter, Leilan; Brain, Richard A; Hosmer, Alan J; Nema, Mohini; Müller, Kirsten M; Solomon, Keith R; Hanson, Mark L
2015-11-01
Embryonic growth of the yellow-spotted salamander (Ambystoma maculatum) is enhanced by the presence of the green alga Oophila amblystomatis, in the egg capsule. To further assess potential impacts of herbicides on this relationship, A. maculatum egg masses were exposed to atrazine (0-338 μg/L) until hatching (up to 66 days). Exposure to atrazine reduced PSII yield of the symbiotic algae in a concentration-dependent manner, but did not significantly affect visible algal growth or any metrics associated with salamander development. Algal cells were also cultured in the laboratory for toxicity testing. In the 96-h growth inhibition test (0-680 μg/L), ECx values were generally greater than those reported for standard algal test species. Complete recovery of growth rates occurred within 96-h of transferring cells to untreated media. Overall, development of A. maculatum embryos was not affected by exposure to atrazine at concentrations and durations exceeding those found in the environment.
Pietsch, P; Schneider, C W
1990-08-01
A wide variety of visual functions show increases attributable to binocularity, and the question pursued here was whether a second eye enhances the visually stimulated skin blanching reaction of the larval salamander. Dermal melanin spots (produced by the aggregations of melanosomes within dermal melanophores and which contract or expand to lighten or darken the skin) were measured in eyeless (controls), one-eyed and two-eyed Ambystoma punctatum larvae after chronic adaptation of the subjects to a white background (i.e., stimulus conditions for maximum blanching). The eyeless subjects showed no blanching (thus remained dark) in white cups, and they exhibited melanin spots 7 or 8 times the size of those of the other two groups. All one-eyed or two-eyed subjects exhibited blanching reactions; planometric comparison revealed a significantly larger melanin spot area for one-eyed than for two-eyed animals; i.e., the binocular condition permitted greater contraction of the pigment spots than did the monocular condition. Analytical data compared favorably with independently ascertained pigmentation indices. The results indicate that a second eye quantitatively elevates the blanching maximum of a larval salamander.
Directory of Open Access Journals (Sweden)
Jessica Wooten
2011-12-01
Full Text Available The discovery and subsequent description of cryptic biodiversity is often challenging, especially for groups that have undergone rapid lineage accumulation in the relatively recent past. Even without formal descriptions, understanding genetic diversity patterns as they relate to underlying ecological or historical processes can be important for conservation. The dusky salamanders of the genus Desmognathus, with 20 described species, comprise the second largest genus of plethodontid salamanders in the eastern United States. However, due to the presence of high genetic diversity and relatively few morphological synapomorphies, the number of species is likely to increase. For the three nominal species within the D. quadramaculatus species complex, including D. quadramaculatus, D. folkertsi, and D. marmoratus, we used a portion of the mitochondrial genome and nuclear markers in the form of amplified fragment length polymorphisms (AFLP to uncover spatial patterns of genetic diversity. Within D. quadramaculatus and D. marmoratus, we uncovered four well-supported lineages with the mitochondrial sequences; phylogeographic patterns were not congruent with the AFLP data. Both sets of markers identified a clear isolation by stream distance. Using multiple regressions, we found that historical river drainages and terrestrial ecoregions explained the phylogeographic patterning we observed for D. quadramaculatus.
Sun, Jingyan; Geng, Xiaofang; Guo, Jianlin; Zang, Xiayan; Li, Pengfei; Li, Deming; Xu, Cunshuan
2016-09-01
Animal skin that directly interfaces with the external environment has developed diverse adaptive functions to a variety of ecological conditions laden with pathogenic infection and physical harm. Amphibians exhibit various adaptations related to their "incomplete" shift from the aquatic to the terrestrial habitat. Therefore, it is very necessary to explore the molecular basis of skin function and adaptation in amphibians. Currently, the studies on the molecular mechanisms of skin functions in anuran amphibians have been reported, but in urodele amphibians are rare. This study identified the skin proteomes of Chinese fire-bellied newt Cynops orientalis by a proteomic method, and compared the results to the skin proteomes of Chinese giant salamander Andrias davidianus obtained previously. A total of 452 proteins were identified in the newt skin by MALDI-TOF/MS, and functional annotation results by DAVID analysis showed that special functions such as wound healing, immune response, defense and respiration, were significantly enriched. Comparison results showed that the two species had a great difference in the aspects of protein kinds and abundance, and the highly expressed proteins may tightly correlate with living conditions. Moreover, the newt skin might have stronger immunity, but weaker respiration than the giant salamander skin to adapt to various living environments. This research provides a molecular basis for further studies on amphibian skin function and adaptation. PMID:27343457
A Bayesian stochastic frontier analysis of Chinese fossil-fuel electricity generation companies
International Nuclear Information System (INIS)
This paper analyses the technical efficiency of Chinese fossil-fuel electricity generation companies from 1999 to 2011, using a Bayesian stochastic frontier model. The results reveal that efficiency varies among the fossil-fuel electricity generation companies that were analysed. We also focus on the factors of size, location, government ownership and mixed sources of electricity generation for the fossil-fuel electricity generation companies, and also examine their effects on the efficiency of these companies. Policy implications are derived. - Highlights: • We analyze the efficiency of 27 quoted Chinese fossil-fuel electricity generation companies during 1999–2011. • We adopt a Bayesian stochastic frontier model taking into consideration the identified heterogeneity. • With reform background in Chinese energy industry, we propose four hypotheses and check their influence on efficiency. • Big size, coastal location, government control and hydro energy sources all have increased costs
Jones, Matt; Love, Bradley C
2011-08-01
The prominence of Bayesian modeling of cognition has increased recently largely because of mathematical advances in specifying and deriving predictions from complex probabilistic models. Much of this research aims to demonstrate that cognitive behavior can be explained from rational principles alone, without recourse to psychological or neurological processes and representations. We note commonalities between this rational approach and other movements in psychology - namely, Behaviorism and evolutionary psychology - that set aside mechanistic explanations or make use of optimality assumptions. Through these comparisons, we identify a number of challenges that limit the rational program's potential contribution to psychological theory. Specifically, rational Bayesian models are significantly unconstrained, both because they are uninformed by a wide range of process-level data and because their assumptions about the environment are generally not grounded in empirical measurement. The psychological implications of most Bayesian models are also unclear. Bayesian inference itself is conceptually trivial, but strong assumptions are often embedded in the hypothesis sets and the approximation algorithms used to derive model predictions, without a clear delineation between psychological commitments and implementational details. Comparing multiple Bayesian models of the same task is rare, as is the realization that many Bayesian models recapitulate existing (mechanistic level) theories. Despite the expressive power of current Bayesian models, we argue they must be developed in conjunction with mechanistic considerations to offer substantive explanations of cognition. We lay out several means for such an integration, which take into account the representations on which Bayesian inference operates, as well as the algorithms and heuristics that carry it out. We argue this unification will better facilitate lasting contributions to psychological theory, avoiding the pitfalls
Most frugal explanations in Bayesian networks
Kwisthout, J.H.P.
2015-01-01
Inferring the most probable explanation to a set of variables, given a partial observation of the remaining variables, is one of the canonical computational problems in Bayesian networks, with widespread applications in AI and beyond. This problem, known as MAP, is computationally intractable (NP-ha
Bayesian semiparametric dynamic Nelson-Siegel model
C. Cakmakli
2011-01-01
This paper proposes the Bayesian semiparametric dynamic Nelson-Siegel model where the density of the yield curve factors and thereby the density of the yields are estimated along with other model parameters. This is accomplished by modeling the error distributions of the factors according to a Diric
Von Neumann was not a Quantum Bayesian.
Stacey, Blake C
2016-05-28
Wikipedia has claimed for over 3 years now that John von Neumann was the 'first quantum Bayesian'. In context, this reads as stating that von Neumann inaugurated QBism, the approach to quantum theory promoted by Fuchs, Mermin and Schack. This essay explores how such a claim is, historically speaking, unsupported. PMID:27091166
Von Neumann Was Not a Quantum Bayesian
Blake C. Stacey
2014-01-01
Wikipedia has claimed for over three years now that John von Neumann was the "first quantum Bayesian." In context, this reads as stating that von Neumann inaugurated QBism, the approach to quantum theory promoted by Fuchs, Mermin and Schack. This essay explores how such a claim is, historically speaking, unsupported.
A Bayesian Approach to Interactive Retrieval
Tague, Jean M.
1973-01-01
A probabilistic model for interactive retrieval is presented. Bayesian statistical decision theory principles are applied: use of prior and sample information about the relationship of document descriptions to query relevance; maximization of expected value of a utility function, to the problem of optimally restructuring search strategies in an…
Bayesian regularization of diffusion tensor images
DEFF Research Database (Denmark)
Frandsen, Jesper; Hobolth, Asger; Østergaard, Leif;
2007-01-01
several directions. The measured diffusion coefficients and thereby the diffusion tensors are subject to noise, leading to possibly flawed representations of the three dimensional fibre bundles. In this paper we develop a Bayesian procedure for regularizing the diffusion tensor field, fully utilizing...
Inverse Problems in a Bayesian Setting
Matthies, Hermann G.
2016-02-13
In a Bayesian setting, inverse problems and uncertainty quantification (UQ)—the propagation of uncertainty through a computational (forward) model—are strongly connected. In the form of conditional expectation the Bayesian update becomes computationally attractive. We give a detailed account of this approach via conditional approximation, various approximations, and the construction of filters. Together with a functional or spectral approach for the forward UQ there is no need for time-consuming and slowly convergent Monte Carlo sampling. The developed sampling-free non-linear Bayesian update in form of a filter is derived from the variational problem associated with conditional expectation. This formulation in general calls for further discretisation to make the computation possible, and we choose a polynomial approximation. After giving details on the actual computation in the framework of functional or spectral approximations, we demonstrate the workings of the algorithm on a number of examples of increasing complexity. At last, we compare the linear and nonlinear Bayesian update in form of a filter on some examples.
Comprehension and computation in Bayesian problem solving
Directory of Open Access Journals (Sweden)
Eric D. Johnson
2015-07-01
Full Text Available Humans have long been characterized as poor probabilistic reasoners when presented with explicit numerical information. Bayesian word problems provide a well-known example of this, where even highly educated and cognitively skilled individuals fail to adhere to mathematical norms. It is widely agreed that natural frequencies can facilitate Bayesian reasoning relative to normalized formats (e.g. probabilities, percentages, both by clarifying logical set-subset relations and by simplifying numerical calculations. Nevertheless, between-study performance on transparent Bayesian problems varies widely, and generally remains rather unimpressive. We suggest there has been an over-focus on this representational facilitator (i.e. transparent problem structures at the expense of the specific logical and numerical processing requirements and the corresponding individual abilities and skills necessary for providing Bayesian-like output given specific verbal and numerical input. We further suggest that understanding this task-individual pair could benefit from considerations from the literature on mathematical cognition, which emphasizes text comprehension and problem solving, along with contributions of online executive working memory, metacognitive regulation, and relevant stored knowledge and skills. We conclude by offering avenues for future research aimed at identifying the stages in problem solving at which correct versus incorrect reasoners depart, and how individual difference might influence this time point.
Bayesian Vector Autoregressions with Stochastic Volatility
Uhlig, H.F.H.V.S.
1996-01-01
This paper proposes a Bayesian approach to a vector autoregression with stochastic volatility, where the multiplicative evolution of the precision matrix is driven by a multivariate beta variate.Exact updating formulas are given to the nonlinear filtering of the precision matrix.Estimation of the au
Scaling Bayesian network discovery through incremental recovery
Castelo, J.R.; Siebes, A.P.J.M.
1999-01-01
Bayesian networks are a type of graphical models that, e.g., allow one to analyze the interaction among the variables in a database. A well-known problem with the discovery of such models from a database is the ``problem of high-dimensionality''. That is, the discovery of a network from a database w
A Bayesian Bootstrap for a Finite Population
Lo, Albert Y.
1988-01-01
A Bayesian bootstrap for a finite population is introduced; its small-sample distributional properties are discussed and compared with those of the frequentist bootstrap for a finite population. It is also shown that the two are first-order asymptotically equivalent.
Bayesian calibration for forensic age estimation.
Ferrante, Luigi; Skrami, Edlira; Gesuita, Rosaria; Cameriere, Roberto
2015-05-10
Forensic medicine is increasingly called upon to assess the age of individuals. Forensic age estimation is mostly required in relation to illegal immigration and identification of bodies or skeletal remains. A variety of age estimation methods are based on dental samples and use of regression models, where the age of an individual is predicted by morphological tooth changes that take place over time. From the medico-legal point of view, regression models, with age as the dependent random variable entail that age tends to be overestimated in the young and underestimated in the old. To overcome this bias, we describe a new full Bayesian calibration method (asymmetric Laplace Bayesian calibration) for forensic age estimation that uses asymmetric Laplace distribution as the probability model. The method was compared with three existing approaches (two Bayesian and a classical method) using simulated data. Although its accuracy was comparable with that of the other methods, the asymmetric Laplace Bayesian calibration appears to be significantly more reliable and robust in case of misspecification of the probability model. The proposed method was also applied to a real dataset of values of the pulp chamber of the right lower premolar measured on x-ray scans of individuals of known age. PMID:25645903
Exploiting structure in cooperative Bayesian games
F.A. Oliehoek; S. Whiteson; M.T.J. Spaan
2012-01-01
Cooperative Bayesian games (BGs) can model decision-making problems for teams of agents under imperfect information, but require space and computation time that is exponential in the number of agents. While agent independence has been used to mitigate these problems in perfect information settings,
Perfect Bayesian equilibrium. Part II: epistemic foundations
Bonanno, Giacomo
2011-01-01
In a companion paper we introduced a general notion of perfect Bayesian equilibrium which can be applied to arbitrary extensive-form games. The essential ingredient of the proposed definition is the qualitative notion of AGM-consistency. In this paper we provide an epistemic foundation for AGM-consistency based on the AGM theory of belief revision.
Decision generation tools and Bayesian inference
Jannson, Tomasz; Wang, Wenjian; Forrester, Thomas; Kostrzewski, Andrew; Veeris, Christian; Nielsen, Thomas
2014-05-01
Digital Decision Generation (DDG) tools are important software sub-systems of Command and Control (C2) systems and technologies. In this paper, we present a special type of DDGs based on Bayesian Inference, related to adverse (hostile) networks, including such important applications as terrorism-related networks and organized crime ones.
Von Neumann Was Not a Quantum Bayesian
Stacey, Blake C
2014-01-01
Wikipedia has claimed for over two years now that John von Neumann was the "first quantum Bayesian." In context, this reads as stating that von Neumann inaugurated QBism, the approach to quantum theory promoted by Fuchs, Mermin and Schack. This essay explores how such a claim is, historically speaking, unsupported.
Bayesian calibration of car-following models
Van Hinsbergen, C.P.IJ.; Van Lint, H.W.C.; Hoogendoorn, S.P.; Van Zuylen, H.J.
2010-01-01
Recent research has revealed that there exist large inter-driver differences in car-following behavior such that different car-following models may apply to different drivers. This study applies Bayesian techniques to the calibration of car-following models, where prior distributions on each model p
Basics of Bayesian Learning - Basically Bayes
DEFF Research Database (Denmark)
Larsen, Jan
Tutorial presented at the IEEE Machine Learning for Signal Processing Workshop 2006, Maynooth, Ireland, September 8, 2006. The tutorial focuses on the basic elements of Bayesian learning and its relation to classical learning paradigms. This includes a critical discussion of the pros and cons...
On local optima in learning bayesian networks
DEFF Research Database (Denmark)
Dalgaard, Jens; Kocka, Tomas; Pena, Jose
2003-01-01
This paper proposes and evaluates the k-greedy equivalence search algorithm (KES) for learning Bayesian networks (BNs) from complete data. The main characteristic of KES is that it allows a trade-off between greediness and randomness, thus exploring different good local optima. When greediness...
Bayesian Estimation Supersedes the "t" Test
Kruschke, John K.
2013-01-01
Bayesian estimation for 2 groups provides complete distributions of credible values for the effect size, group means and their difference, standard deviations and their difference, and the normality of the data. The method handles outliers. The decision rule can accept the null value (unlike traditional "t" tests) when certainty in the estimate is…
Bayesian Estimation of Thermonuclear Reaction Rates
Iliadis, Christian; Coc, Alain; Timmes, Frank; Starrfield, Sumner
2016-01-01
The problem of estimating non-resonant astrophysical S-factors and thermonuclear reaction rates, based on measured nuclear cross sections, is of major interest for nuclear energy generation, neutrino physics, and element synthesis. Many different methods have been applied in the past to this problem, all of them based on traditional statistics. Bayesian methods, on the other hand, are now in widespread use in the physical sciences. In astronomy, for example, Bayesian statistics is applied to the observation of extra-solar planets, gravitational waves, and type Ia supernovae. However, nuclear physics, in particular, has been slow to adopt Bayesian methods. We present the first astrophysical S-factors and reaction rates based on Bayesian statistics. We develop a framework that incorporates robust parameter estimation, systematic effects, and non-Gaussian uncertainties in a consistent manner. The method is applied to the d(p,$\\gamma$)$^3$He, $^3$He($^3$He,2p)$^4$He, and $^3$He($\\alpha$,$\\gamma$)$^7$Be reactions,...
Bayesian analysis of Markov point processes
DEFF Research Database (Denmark)
Berthelsen, Kasper Klitgaard; Møller, Jesper
2006-01-01
Recently Møller, Pettitt, Berthelsen and Reeves introduced a new MCMC methodology for drawing samples from a posterior distribution when the likelihood function is only specified up to a normalising constant. We illustrate the method in the setting of Bayesian inference for Markov point processes...
Bayesian Averaging is Well-Temperated
DEFF Research Database (Denmark)
Hansen, Lars Kai
2000-01-01
Bayesian predictions are stochastic just like predictions of any other inference scheme that generalize from a finite sample. While a simple variational argument shows that Bayes averaging is generalization optimal given that the prior matches the teacher parameter distribution the situation...
Modelling crime linkage with Bayesian networks
J. de Zoete; M. Sjerps; D. Lagnado; N. Fenton
2015-01-01
When two or more crimes show specific similarities, such as a very distinct modus operandi, the probability that they were committed by the same offender becomes of interest. This probability depends on the degree of similarity and distinctiveness. We show how Bayesian networks can be used to model
A Bayesian approach to linear regression in astronomy
Sereno, Mauro
2015-01-01
Linear regression is common in astronomical analyses. I discuss a Bayesian hierarchical modeling of data with heteroscedastic and possibly correlated measurement errors and intrinsic scatter. The method fully accounts for time evolution. The slope, the normalization, and the intrinsic scatter of the relation can evolve with the redshift. The intrinsic distribution of the independent variable is approximated using a mixture of Gaussian distributions whose means and standard deviations depend on time. The method can address scatter in the measured independent variable (a kind of Eddington bias), selection effects in the response variable (Malmquist bias), and departure from linearity in form of a knee. I tested the method with toy models and simulations and quantified the effect of biases and inefficient modeling. The R-package LIRA (LInear Regression in Astronomy) is made available to perform the regression.
On Bayesian methods of exploring qualitative interactions for targeted treatment.
Chen, Wei; Ghosh, Debashis; Raghunathan, Trivellore E; Norkin, Maxim; Sargent, Daniel J; Bepler, Gerold
2012-12-10
Providing personalized treatments designed to maximize benefits and minimizing harms is of tremendous current medical interest. One problem in this area is the evaluation of the interaction between the treatment and other predictor variables. Treatment effects in subgroups having the same direction but different magnitudes are called quantitative interactions, whereas those having opposite directions in subgroups are called qualitative interactions (QIs). Identifying QIs is challenging because they are rare and usually unknown among many potential biomarkers. Meanwhile, subgroup analysis reduces the power of hypothesis testing and multiple subgroup analyses inflate the type I error rate. We propose a new Bayesian approach to search for QI in a multiple regression setting with adaptive decision rules. We consider various regression models for the outcome. We illustrate this method in two examples of phase III clinical trials. The algorithm is straightforward and easy to implement using existing software packages. We provide a sample code in Appendix A.
Petit, V.; Wade, G. A.
2011-01-01
In this paper we describe a Bayesian statistical method designed to infer the magnetic properties of stars observed using high-resolution circular spectropolarimetry in the context of large surveys. This approach is well suited for analysing stars for which the stellar rotation period is not known, and therefore the rotational phases of the observations are ambiguous. The model assumes that the magnetic observations correspond to a dipole oblique rotator, a situation commonly encountered in i...
Bayesian network as a modelling tool for risk management in agriculture
Svend Rasmussen; Madsen, Anders L.; Mogens Lund
2013-01-01
The importance of risk management increases as farmers become more exposed to risk. But risk management is a difficult topic because income risk is the result of the complex interaction of multiple risk factors combined with the effect of an increasing array of possible risk management tools. In this paper we use Bayesian networks as an integrated modelling approach for representing uncertainty and analysing risk management in agriculture. It is shown how historical farm account data may be e...
Directory of Open Access Journals (Sweden)
Andrew K. DAVIS, Joseph R. MILANOVICH
2010-04-01
Full Text Available Throughout the animal kingdom there are species that have two or more phenotypic forms or ‘morphs’, and many of these are amphibians. In North America, the red-backed salamander Plethodon cinereus can have either a red dorsal stripe or no dorsal stripe (lead-phase form, and evidence to date indicates the lead-phase form incurs a greater number of attacks from predators. In a recent collection of 51 P. cinereus, blood smears of both color morphs (35 red-stripe, 16 lead-phase were examined to obtain numbers of circulating leukocytes (via light microscopy, which can be used to indirectly estimate levels of stress hormones in vertebrates via a ‘hematological stress index’, which is the ratio between the number of two leukocyte types (neutrophils and lymphocytes. Our results showed that lead-phase salamanders tended to have greater numbers of circulating neutrophils and lower numbers of circulating lymphocytes than red-stripe morphs, leading to higher average neutrophil-lymphocyte ratios in lead-phase individuals. Since the salamanders were held (refrigerated for 7 days before sampling, we cannot be certain if this effect is a stress reaction to the captivity or the normal level for this morph. However comparison with two sets of related salamanders that were captured and sampled immediately indicates the red-stripe salamanders were either not stressed from the captivity at all, or their white blood cell distributions had returned to normal after 7 days of captivity. Taken together, our results indicate that lead-phase forms of P. cinereus have higher stress levels than the red-stripe forms, which may be a consequence of their higher exposure to, and/or attacks from, predators. They may also indicate that the lead-phase form is less-suited to captivity than the red-stripe form of this species [Current Zoology 56 (2: 238–243, 2010].
Directory of Open Access Journals (Sweden)
Breanna L. Riedel
2012-01-01
Full Text Available Nonforested habitats such as open fields and pastures have been considered unsuitable for desiccation-prone woodland salamanders such as the Eastern Red-backed Salamander (Plethodon cinereus. Recent research has suggested that Plethodon cinereus may not only disperse across but also reside within open habitats including fields, meadows, and pastures. However, presence and high densities of P. cinereus within agriculturally disturbed habitats may be misleading if these populations exhibit atypical demographic characteristics or decreased physical condition relative to forest populations. We surveyed artificial cover boards from 2004-2005 to compare physical condition, sex ratios, and age-class structure of P. cinereus among woodland, woodland-meadow edge, silvopasture, and meadow sites in the central Appalachian Mountains of southern West Virginia. Physical condition of salamanders was not significantly different among the four habitats. Furthermore, adult sex ratios of P. cinereus typically were not significantly different from 1 : 1 and were similar between forested and non-forested sites, although populations within silvopastures were biased towards females. However, adult salamanders were significantly more abundant than juveniles in all habitat types, with differences most pronounced within meadow habitats. Our study indicates that relatively small, non-forested habitats such as silvopastures and meadows may not adversely affect the overall physical condition or sex ratios of Plethodon cinereus. However, the paucity of juveniles within disturbed meadows indicates that these agriculturally modified habitats may negatively impact reproduction or that immature salamanders are at a physiological or competitive disadvantage in comparison to adults, particularly when surface cover is limited.
Computational statistics using the Bayesian Inference Engine
Weinberg, Martin D.
2013-09-01
This paper introduces the Bayesian Inference Engine (BIE), a general parallel, optimized software package for parameter inference and model selection. This package is motivated by the analysis needs of modern astronomical surveys and the need to organize and reuse expensive derived data. The BIE is the first platform for computational statistics designed explicitly to enable Bayesian update and model comparison for astronomical problems. Bayesian update is based on the representation of high-dimensional posterior distributions using metric-ball-tree based kernel density estimation. Among its algorithmic offerings, the BIE emphasizes hybrid tempered Markov chain Monte Carlo schemes that robustly sample multimodal posterior distributions in high-dimensional parameter spaces. Moreover, the BIE implements a full persistence or serialization system that stores the full byte-level image of the running inference and previously characterized posterior distributions for later use. Two new algorithms to compute the marginal likelihood from the posterior distribution, developed for and implemented in the BIE, enable model comparison for complex models and data sets. Finally, the BIE was designed to be a collaborative platform for applying Bayesian methodology to astronomy. It includes an extensible object-oriented and easily extended framework that implements every aspect of the Bayesian inference. By providing a variety of statistical algorithms for all phases of the inference problem, a scientist may explore a variety of approaches with a single model and data implementation. Additional technical details and download details are available from http://www.astro.umass.edu/bie. The BIE is distributed under the GNU General Public License.
Directory of Open Access Journals (Sweden)
Benjamin W. Y. Lo
2013-01-01
Full Text Available Objective. The novel clinical prediction approach of Bayesian neural networks with fuzzy logic inferences is created and applied to derive prognostic decision rules in cerebral aneurysmal subarachnoid hemorrhage (aSAH. Methods. The approach of Bayesian neural networks with fuzzy logic inferences was applied to data from five trials of Tirilazad for aneurysmal subarachnoid hemorrhage (3551 patients. Results. Bayesian meta-analyses of observational studies on aSAH prognostic factors gave generalizable posterior distributions of population mean log odd ratios (ORs. Similar trends were noted in Bayesian and linear regression ORs. Significant outcome predictors include normal motor response, cerebral infarction, history of myocardial infarction, cerebral edema, history of diabetes mellitus, fever on day 8, prior subarachnoid hemorrhage, admission angiographic vasospasm, neurological grade, intraventricular hemorrhage, ruptured aneurysm size, history of hypertension, vasospasm day, age and mean arterial pressure. Heteroscedasticity was present in the nontransformed dataset. Artificial neural networks found nonlinear relationships with 11 hidden variables in 1 layer, using the multilayer perceptron model. Fuzzy logic decision rules (centroid defuzzification technique denoted cut-off points for poor prognosis at greater than 2.5 clusters. Discussion. This aSAH prognostic system makes use of existing knowledge, recognizes unknown areas, incorporates one's clinical reasoning, and compensates for uncertainty in prognostication.
A Bayesian outlier criterion to detect SNPs under selection in large data sets.
Directory of Open Access Journals (Sweden)
Mathieu Gautier
Full Text Available BACKGROUND: The recent advent of high-throughput SNP genotyping technologies has opened new avenues of research for population genetics. In particular, a growing interest in the identification of footprints of selection, based on genome scans for adaptive differentiation, has emerged. METHODOLOGY/PRINCIPAL FINDINGS: The purpose of this study is to develop an efficient model-based approach to perform bayesian exploratory analyses for adaptive differentiation in very large SNP data sets. The basic idea is to start with a very simple model for neutral loci that is easy to implement under a bayesian framework and to identify selected loci as outliers via Posterior Predictive P-values (PPP-values. Applications of this strategy are considered using two different statistical models. The first one was initially interpreted in the context of populations evolving respectively under pure genetic drift from a common ancestral population while the second one relies on populations under migration-drift equilibrium. Robustness and power of the two resulting bayesian model-based approaches to detect SNP under selection are further evaluated through extensive simulations. An application to a cattle data set is also provided. CONCLUSIONS/SIGNIFICANCE: The procedure described turns out to be much faster than former bayesian approaches and also reasonably efficient especially to detect loci under positive selection.
Dynamic causal modelling of electrographic seizure activity using Bayesian belief updating.
Cooray, Gerald K; Sengupta, Biswa; Douglas, Pamela K; Friston, Karl
2016-01-15
Seizure activity in EEG recordings can persist for hours with seizure dynamics changing rapidly over time and space. To characterise the spatiotemporal evolution of seizure activity, large data sets often need to be analysed. Dynamic causal modelling (DCM) can be used to estimate the synaptic drivers of cortical dynamics during a seizure; however, the requisite (Bayesian) inversion procedure is computationally expensive. In this note, we describe a straightforward procedure, within the DCM framework, that provides efficient inversion of seizure activity measured with non-invasive and invasive physiological recordings; namely, EEG/ECoG. We describe the theoretical background behind a Bayesian belief updating scheme for DCM. The scheme is tested on simulated and empirical seizure activity (recorded both invasively and non-invasively) and compared with standard Bayesian inversion. We show that the Bayesian belief updating scheme provides similar estimates of time-varying synaptic parameters, compared to standard schemes, indicating no significant qualitative change in accuracy. The difference in variance explained was small (less than 5%). The updating method was substantially more efficient, taking approximately 5-10min compared to approximately 1-2h. Moreover, the setup of the model under the updating scheme allows for a clear specification of how neuronal variables fluctuate over separable timescales. This method now allows us to investigate the effect of fast (neuronal) activity on slow fluctuations in (synaptic) parameters, paving a way forward to understand how seizure activity is generated.
Universal Darwinism as a process of Bayesian inference
Campbell, John O
2016-01-01
Many of the mathematical frameworks describing natural selection are equivalent to Bayes Theorem, also known as Bayesian updating. By definition, a process of Bayesian Inference is one which involves a Bayesian update, so we may conclude that these frameworks describe natural selection as a process of Bayesian inference. Thus natural selection serves as a counter example to a widely-held interpretation that restricts Bayesian Inference to human mental processes (including the endeavors of statisticians). As Bayesian inference can always be cast in terms of (variational) free energy minimization, natural selection can be viewed as comprising two components: a generative model of an "experiment" in the external world environment, and the results of that "experiment" or the "surprise" entailed by predicted and actual outcomes of the "experiment". Minimization of free energy implies that the implicit measure of "surprise" experienced serves to update the generative model in a Bayesian manner. This description clo...
Allegory and Event: Two ways of saying the salamander in Yves Bonnefoy
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Layla Roesler
2010-07-01
Full Text Available L’article examine l’idée d’événement à travers la figure de la salamandre dans l’œuvre d’Yves Bonnefoy. L’image, saisissante en elle-même, est rendue plus significative encore par le fait qu’elle franchit les frontières séparant habituellement les genres littéraires. Son apparition à la fois dans un essai et dans un cycle de poèmes tend à l’ancrer dans la réalité d’un événement vécu. Nous proposons de voir dans la juxtaposition des deux textes non seulement une narration qui prend l’événement vécu en charge, mais l’agencement même des possibilités permettant de reconnaître l’événement comme tel.This paper addresses the notion of event through the prism of Yves Bonnefoy’s salamander trope. This arresting image is all the more memorable because it crosses the boundaries of generic separations, appearing both in an essay as well as in an early poetry collection. The fact that an identical image should be reiterated in such formally disparate structures seems to point insistently to its reality as a material event. I argue that juxtaposing the two texts reveals both a narration recounting an event and, simultaneously, the ordering of possibilities leading to its recognition as event.El artículo examina la idea del acontecimiento a través de la figura de la salamandra en la obra de Yves Bonnefoy. La imagen, sorprendente en sí misma, se vuelve más significativa aún debido al hecho de que cruza las fronteras que separan generalmente los géneros literarios. Su presencia tanto en un ensayo como en un ciclo de poemas tiende a situarla en la realidad de un acontecimiento vivido. En la yuxtaposición de los dos textos proponemos ver no sólo una narración que asume el acontecimiento vivido, sino también la disposición misma de las posibilidades que permiten reconocer al acontecimiento como tal.
Bayesian network learning for natural hazard assessments
Vogel, Kristin
2016-04-01
Even though quite different in occurrence and consequences, from a modelling perspective many natural hazards share similar properties and challenges. Their complex nature as well as lacking knowledge about their driving forces and potential effects make their analysis demanding. On top of the uncertainty about the modelling framework, inaccurate or incomplete event observations and the intrinsic randomness of the natural phenomenon add up to different interacting layers of uncertainty, which require a careful handling. Thus, for reliable natural hazard assessments it is crucial not only to capture and quantify involved uncertainties, but also to express and communicate uncertainties in an intuitive way. Decision-makers, who often find it difficult to deal with uncertainties, might otherwise return to familiar (mostly deterministic) proceedings. In the scope of the DFG research training group „NatRiskChange" we apply the probabilistic framework of Bayesian networks for diverse natural hazard and vulnerability studies. The great potential of Bayesian networks was already shown in previous natural hazard assessments. Treating each model component as random variable, Bayesian networks aim at capturing the joint distribution of all considered variables. Hence, each conditional distribution of interest (e.g. the effect of precautionary measures on damage reduction) can be inferred. The (in-)dependencies between the considered variables can be learned purely data driven or be given by experts. Even a combination of both is possible. By translating the (in-)dependences into a graph structure, Bayesian networks provide direct insights into the workings of the system and allow to learn about the underlying processes. Besides numerous studies on the topic, learning Bayesian networks from real-world data remains challenging. In previous studies, e.g. on earthquake induced ground motion and flood damage assessments, we tackled the problems arising with continuous variables
Bayesian multitask inverse reinforcement learning
Dimitrakakis, Christos
2011-01-01
We generalise the problem of inverse reinforcement learning to multiple tasks, from a set of demonstrations. Each demonstration may represent one expert trying to solve a different task. Alternatively, one may see each demonstration as given by a different expert trying to solve the same task. Our main technical contribution is to solve the problem by formalising it as statistical preference elicitation, via a number of structured priors, whose form captures our biases about the relatedness of different tasks or expert policies. We show that our methodology allows us not only to learn to efficiently from multiple experts but to also effectively differentiate between the goals of each. Possible applications include analysing the intrinsic motivations of subjects in behavioural experiments and imitation learning from multiple teachers.
Dembo, Mana; Radovčić, Davorka; Garvin, Heather M; Laird, Myra F; Schroeder, Lauren; Scott, Jill E; Brophy, Juliet; Ackermann, Rebecca R; Musiba, Chares M; de Ruiter, Darryl J; Mooers, Arne Ø; Collard, Mark
2016-08-01
Homo naledi is a recently discovered species of fossil hominin from South Africa. A considerable amount is already known about H. naledi but some important questions remain unanswered. Here we report a study that addressed two of them: "Where does H. naledi fit in the hominin evolutionary tree?" and "How old is it?" We used a large supermatrix of craniodental characters for both early and late hominin species and Bayesian phylogenetic techniques to carry out three analyses. First, we performed a dated Bayesian analysis to generate estimates of the evolutionary relationships of fossil hominins including H. naledi. Then we employed Bayes factor tests to compare the strength of support for hypotheses about the relationships of H. naledi suggested by the best-estimate trees. Lastly, we carried out a resampling analysis to assess the accuracy of the age estimate for H. naledi yielded by the dated Bayesian analysis. The analyses strongly supported the hypothesis that H. naledi forms a clade with the other Homo species and Australopithecus sediba. The analyses were more ambiguous regarding the position of H. naledi within the (Homo, Au. sediba) clade. A number of hypotheses were rejected, but several others were not. Based on the available craniodental data, Homo antecessor, Asian Homo erectus, Homo habilis, Homo floresiensis, Homo sapiens, and Au. sediba could all be the sister taxon of H. naledi. According to the dated Bayesian analysis, the most likely age for H. naledi is 912 ka. This age estimate was supported by the resampling analysis. Our findings have a number of implications. Most notably, they support the assignment of the new specimens to Homo, cast doubt on the claim that H. naledi is simply a variant of H. erectus, and suggest H. naledi is younger than has been previously proposed. PMID:27457542
Dembo, Mana; Radovčić, Davorka; Garvin, Heather M; Laird, Myra F; Schroeder, Lauren; Scott, Jill E; Brophy, Juliet; Ackermann, Rebecca R; Musiba, Chares M; de Ruiter, Darryl J; Mooers, Arne Ø; Collard, Mark
2016-08-01
Homo naledi is a recently discovered species of fossil hominin from South Africa. A considerable amount is already known about H. naledi but some important questions remain unanswered. Here we report a study that addressed two of them: "Where does H. naledi fit in the hominin evolutionary tree?" and "How old is it?" We used a large supermatrix of craniodental characters for both early and late hominin species and Bayesian phylogenetic techniques to carry out three analyses. First, we performed a dated Bayesian analysis to generate estimates of the evolutionary relationships of fossil hominins including H. naledi. Then we employed Bayes factor tests to compare the strength of support for hypotheses about the relationships of H. naledi suggested by the best-estimate trees. Lastly, we carried out a resampling analysis to assess the accuracy of the age estimate for H. naledi yielded by the dated Bayesian analysis. The analyses strongly supported the hypothesis that H. naledi forms a clade with the other Homo species and Australopithecus sediba. The analyses were more ambiguous regarding the position of H. naledi within the (Homo, Au. sediba) clade. A number of hypotheses were rejected, but several others were not. Based on the available craniodental data, Homo antecessor, Asian Homo erectus, Homo habilis, Homo floresiensis, Homo sapiens, and Au. sediba could all be the sister taxon of H. naledi. According to the dated Bayesian analysis, the most likely age for H. naledi is 912 ka. This age estimate was supported by the resampling analysis. Our findings have a number of implications. Most notably, they support the assignment of the new specimens to Homo, cast doubt on the claim that H. naledi is simply a variant of H. erectus, and suggest H. naledi is younger than has been previously proposed.
Bayesian parameter estimation for effective field theories
Wesolowski, S; Furnstahl, R J; Phillips, D R; Thapaliya, A
2015-01-01
We present procedures based on Bayesian statistics for effective field theory (EFT) parameter estimation from data. The extraction of low-energy constants (LECs) is guided by theoretical expectations that supplement such information in a quantifiable way through the specification of Bayesian priors. A prior for natural-sized LECs reduces the possibility of overfitting, and leads to a consistent accounting of different sources of uncertainty. A set of diagnostic tools are developed that analyze the fit and ensure that the priors do not bias the EFT parameter estimation. The procedures are illustrated using representative model problems and the extraction of LECs for the nucleon mass expansion in SU(2) chiral perturbation theory from synthetic lattice data.
Applications of Bayesian spectrum representation in acoustics
Botts, Jonathan M.
This dissertation utilizes a Bayesian inference framework to enhance the solution of inverse problems where the forward model maps to acoustic spectra. A Bayesian solution to filter design inverts a acoustic spectra to pole-zero locations of a discrete-time filter model. Spatial sound field analysis with a spherical microphone array is a data analysis problem that requires inversion of spatio-temporal spectra to directions of arrival. As with many inverse problems, a probabilistic analysis results in richer solutions than can be achieved with ad-hoc methods. In the filter design problem, the Bayesian inversion results in globally optimal coefficient estimates as well as an estimate the most concise filter capable of representing the given spectrum, within a single framework. This approach is demonstrated on synthetic spectra, head-related transfer function spectra, and measured acoustic reflection spectra. The Bayesian model-based analysis of spatial room impulse responses is presented as an analogous problem with equally rich solution. The model selection mechanism provides an estimate of the number of arrivals, which is necessary to properly infer the directions of simultaneous arrivals. Although, spectrum inversion problems are fairly ubiquitous, the scope of this dissertation has been limited to these two and derivative problems. The Bayesian approach to filter design is demonstrated on an artificial spectrum to illustrate the model comparison mechanism and then on measured head-related transfer functions to show the potential range of application. Coupled with sampling methods, the Bayesian approach is shown to outperform least-squares filter design methods commonly used in commercial software, confirming the need for a global search of the parameter space. The resulting designs are shown to be comparable to those that result from global optimization methods, but the Bayesian approach has the added advantage of a filter length estimate within the same unified
Narrowband interference parameterization for sparse Bayesian recovery
Ali, Anum
2015-09-11
This paper addresses the problem of narrowband interference (NBI) in SC-FDMA systems by using tools from compressed sensing and stochastic geometry. The proposed NBI cancellation scheme exploits the frequency domain sparsity of the unknown signal and adopts a Bayesian sparse recovery procedure. This is done by keeping a few randomly chosen sub-carriers data free to sense the NBI signal at the receiver. As Bayesian recovery requires knowledge of some NBI parameters (i.e., mean, variance and sparsity rate), we use tools from stochastic geometry to obtain analytical expressions for the required parameters. Our simulation results validate the analysis and depict suitability of the proposed recovery method for NBI mitigation. © 2015 IEEE.
Bayesian networks for enterprise risk assessment
Bonafede, C E
2006-01-01
According to different typologies of activity and priority, risks can assume diverse meanings and it can be assessed in different ways. In general risk is measured in terms of a probability combination of an event (frequency) and its consequence (impact). To estimate the frequency and the impact (severity) historical data or expert opinions (either qualitative or quantitative data) are used. Moreover qualitative data must be converted in numerical values to be used in the model. In the case of enterprise risk assessment the considered risks are, for instance, strategic, operational, legal and of image, which many times are difficult to be quantified. So in most cases only expert data, gathered by scorecard approaches, are available for risk analysis. The Bayesian Network is a useful tool to integrate different information and in particular to study the risk's joint distribution by using data collected from experts. In this paper we want to show a possible approach for building a Bayesian networks in the parti...
Bayesianism and inference to the best explanation
Directory of Open Access Journals (Sweden)
Valeriano IRANZO
2008-01-01
Full Text Available Bayesianism and Inference to the best explanation (IBE are two different models of inference. Recently there has been some debate about the possibility of “bayesianizing” IBE. Firstly I explore several alternatives to include explanatory considerations in Bayes’s Theorem. Then I distinguish two different interpretations of prior probabilities: “IBE-Bayesianism” (IBE-Bay and “frequentist-Bayesianism” (Freq-Bay. After detailing the content of the latter, I propose a rule for assessing the priors. I also argue that Freq-Bay: (i endorses a role for explanatory value in the assessment of scientific hypotheses; (ii avoids a purely subjectivist reading of prior probabilities; and (iii fits better than IBE-Bayesianism with two basic facts about science, i.e., the prominent role played by empirical testing and the existence of many scientific theories in the past that failed to fulfil their promises and were subsequently abandoned.
QBism, the Perimeter of Quantum Bayesianism
Fuchs, Christopher A
2010-01-01
This article summarizes the Quantum Bayesian point of view of quantum mechanics, with special emphasis on the view's outer edges---dubbed QBism. QBism has its roots in personalist Bayesian probability theory, is crucially dependent upon the tools of quantum information theory, and most recently, has set out to investigate whether the physical world might be of a type sketched by some false-started philosophies of 100 years ago (pragmatism, pluralism, nonreductionism, and meliorism). Beyond conceptual issues, work at Perimeter Institute is focused on the hard technical problem of finding a good representation of quantum mechanics purely in terms of probabilities, without amplitudes or Hilbert-space operators. The best candidate representation involves a mysterious entity called a symmetric informationally complete quantum measurement. Contemplation of it gives a way of thinking of the Born Rule as an addition to the rules of probability theory, applicable when an agent considers gambling on the consequences of...
Distributed Bayesian Networks for User Modeling
DEFF Research Database (Denmark)
Tedesco, Roberto; Dolog, Peter; Nejdl, Wolfgang;
2006-01-01
The World Wide Web is a popular platform for providing eLearning applications to a wide spectrum of users. However – as users differ in their preferences, background, requirements, and goals – applications should provide personalization mechanisms. In the Web context, user models used...... by such adaptive applications are often partial fragments of an overall user model. The fragments have then to be collected and merged into a global user profile. In this paper we investigate and present algorithms able to cope with distributed, fragmented user models – based on Bayesian Networks – in the context...... of Web-based eLearning platforms. The scenario we are tackling assumes learners who use several systems over time, which are able to create partial Bayesian Networks for user models based on the local system context. In particular, we focus on how to merge these partial user models. Our merge mechanism...
Machine learning a Bayesian and optimization perspective
Theodoridis, Sergios
2015-01-01
This tutorial text gives a unifying perspective on machine learning by covering both probabilistic and deterministic approaches, which rely on optimization techniques, as well as Bayesian inference, which is based on a hierarchy of probabilistic models. The book presents the major machine learning methods as they have been developed in different disciplines, such as statistics, statistical and adaptive signal processing and computer science. Focusing on the physical reasoning behind the mathematics, all the various methods and techniques are explained in depth, supported by examples and problems, giving an invaluable resource to the student and researcher for understanding and applying machine learning concepts. The book builds carefully from the basic classical methods to the most recent trends, with chapters written to be as self-contained as possible, making the text suitable for different courses: pattern recognition, statistical/adaptive signal processing, statistical/Bayesian learning, as well as shor...
Bayesian image reconstruction: Application to emission tomography
Energy Technology Data Exchange (ETDEWEB)
Nunez, J.; Llacer, J.
1989-02-01
In this paper we propose a Maximum a Posteriori (MAP) method of image reconstruction in the Bayesian framework for the Poisson noise case. We use entropy to define the prior probability and likelihood to define the conditional probability. The method uses sharpness parameters which can be theoretically computed or adjusted, allowing us to obtain MAP reconstructions without the problem of the grey'' reconstructions associated with the pre Bayesian reconstructions. We have developed several ways to solve the reconstruction problem and propose a new iterative algorithm which is stable, maintains positivity and converges to feasible images faster than the Maximum Likelihood Estimate method. We have successfully applied the new method to the case of Emission Tomography, both with simulated and real data. 41 refs., 4 figs., 1 tab.
The Bayesian Who Knew Too Much
Benétreau-Dupin, Yann
2014-01-01
In several papers, John Norton has argued that Bayesianism cannot handle ignorance adequately due to its inability to distinguish between neutral and disconfirming evidence. He argued that this inability sows confusion in, e.g., anthropic reasoning in cosmology or the Doomsday argument, by allowing one to draw unwarranted conclusions from a lack of knowledge. Norton has suggested criteria for a candidate for representation of neutral support. Imprecise credences (families of credal probability functions) constitute a Bayesian-friendly framework that allows us to avoid inadequate neutral priors and better handle ignorance. The imprecise model generally agrees with Norton's representation of ignorance but requires that his criterion of self-duality be reformulated or abandoned
Software Health Management with Bayesian Networks
Mengshoel, Ole; Schumann, JOhann
2011-01-01
Most modern aircraft as well as other complex machinery is equipped with diagnostics systems for its major subsystems. During operation, sensors provide important information about the subsystem (e.g., the engine) and that information is used to detect and diagnose faults. Most of these systems focus on the monitoring of a mechanical, hydraulic, or electromechanical subsystem of the vehicle or machinery. Only recently, health management systems that monitor software have been developed. In this paper, we will discuss our approach of using Bayesian networks for Software Health Management (SWHM). We will discuss SWHM requirements, which make advanced reasoning capabilities for the detection and diagnosis important. Then we will present our approach to using Bayesian networks for the construction of health models that dynamically monitor a software system and is capable of detecting and diagnosing faults.
Learning Bayesian networks using genetic algorithm
Institute of Scientific and Technical Information of China (English)
Chen Fei; Wang Xiufeng; Rao Yimei
2007-01-01
A new method to evaluate the fitness of the Bayesian networks according to the observed data is provided. The main advantage of this criterion is that it is suitable for both the complete and incomplete cases while the others not.Moreover it facilitates the computation greatly. In order to reduce the search space, the notation of equivalent class proposed by David Chickering is adopted. Instead of using the method directly, the novel criterion, variable ordering, and equivalent class are combined,moreover the proposed mthod avoids some problems caused by the previous one. Later, the genetic algorithm which allows global convergence, lack in the most of the methods searching for Bayesian network is applied to search for a good model in thisspace. To speed up the convergence, the genetic algorithm is combined with the greedy algorithm. Finally, the simulation shows the validity of the proposed approach.
Bayesian Population Projections for the United Nations.
Raftery, Adrian E; Alkema, Leontine; Gerland, Patrick
2014-02-01
The United Nations regularly publishes projections of the populations of all the world's countries broken down by age and sex. These projections are the de facto standard and are widely used by international organizations, governments and researchers. Like almost all other population projections, they are produced using the standard deterministic cohort-component projection method and do not yield statements of uncertainty. We describe a Bayesian method for producing probabilistic population projections for most countries that the United Nations could use. It has at its core Bayesian hierarchical models for the total fertility rate and life expectancy at birth. We illustrate the method and show how it can be extended to address concerns about the UN's current assumptions about the long-term distribution of fertility. The method is implemented in the R packages bayesTFR, bayesLife, bayesPop and bayesDem.
Approximate Bayesian Computation: a nonparametric perspective
Blum, Michael
2010-01-01
Approximate Bayesian Computation is a family of likelihood-free inference techniques that are well-suited to models defined in terms of a stochastic generating mechanism. In a nutshell, Approximate Bayesian Computation proceeds by computing summary statistics s_obs from the data and simulating summary statistics for different values of the parameter theta. The posterior distribution is then approximated by an estimator of the conditional density g(theta|s_obs). In this paper, we derive the asymptotic bias and variance of the standard estimators of the posterior distribution which are based on rejection sampling and linear adjustment. Additionally, we introduce an original estimator of the posterior distribution based on quadratic adjustment and we show that its bias contains a fewer number of terms than the estimator with linear adjustment. Although we find that the estimators with adjustment are not universally superior to the estimator based on rejection sampling, we find that they can achieve better perfor...
Bayesian information fusion networks for biosurveillance applications.
Mnatsakanyan, Zaruhi R; Burkom, Howard S; Coberly, Jacqueline S; Lombardo, Joseph S
2009-01-01
This study introduces new information fusion algorithms to enhance disease surveillance systems with Bayesian decision support capabilities. A detection system was built and tested using chief complaints from emergency department visits, International Classification of Diseases Revision 9 (ICD-9) codes from records of outpatient visits to civilian and military facilities, and influenza surveillance data from health departments in the National Capital Region (NCR). Data anomalies were identified and distribution of time offsets between events in the multiple data streams were established. The Bayesian Network was built to fuse data from multiple sources and identify influenza-like epidemiologically relevant events. Results showed increased specificity compared with the alerts generated by temporal anomaly detection algorithms currently deployed by NCR health departments. Further research should be done to investigate correlations between data sources for efficient fusion of the collected data.
Bayesian Magnetohydrodynamic Seismology of Coronal Loops
Arregui, Inigo
2011-01-01
We perform a Bayesian parameter inference in the context of resonantly damped transverse coronal loop oscillations. The forward problem is solved in terms of parametric results for kink waves in one-dimensional flux tubes in the thin tube and thin boundary approximations. For the inverse problem, we adopt a Bayesian approach to infer the most probable values of the relevant parameters, for given observed periods and damping times, and to extract their confidence levels. The posterior probability distribution functions are obtained by means of Markov Chain Monte Carlo simulations, incorporating observed uncertainties in a consistent manner. We find well localized solutions in the posterior probability distribution functions for two of the three parameters of interest, namely the Alfven travel time and the transverse inhomogeneity length-scale. The obtained estimates for the Alfven travel time are consistent with previous inversion results, but the method enables us to additionally constrain the transverse inho...
A Bayesian nonparametric meta-analysis model.
Karabatsos, George; Talbott, Elizabeth; Walker, Stephen G
2015-03-01
In a meta-analysis, it is important to specify a model that adequately describes the effect-size distribution of the underlying population of studies. The conventional normal fixed-effect and normal random-effects models assume a normal effect-size population distribution, conditionally on parameters and covariates. For estimating the mean overall effect size, such models may be adequate, but for prediction, they surely are not if the effect-size distribution exhibits non-normal behavior. To address this issue, we propose a Bayesian nonparametric meta-analysis model, which can describe a wider range of effect-size distributions, including unimodal symmetric distributions, as well as skewed and more multimodal distributions. We demonstrate our model through the analysis of real meta-analytic data arising from behavioral-genetic research. We compare the predictive performance of the Bayesian nonparametric model against various conventional and more modern normal fixed-effects and random-effects models.
Distributed Detection via Bayesian Updates and Consensus
Liu, Qipeng; Wang, Xiaofan
2014-01-01
In this paper, we discuss a class of distributed detection algorithms which can be viewed as implementations of Bayes' law in distributed settings. Some of the algorithms are proposed in the literature most recently, and others are first developed in this paper. The common feature of these algorithms is that they all combine (i) certain kinds of consensus protocols with (ii) Bayesian updates. They are different mainly in the aspect of the type of consensus protocol and the order of the two operations. After discussing their similarities and differences, we compare these distributed algorithms by numerical examples. We focus on the rate at which these algorithms detect the underlying true state of an object. We find that (a) The algorithms with consensus via geometric average is more efficient than that via arithmetic average; (b) The order of consensus aggregation and Bayesian update does not apparently influence the performance of the algorithms; (c) The existence of communication delay dramatically slows do...
Probabilistic forecasting and Bayesian data assimilation
Reich, Sebastian
2015-01-01
In this book the authors describe the principles and methods behind probabilistic forecasting and Bayesian data assimilation. Instead of focusing on particular application areas, the authors adopt a general dynamical systems approach, with a profusion of low-dimensional, discrete-time numerical examples designed to build intuition about the subject. Part I explains the mathematical framework of ensemble-based probabilistic forecasting and uncertainty quantification. Part II is devoted to Bayesian filtering algorithms, from classical data assimilation algorithms such as the Kalman filter, variational techniques, and sequential Monte Carlo methods, through to more recent developments such as the ensemble Kalman filter and ensemble transform filters. The McKean approach to sequential filtering in combination with coupling of measures serves as a unifying mathematical framework throughout Part II. Assuming only some basic familiarity with probability, this book is an ideal introduction for graduate students in ap...
Bayesian Peak Picking for NMR Spectra
Cheng, Yichen
2014-02-01
Protein structure determination is a very important topic in structural genomics, which helps people to understand varieties of biological functions such as protein-protein interactions, protein–DNA interactions and so on. Nowadays, nuclear magnetic resonance (NMR) has often been used to determine the three-dimensional structures of protein in vivo. This study aims to automate the peak picking step, the most important and tricky step in NMR structure determination. We propose to model the NMR spectrum by a mixture of bivariate Gaussian densities and use the stochastic approximation Monte Carlo algorithm as the computational tool to solve the problem. Under the Bayesian framework, the peak picking problem is casted as a variable selection problem. The proposed method can automatically distinguish true peaks from false ones without preprocessing the data. To the best of our knowledge, this is the first effort in the literature that tackles the peak picking problem for NMR spectrum data using Bayesian method.
A Bayesian approach to person perception.
Clifford, C W G; Mareschal, I; Otsuka, Y; Watson, T L
2015-11-01
Here we propose a Bayesian approach to person perception, outlining the theoretical position and a methodological framework for testing the predictions experimentally. We use the term person perception to refer not only to the perception of others' personal attributes such as age and sex but also to the perception of social signals such as direction of gaze and emotional expression. The Bayesian approach provides a formal description of the way in which our perception combines current sensory evidence with prior expectations about the structure of the environment. Such expectations can lead to unconscious biases in our perception that are particularly evident when sensory evidence is uncertain. We illustrate the ideas with reference to our recent studies on gaze perception which show that people have a bias to perceive the gaze of others as directed towards themselves. We also describe a potential application to the study of the perception of a person's sex, in which a bias towards perceiving males is typically observed.
Bayesian parameter estimation for effective field theories
Wesolowski, S.; Klco, N.; Furnstahl, R. J.; Phillips, D. R.; Thapaliya, A.
2016-07-01
We present procedures based on Bayesian statistics for estimating, from data, the parameters of effective field theories (EFTs). The extraction of low-energy constants (LECs) is guided by theoretical expectations in a quantifiable way through the specification of Bayesian priors. A prior for natural-sized LECs reduces the possibility of overfitting, and leads to a consistent accounting of different sources of uncertainty. A set of diagnostic tools is developed that analyzes the fit and ensures that the priors do not bias the EFT parameter estimation. The procedures are illustrated using representative model problems, including the extraction of LECs for the nucleon-mass expansion in SU(2) chiral perturbation theory from synthetic lattice data.
BONNSAI: correlated stellar observables in Bayesian methods
Schneider, F R N; Fossati, L; Langer, N; de Koter, A
2016-01-01
In an era of large spectroscopic surveys of stars and big data, sophisticated statistical methods become more and more important in order to infer fundamental stellar parameters such as mass and age. Bayesian techniques are powerful methods because they can match all available observables simultaneously to stellar models while taking prior knowledge properly into account. However, in most cases it is assumed that observables are uncorrelated which is generally not the case. Here, we include correlations in the Bayesian code BONNSAI by incorporating the covariance matrix in the likelihood function. We derive a parametrisation of the covariance matrix that, in addition to classical uncertainties, only requires the specification of a correlation parameter that describes how observables co-vary. Our correlation parameter depends purely on the method with which observables have been determined and can be analytically derived in some cases. This approach therefore has the advantage that correlations can be accounte...
The Size-Weight Illusion is not anti-Bayesian after all: a unifying Bayesian account.
Peters, Megan A K; Ma, Wei Ji; Shams, Ladan
2016-01-01
When we lift two differently-sized but equally-weighted objects, we expect the larger to be heavier, but the smaller feels heavier. However, traditional Bayesian approaches with "larger is heavier" priors predict the smaller object should feel lighter; this Size-Weight Illusion (SWI) has thus been labeled "anti-Bayesian" and has stymied psychologists for generations. We propose that previous Bayesian approaches neglect the brain's inference process about density. In our Bayesian model, objects' perceived heaviness relationship is based on both their size and inferred density relationship: observers evaluate competing, categorical hypotheses about objects' relative densities, the inference about which is then used to produce the final estimate of weight. The model can qualitatively and quantitatively reproduce the SWI and explain other researchers' findings, and also makes a novel prediction, which we confirmed. This same computational mechanism accounts for other multisensory phenomena and illusions; that the SWI follows the same process suggests that competitive-prior Bayesian inference can explain human perception across many domains.
Bayesian nonparametric regression with varying residual density
Pati, Debdeep; Dunson, David B.
2013-01-01
We consider the problem of robust Bayesian inference on the mean regression function allowing the residual density to change flexibly with predictors. The proposed class of models is based on a Gaussian process prior for the mean regression function and mixtures of Gaussians for the collection of residual densities indexed by predictors. Initially considering the homoscedastic case, we propose priors for the residual density based on probit stick-breaking (PSB) scale mixtures and symmetrized ...
Towards Bayesian Deep Learning: A Survey
Wang, Hao; Yeung, Dit-Yan
2016-01-01
While perception tasks such as visual object recognition and text understanding play an important role in human intelligence, the subsequent tasks that involve inference, reasoning and planning require an even higher level of intelligence. The past few years have seen major advances in many perception tasks using deep learning models. For higher-level inference, however, probabilistic graphical models with their Bayesian nature are still more powerful and flexible. To achieve integrated intel...
Approximate Bayesian inference for complex ecosystems
Michael P H Stumpf
2014-01-01
Mathematical models have been central to ecology for nearly a century. Simple models of population dynamics have allowed us to understand fundamental aspects underlying the dynamics and stability of ecological systems. What has remained a challenge, however, is to meaningfully interpret experimental or observational data in light of mathematical models. Here, we review recent developments, notably in the growing field of approximate Bayesian computation (ABC), that allow us to calibrate mathe...
Forming Object Concept Using Bayesian Network
Nakamura, Tomoaki; Nagai, Takayuki
2010-01-01
This chapter hase discussed a novel framework for object understanding. Implementation of the proposed framework using Bayesian Network has been presented. Although the result given in this paper is preliminary one, we have shown that the system can form object concept by observing the performance by human hands. The on-line learning is left for the future works. Moreover the model should be extended so that it can represent the object usage and work objects.
Bayesian belief networks in business continuity.
Phillipson, Frank; Matthijssen, Edwin; Attema, Thomas
2014-01-01
Business continuity professionals aim to mitigate the various challenges to the continuity of their company. The goal is a coherent system of measures that encompass detection, prevention and recovery. Choices made in one part of the system affect other parts as well as the continuity risks of the company. In complex organisations, however, these relations are far from obvious. This paper proposes the use of Bayesian belief networks to expose these relations, and presents a modelling framework for this approach. PMID:25193453
Informed Source Separation: A Bayesian Tutorial
Knuth, Kevin
2013-01-01
Source separation problems are ubiquitous in the physical sciences; any situation where signals are superimposed calls for source separation to estimate the original signals. In this tutorial I will discuss the Bayesian approach to the source separation problem. This approach has a specific advantage in that it requires the designer to explicitly describe the signal model in addition to any other information or assumptions that go into the problem description. This leads naturally to the idea...
Market Segmentation Using Bayesian Model Based Clustering
Van Hattum, P.
2009-01-01
This dissertation deals with two basic problems in marketing, that are market segmentation, which is the grouping of persons who share common aspects, and market targeting, which is focusing your marketing efforts on one or more attractive market segments. For the grouping of persons who share common aspects a Bayesian model based clustering approach is proposed such that it can be applied to data sets that are specifically used for market segmentation. The cluster algorithm can handle very l...
Approximate Bayesian computation in population genetics.
Beaumont, Mark A; Zhang, Wenyang; Balding, David J.
2002-01-01
We propose a new method for approximate Bayesian statistical inference on the basis of summary statistics. The method is suited to complex problems that arise in population genetics, extending ideas developed in this setting by earlier authors. Properties of the posterior distribution of a parameter, such as its mean or density curve, are approximated without explicit likelihood calculations. This is achieved by fitting a local-linear regression of simulated parameter values on simulated summ...
Bayesian nonparametric duration model with censorship
Directory of Open Access Journals (Sweden)
Joseph Hakizamungu
2007-10-01
Full Text Available This paper is concerned with nonparametric i.i.d. durations models censored observations and we establish by a simple and unified approach the general structure of a bayesian nonparametric estimator for a survival function S. For Dirichlet prior distributions, we describe completely the structure of the posterior distribution of the survival function. These results are essentially supported by prior and posterior independence properties.
Bayesian modeling and classification of neural signals
Lewicki, Michael S.
1994-01-01
Signal processing and classification algorithms often have limited applicability resulting from an inaccurate model of the signal's underlying structure. We present here an efficient, Bayesian algorithm for modeling a signal composed of the superposition of brief, Poisson-distributed functions. This methodology is applied to the specific problem of modeling and classifying extracellular neural waveforms which are composed of a superposition of an unknown number of action potentials CAPs). ...
Bayesian Estimation and Inference Using Stochastic Electronics.
Thakur, Chetan Singh; Afshar, Saeed; Wang, Runchun M; Hamilton, Tara J; Tapson, Jonathan; van Schaik, André
2016-01-01
In this paper, we present the implementation of two types of Bayesian inference problems to demonstrate the potential of building probabilistic algorithms in hardware using single set of building blocks with the ability to perform these computations in real time. The first implementation, referred to as the BEAST (Bayesian Estimation and Stochastic Tracker), demonstrates a simple problem where an observer uses an underlying Hidden Markov Model (HMM) to track a target in one dimension. In this implementation, sensors make noisy observations of the target position at discrete time steps. The tracker learns the transition model for target movement, and the observation model for the noisy sensors, and uses these to estimate the target position by solving the Bayesian recursive equation online. We show the tracking performance of the system and demonstrate how it can learn the observation model, the transition model, and the external distractor (noise) probability interfering with the observations. In the second implementation, referred to as the Bayesian INference in DAG (BIND), we show how inference can be performed in a Directed Acyclic Graph (DAG) using stochastic circuits. We show how these building blocks can be easily implemented using simple digital logic gates. An advantage of the stochastic electronic implementation is that it is robust to certain types of noise, which may become an issue in integrated circuit (IC) technology with feature sizes in the order of tens of nanometers due to their low noise margin, the effect of high-energy cosmic rays and the low supply voltage. In our framework, the flipping of random individual bits would not affect the system performance because information is encoded in a bit stream. PMID:27047326
Bayesian biclustering of gene expression data
Liu Jun S; Gu Jiajun
2008-01-01
Abstract Background Biclustering of gene expression data searches for local patterns of gene expression. A bicluster (or a two-way cluster) is defined as a set of genes whose expression profiles are mutually similar within a subset of experimental conditions/samples. Although several biclustering algorithms have been studied, few are based on rigorous statistical models. Results We developed a Bayesian biclustering model (BBC), and implemented a Gibbs sampling procedure for its statistical in...
Nonparametric Bayesian Storyline Detection from Microtexts
Krishnan, Vinodh; Eisenstein, Jacob
2016-01-01
News events and social media are composed of evolving storylines, which capture public attention for a limited period of time. Identifying these storylines would enable many high-impact applications, such as tracking public interest and opinion in ongoing crisis events. However, this requires integrating temporal and linguistic information, and prior work takes a largely heuristic approach. We present a novel online non-parametric Bayesian framework for storyline detection, using the distance...