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.
Directory of Open Access Journals (Sweden)
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.
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.
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...
Mueller, Julie M.; Loomis, John B.
2010-01-01
The choice of weights is a non-nested problem in most applied spatial econometric models. Despite numerous recent advances in spatial econometrics, the choice of spatial weights remains exogenously determined by the researcher in empirical applications. Bayesian techniques provide statistical evidence regarding the simultaneous choice of model specification and spatial weights matrices by using posterior probabilities. This paper demonstrates the Bayesian estimation approach in a spatial hedo...
New insights into the phylogeny of fig pollinators using Bayesian analyses.
Jiang, Zi-Feng; Huang, Da-Wei; Zhu, Chao-Dong; Zhen, Wen-Quan
2006-02-01
The interaction between figs and fig pollinators is one of the most species-specific mutualisms. Recently, phylogenies of both partners based on molecular data provided insights into a wide spectrum of co-evolutionary questions. However, for the phylogeny of fig pollinators, there are some discrepancies between different studies and left some relationships unresolved, especially for deep nodes. The phylogenetic uncertainties of pollinators prohibit our further understanding of the history of the mutualism. Here, we present phylogenetic analyses of a larger COI sequence dataset that includes previously published datasets and our sequences from 20 species using Bayesian method and maximum parsimony. The analyses using different methods share similar topologies. Bayesian analyses provide high level of confidence for most internal nodes in terms of posterior probability. This study also clarifies some discrepancies between previous studies. After rooting with Tetrapus, other pollinators split into two clades. Wiebesia and Blastophaga are at basal positions in respective clade. Ceratosolen is not monophyletic because Kradibia and Liporrhopalum fall inside this group. Three subgenera of Ceratosolen: subgen. Ceratosolen, subgen. Rothropus, and subgen. Strepitus are not supported. Therefore, Ceratosolen is suggested to be re-divided into three groups. Urostigma pollinators (including Dolichoris and Blastophaga psenes) are clustered together. The monophylies of Wiebesia, Blastophaga, Dolichoris are not supported in this analysis. This study also provides a new framework for re-evaluating character evolution and re-inspecting the definition of some genera. PMID:16364663
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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.
Directory of Open Access Journals (Sweden)
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.
Simulation of Salamander Locomotion
Viazzi, Stefano
2008-01-01
As part of the research on locomotion controller that aims to produce robots whose design is inspired by Nature, this thesis intends to develop a simulator of the salamander locomotion. It investigates, in particular, what type of circuitry can produce and modulate the neural activity for swimming and trotting. In water, the animal moves by propagating a traveling wave of muscular contractions along the body while holding the limbs against it in an undulatory gait. On the ground, instead, the...
An application of the 'Bayesian cohort model' to nuclear power plant cost analyses
International Nuclear Information System (INIS)
We have developed a new method for identifying the effects of calendar year, plant age and commercial operation starting year on the costs and performances of nuclear power plants and also developed an analysis system running on personal computers. The method extends the Bayesian cohort model for time series social survey data proposed by one of the authors. The proposed method was shown to be able to separate the above three effects more properly than traditional methods such as taking simple means by time domain. The analyses of US nuclear plant cost and performance data by using the proposed method suggest that many of the US plants spent relatively long time and much capital cost for modification at their age of about 10 to 20 years, but that, after those ages, they performed fairly well with lower and stabilized O and M and additional capital costs. (author)
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
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
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
Bayesian Synthesis: Combining subjective analyses, with an application to ozone data
Yu, Qingzhao; MacEachern, Steven N.; Peruggia, Mario
2011-01-01
Bayesian model averaging enables one to combine the disparate predictions of a number of models in a coherent fashion, leading to superior predictive performance. The improvement in performance arises from averaging models that make different predictions. In this work, we tap into perhaps the biggest driver of different predictions—different analysts—in order to gain the full benefits of model averaging. In a standard implementation of our method, several data analysts work independently on p...
Directory of Open Access Journals (Sweden)
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.
Forecasting neutrino masses from combining KATRIN and the CMB: Frequentist and Bayesian analyses
Host, Ole; Lahav, Ofer; Abdalla, Filipe B.; Eitel, Klaus
2007-01-01
We present a showcase for deriving bounds on the neutrino masses from laboratory experiments and cosmological observations. We compare the frequentist and Bayesian bounds on the effective electron neutrino mass m_beta which the KATRIN neutrino mass experiment is expected to obtain, using both an analytical likelihood function and Monte Carlo simulations of KATRIN. Assuming a uniform prior in m_beta, we find that a null result yields an upper bound of about 0.17 eV at 90% confidence in the Bay...
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.
Malyarchuk, Boris; Derenko, Miroslava; Denisova, Galina
2013-05-01
We assessed phylogeny of the Siberian salamander (Salamandrella keyserlingii, Dybowski, 1870), the most northern ectothermic, terrestrial vertebrate in Eurasia, by sequence analysis of complete mitochondrial genomes in 26 specimens from different localities (China, Khabarovsk region, Sakhalin, Yakutia, Magadan region, Chukotka, Kamchatka, Ural, European part of Russia). In addition, a complete mitochondrial genome of the Schrenck salamander, Salamandrella schrenckii, was determined for the first time. Bayesian phylogenetic analysis of the entire mtDNA genomes of S. keyserlingii demonstrates that two haplotype clades, AB and C, radiated about 1.4 million years ago (Mya). Bayesian skyline plots of population size change through time show an expansion around 250 thousand years ago (kya) and then a decline around the Last Glacial Maximum (25 kya) with subsequent restoration of population size. Climatic changes during the Quaternary period have dramatically affected the population genetic structure of the Siberian salamanders. In addition, complete mtDNA sequence analysis allowed us to recognize that the vast area of Northern Eurasia was colonized only by the Siberian salamander clade C1b during the last 150 kya. Meanwhile, we were unable to find evidence of molecular adaptation in this clade by analyzing the whole mitochondrial genomes of the Siberian salamanders. PMID:23415986
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
'Salamander plague' on Britain's doorstep.
Mills, Georgina
2015-01-24
Chytridiomycosis can cause mass declines in amphibians, and the chytrid fungus Batrachochytrium dendrobatidis is the classic cause of this disease. However, recently, a second strain of chytrid fungus has emerged in Europe, resulting in major declines in fire salamanders. The Zoological Society of London (ZSL) discussed this, and the implications for the UK, at a meeting in December in London. Georgina Mills reports. PMID:25614547
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.
Ambystoma maculatum (spotted salamander). Reproduction
Glorioso, Brad M.; Waddle, Hardin; Hefner, Jeromi
2012-01-01
The Spotted Salamander is a wide-ranging salamander of the eastern United States that typically breeds in winter or early spring in ephemeral pools in lowland forests. Ambystoma maculatum is known to deposit 2-4 egg masses per year, each containing 1-250 eggs. As part of ongoing research into the ecology and reproductive biology of Spotted Salamanders in the Kisatchie District of Kisatchie National Forest in Natchitoches Parish, Louisiana, USA, we have been counting the number of embryos per egg mass. We captured seven female A. maculatum in a small pool, six of which were still gravid. We took standard measurements, including SVL, and then implanted a Passive Integrated Transponder (PIT tag) into each adult female as was the protocol. About an hour after processing these animals we marked new A. maculatum egg masses found in the same small pool using PVC pin flags pushed carefully through the outer jelly. We did not have enough time to process them that evening, and it was not until a few days later that we photographed those masses. We discovered that one of the masses contained a PIT tag in the outer jelly that corresponded to one of the six gravid females that were marked that same evening. To our knowledge, this is the first report of PIT tags being the means, albeit coincidentally, by which a particular egg mass of Ambystoma maculatum has been assigned to a particular female. For our purposes, losing the PIT tag from the adult female is counter to the goals of our study of this population, and we will no longer be implanting PIT tags into gravid females.
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.
Deep divergences and extensive phylogeographic structure in a clade of lowland tropical salamanders
Rovito, Sean M; Parra-Olea, Gabriela; Vásquez-Almazán, Carlos R.; Luna-Reyes, Roberto; Wake, David B.
2012-01-01
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 geo...
Invasive Asian Earthworms Negatively Impact Keystone Terrestrial Salamanders
Ziemba, Julie L.
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
Salvidio, Sebastiano; Oneto, Fabrizio; Ottonello, Dario; Pastorino, Mauro V.
2016-04-01
The North Atlantic Oscillation (NAO) is a large-scale climatic pattern that strongly influences the atmospheric circulation in the northern Hemisphere and by consequence the long-term variability of marine and terrestrial ecosystem over great part of northern Europe and western Mediterranean. In the Mediterranean, the effects of the NAO on vertebrates has been studied mainly on bird populations but was rarely analysed in ectothermic animals, and in particular in amphibians. In this study, we investigated the relationships between winter, spring and summer NAO indexes and the long-term population dynamics of the plethodontid salamander Speleomantes strinatii. This terrestrial salamander was monitored inside an artificial cave in NW Italy for 24 consecutive years. The relationships between seasonal NAO indexes and the salamander dynamics were assessed by cross-correlation function (CCF) analysis, after prewhitening the time series by autoregressive moving average statistical modelling. Results of CCF analyses indicated that the salamander abundance varied in relation to the one-year ahead winter NAO ( P = 0.018), while no relationships were found with spring and summer indexes. These results strengthen some previous findings that suggested a high sensitivity of temperate terrestrial amphibians to wintertime climatic conditions.
Effects of timber harvests and silvicultural edges on terrestrial salamanders.
MacNeil, Jami E; Williams, Rod N
2014-01-01
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 (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 seasons and years. Long
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, 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
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, 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
Deep divergences and extensive phylogeographic structure in a clade of lowland tropical salamanders
Rovito Sean M; Parra-Olea Gabriela; Vásquez-Almazán Carlos R; Luna-Reyes Roberto; Wake David B
2012-01-01
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 b...
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.
Effects of red-backed salamanders on ecosystem functions.
Directory of Open Access Journals (Sweden)
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.
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
Shen, Xing-Xing; Liang, Dan; Chen, Meng-Yun; Mao, Rong-Li; Wake, David B; Zhang, Peng
2016-01-01
Deep phylogenetic relationships of the largest salamander family Plethodontidae have been difficult to resolve, probably reflecting a rapid diversification early in their evolutionary history. Here, data from 50 independent nuclear markers (total 48,582 bp) are used to reconstruct the phylogeny and divergence times for plethodontid salamanders, using both concatenation and coalescence-based species tree analyses. Our results robustly resolve the position of the enigmatic eastern North American four-toed salamander (Hemidactylium) as the sister taxon of Batrachoseps + Tribe Bolitoglossini, thus settling a long-standing question. Furthermore, we statistically reject sister taxon status of Karsenia and Hydromantes, the only plethodontids to occur outside the Americas, leading us to new biogeographic hypotheses. Contrary to previous long-standing arguments that plethodontid salamanders are an old lineage originating in the Cretaceous (more than 90 Ma), our analyses lead to the hypothesis that these salamanders are much younger, arising close to the K-T boundary (~66 Ma). These time estimates are highly stable using alternative calibration schemes and dating methods. Our data simulation highlights the potential risk of making strong arguments about phylogenetic timing based on inferences from a handful of nuclear genes, a common practice. Based on the newly obtained timetree and ancestral area reconstruction results, we argue that (i) the classic "Out of Appalachia" hypothesis of plethodontid origins is problematic; (ii) the common ancestor of extant plethodontids may have originated in northwestern North America in the early Paleocene; (iii) origins of Eurasian plethodontids likely result from two separate dispersal events from western North America via Beringia in the late Eocene (~42 Ma) and the early Miocene (~23 Ma), respectively. PMID:26385618
Final Critical Habitat for the San Marcos salamander (Eurycea nana)
US Fish and Wildlife Service, Department of the Interior — To provide the user with a general idea of areas where final critical habitat for San Marcos salamander (Eurycea nana) occur based on the description provided in...
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 along...
Streamside Salamander Inventory and Monitoring Northeast Refuges Summer 2001
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 along...
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 along...
Streamside Salamander Inventory and Monitoring Northeast Refuges Summer 2004
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 along...
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).
Effects of Timber Harvests and Silvicultural Edges on Terrestrial Salamanders
MacNeil, Jami E.; Williams, Rod N.
2014-01-01
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 th...
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.
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
Directory of Open Access Journals (Sweden)
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.
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
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.
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
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
Chatfield, Matthew W. H.; Moler, Paul; Richards-Zawacki, Corinne L.
2012-01-01
Little is known about the impact that the pathogenic amphibian chytrid fungus, Batrachochytrium dendrobatidis (Bd), has on fully aquatic salamander species of the eastern United States. As a first step in determining the impacts of Bd on these species, we aimed to determine the prevalence of Bd in wild populations of fully aquatic salamanders in the genera Amphiuma, Necturus, Pseudobranchus, and Siren. We sampled a total of 98 salamanders, representing nine species from sites in Florida, Miss...
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.
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.
Kirstein, Roland
2005-01-01
This paper presents a modification of the inspection game: The ?Bayesian Monitoring? model rests on the assumption that judges are interested in enforcing compliant behavior and making correct decisions. They may base their judgements on an informative but imperfect signal which can be generated costlessly. In the original inspection game, monitoring is costly and generates a perfectly informative signal. While the inspection game has only one mixed strategy equilibrium, three Perfect Bayesia...
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
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...
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.
Cannibalistic-morph Tiger Salamanders in unexpected ecological contexts
McLean, Kyle I.; Stockwell, Craig A.; Mushet, David M.
2016-01-01
Barred tiger salamanders [Ambystoma mavortium (Baird, 1850)] exhibit two trophic morphologies; a typical and a cannibalistic morph. Cannibalistic morphs, distinguished by enlarged vomerine teeth, wide heads, slender bodies, and cannibalistic tendencies, are often found where conspecifics occur at high density. During 2012 and 2013, 162 North Dakota wetlands and lakes were sampled for salamanders. Fifty-one contained A. mavortium populations; four of these contained cannibalistic morph individuals. Two populations with cannibalistic morphs occurred at sites with high abundances of conspecifics. However, the other two populations occurred at sites with unexpectedly low conspecific but high fathead minnow [Pimephales promelas (Rafinesque, 1820)] abundances. Further, no typical morphs were observed in either of these later two populations, contrasting with earlier research suggesting cannibalistic morphs only occur at low frequencies in salamander populations. Another anomaly of all four populations was the occurrence of cannibalistic morphs in permanent water sites, suggesting their presence was due to factors other than faster growth allowing them to occupy ephemeral habitats. Therefore, our findings suggest environmental factors inducing the cannibalistic morphism may be more complex than previously thought.
Directory of Open Access Journals (Sweden)
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
2012-06-18
... Fish and Wildlife Service Proposed Low-Effect Habitat Conservation Plan for the California Tiger... listed animal, the threatened Central California Distinct Population Segment of the California tiger salamander (tiger salamander). The applicant would implement a conservation program to minimize and...
International Nuclear Information System (INIS)
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).
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
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...
Environmental influences on egg and clutch sizes in lentic- and lotic-breeding salamanders
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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.
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
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...... 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...
Maliarchuk, B A; Derenko, M V; Denisova, G A
2015-01-01
Based on sequence variation of three nuclear genome genes (BDNF, POMC, and RAG1), the phylogenetic relationships among Asiatic salamanders of the genus Salamandrella, Siberian salamander (S. keyserlingii) and Schrenk salamander (S. schrenkii), were examined. Both species demonstrated high levels of heterozygosity determined by intraspecific polymorphism. Fixed interspecific differences were revealed at one nucleotide position of the RAG1 gene, and thus the level of interspecific divergence over the three genes constituted only 0.04%. Analysis of the RAG1 polymorphism across the whole range of S. keyserlingii showed that only one gene variant, encoding for modified RAG1 recombinase, had the highest distribution to the north of the Amur region (west and northeast of Siberia). It is possible that the changes in the RAG1 gene in Siberian salamander are of an adaptive nature. However, cases of interspecific hybridization were identified in Jewish autonomous oblast (JAO), which contains one of the range borders between the two Salamandrella species. PMID:25857197
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...
Egg predators of an endemic Italian salamander, Salamandrina perspicillata (Savi, 1821
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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.
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...
Muletz, Carly; Nicholas M Caruso; Fleischer, Robert C; Roy W McDiarmid; 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 Amer...
Loudon, Andrew H.; Douglas C Woodhams; Parfrey, Laura Wegener; Archer, Holly; Knight, Rob; McKenzie, Valerie; Harris, Reid N.
2013-01-01
Beneficial cutaneous bacteria on amphibians can protect against the lethal disease chytridiomycosis, which has devastated many amphibian species and is caused by the fungus Batrachochytrium dendrobatidis. We describe the diversity of bacteria on red-backed salamanders (Plethodon cinereus) in the wild and the stability of these communities through time in captivity using culture-independent Illumina 16S rRNA gene sequencing. After field sampling, salamanders were housed with soil from the fiel...
Cutaneous Bacteria of the Redback Salamander Prevent Morbidity Associated with a Lethal Disease
Matthew H Becker; Harris, Reid N.
2010-01-01
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 s...
Reintroduction and Post-Release Survival of a Living Fossil: The Chinese Giant Salamander.
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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
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
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...
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.
Peterman, W E; Semlitsch, R D
2014-10-01
Many patterns observed in ecology, such as species richness, life history variation, habitat use, and distribution, have physiological underpinnings. For many ectothermic organisms, temperature relationships shape these patterns, but for terrestrial amphibians, water balance may supersede temperature as the most critical physiologically limiting factor. Many amphibian species have little resistance to water loss, which restricts them to moist microhabitats, and may significantly affect foraging, dispersal, and courtship. Using plaster models as surrogates for terrestrial plethodontid salamanders (Plethodon albagula), we measured water loss under ecologically relevant field conditions to estimate the duration of surface activity time across the landscape. Surface activity time was significantly affected by topography, solar exposure, canopy cover, maximum air temperature, and time since rain. Spatially, surface activity times were highest in ravine habitats and lowest on ridges. Surface activity time was a significant predictor of salamander abundance, as well as a predictor of successful recruitment; the probability of a juvenile salamander occupying an area with high surface activity time was two times greater than an area with limited predicted surface activity. Our results suggest that survival, recruitment, or both are demographic processes that are affected by water loss and the ability of salamanders to be surface-active. Results from our study extend our understanding of plethodontid salamander ecology, emphasize the limitations imposed by their unique physiology, and highlight the importance of water loss to spatial population dynamics. These findings are timely for understanding the effects that fluctuating temperature and moisture conditions predicted for future climates will have on plethodontid salamanders. PMID:25154754
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
Leaf litter bags as an index to populations of northern two-lined salamanders (Eurycea bislineata)
Chalmers, R.J.; Droege, S.
2002-01-01
Concern about recent amphibian declines has led to research on amphibian populations, but few statistically tested, standardized methods of counting amphibians exist. We tested whether counts of northern two-lined salamander larvae (Eurycea bislineata) sheltered in leaf litter bags--a relatively new, easily replicable survey technique--had a linear correlation to total number of larvae. Using experimental enclosures placed in streams, we compared number of salamanders found in artificial habitat (leaf litter bags) with total number of salamanders in each enclosure. Low numbers of the animals were found in leaf litter bags, and the relative amount of variation in the index (number of animals in leaf litter bags compared to total number of animals in stream enclosures) was high. The index of salamanders in leaf litter bags was not significantly related to total number of salamanders in enclosures for two-thirds of the replicates or with pooled replicates (P= 0.066). Consequently, we cannot recommend using leaf litter bags to index populations of northern two-lined salamanders.
Deep divergences and extensive phylogeographic structure in a clade of lowland tropical salamanders
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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
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
Rubin, Donald B.
1981-01-01
The Bayesian bootstrap is the Bayesian analogue of the bootstrap. Instead of simulating the sampling distribution of a statistic estimating a parameter, the Bayesian bootstrap simulates the posterior distribution of the parameter; operationally and inferentially the methods are quite similar. Because both methods of drawing inferences are based on somewhat peculiar model assumptions and the resulting inferences are generally sensitive to these assumptions, neither method should be applied wit...
Hess, Alexandra; McAllister, Caroline; DeMarchi, Joseph; Zidek, Makenzie; Murone, Julie; Venesky, Matthew D
2015-10-27
Immune function is a costly line of defense against parasitism. When infected with a parasite, hosts frequently lose mass due to these costs. However, some infected hosts (e.g. highly resistant individuals) can clear infections with seemingly little fitness losses, but few studies have tested how resistant hosts mitigate these costly immune defenses. We explored this topic using eastern red-backed salamanders Plethodon cinereus and the fungal pathogen Batrachochytrium dendrobatidis (Bd). Bd is generally lethal for amphibians, and stereotypical symptoms of infection include loss in mass and deficits in feeding. However, individuals of P. cinereus can clear their Bd infections with seemingly few fitness costs. We conducted an experiment in which we repeatedly observed the feeding activity of Bd-infected and non-infected salamanders. We found that Bd-infected salamanders generally increased their feeding activity compared to non-infected salamanders. The fact that we did not observe any differences in mass change between the treatments suggests that increased feeding might help Bd-infected salamanders minimize the costs of an effective immune response. PMID:26503775
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
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
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
Zhang, H; Guo, X; Zhong, S; Ge, T; Peng, S; Yu, P; Zhou, Z
2015-01-01
The Chinese giant salamander belongs to an old lineage of salamanders and endangered species. Many studies of breeding and disease regarding this amphibian had been implemented. However, the studies on the ultrastructure of this amphibian are rare. In this work, we provide a histological and ultrastructural investigation on posterior esophagus of Chinese giant salamander. The sections of amphibian esophagus were stained by hematoxylin & eosin (H&E). Moreover, the esophageal epithelium was observed by transmission electron microscopy (TEM). The results showed that esophageal epithelium was a single layer epithelium, which consisted of mucous cells and columnar cells. The esophageal glands were present in submucosa. The columnar cells were ciliated. According to the diverging ultrastructure of mucous vesicles, three types of mucous cells could be identified in the esophageal mucosa: i) electron-lucent vesicles mucous cell (ELV-MC); ii) electron-dense vesicles mucous cell (EDV-MC); and iii) mixed vesicles mucous cell (MV-MC). PMID:26428885
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H. Zhang
2015-08-01
Full Text Available The Chinese giant salamander belongs to an old lineage of salamanders and endangered species. Many studies of breeding and disease regarding this amphibian had been implemented. However, the studies on the ultrastructure of this amphibian are rare. In this work, we provide a histological and ultrastructural investigation on posterior esophagus of Chinese giant salamander. The sections of amphibian esophagus were stained by hematoxylin & eosin (H&E. Moreover, the esophageal epithelium was observed by transmission electron microscopy (TEM. The results showed that esophageal epithelium was a single layer epithelium, which consisted of mucous cells and columnar cells. The esophageal glands were present in submucosa. The columnar cells were ciliated. According to the diverging ultrastructure of mucous vesicles, three types of mucous cells could be identified in the esophageal mucosa: i electron-lucent vesicles mucous cell (ELV-MC; ii electron-dense vesicles mucous cell (EDV-MC; and iii mixed vesicles mucous cell (MV-MC.
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
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…
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.
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
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
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...
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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.
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Matthew W H Chatfield
Full Text Available Little is known about the impact that the pathogenic amphibian chytrid fungus, Batrachochytrium dendrobatidis (Bd, has on fully aquatic salamander species of the eastern United States. As a first step in determining the impacts of Bd on these species, we aimed to determine the prevalence of Bd in wild populations of fully aquatic salamanders in the genera Amphiuma, Necturus, Pseudobranchus, and Siren. We sampled a total of 98 salamanders, representing nine species from sites in Florida, Mississippi, and Louisiana. Overall, infection prevalence was found to be 0.34, with significant differences among genera but no clear geographic pattern. We also found evidence for seasonal variation, but additional sampling throughout the year is needed to clarify this pattern. The high rate of infection discovered in this study is consistent with studies of other amphibians from the southeastern United States. Coupled with previously published data on life histories and population densities, the results presented here suggest that fully aquatic salamanders may be serving as important vectors of Bd and the interaction between these species and Bd warrants additional research.
Cutaneous bacteria of the redback salamander prevent morbidity associated with a lethal disease.
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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.
Cutaneous bacteria of the redback salamander prevent morbidity associated with a lethal disease.
Becker, Matthew H; Harris, Reid N
2010-01-01
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. PMID:20532032
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].
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.
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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.
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
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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
A Bayesian Modelling of Wildfires in Portugal
Silva, Giovani L.; Soares, Paulo; Marques, Susete; Dias, Inês M.; Oliveira, Manuela M.; Borges, Guilherme J.
2015-01-01
In the last decade wildfires became a serious problem in Portugal due to different issues such as climatic characteristics and nature of Portuguese forest. In order to analyse wildfire data, we employ beta regression for modelling the proportion of burned forest area, under a Bayesian perspective. Our main goal is to find out fire risk factors that influence the proportion of area burned and what may make a forest type susceptible or resistant to fire. Then, we analyse wildfire...
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.
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 exploratory factor analysis
Gabriella Conti; Sylvia Frühwirth-Schnatter; James Heckman; Rémi Piatek
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 corresponding factor loadings. Classical identifi cation criteria are applied and integrated into our Bayesian procedure to generate models that are stable and clearly interpretable. A Monte Carlo study c...
Bayesian Exploratory Factor Analysis
Conti, Gabriella; Frühwirth-Schnatter, Sylvia; Heckman, James J.; Piatek, Rémi
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 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 co...
Bayesian Exploratory Factor Analysis
Gabriella Conti; Sylvia Fruehwirth-Schnatter; Heckman, James J.; Remi Piatek
2014-01-01
This paper develops and applies a Bayesian approach to Exploratory Factor Analysis that improves on \\emph{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 s...
Bayesian exploratory factor analysis
Conti, Gabriella; Frühwirth-Schnatter, Sylvia; Heckman, James J.; Piatek, Rémi
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 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 st...
Bayesian exploratory factor analysis
Conti, Gabriella; Frühwirth-Schnatter, Sylvia; Heckman, James; Piatek, Rémi
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 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 co...
Carbonetto, Peter; Kisynski, Jacek; De Freitas, Nando; Poole, David L
2012-01-01
The Bayesian Logic (BLOG) language was recently developed for defining first-order probability models over worlds with unknown numbers of objects. It handles important problems in AI, including data association and population estimation. This paper extends BLOG by adopting generative processes over function spaces - known as nonparametrics in the Bayesian literature. We introduce syntax for reasoning about arbitrary collections of objects, and their properties, in an intuitive manner. By expl...
Bayesian default probability models
Andrlíková, Petra
2014-01-01
This paper proposes a methodology for default probability estimation for low default portfolios, where the statistical inference may become troublesome. The author suggests using logistic regression models with the Bayesian estimation of parameters. The piecewise logistic regression model and Box-Cox transformation of credit risk score is used to derive the estimates of probability of default, which extends the work by Neagu et al. (2009). The paper shows that the Bayesian models are more acc...
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
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.
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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.
Bayesian phylogeography finds its roots.
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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.
Geng, Y; Wang, K Y; Zhou, Z Y; Li, C W; Wang, J; He, M; Yin, Z Q; Lai, W M
2011-07-01
From February to May 2010, an outbreak of disease occurred amongst farmed Chinese giant salamanders (Andrias davidianus) in Hanzhong County, Shanxi Province, China. Clinical signs included anorexia, lethargy, ecchymoses and swollen areas on the head and limbs, and skin ulceration. The aim of this study was to determine the cause of this disease. Necropsy examination revealed subcutaneous and intramuscular oedema, swollen and pale livers with multifocal haemorrhage, swollen kidneys with multifocal haemorrhage and distended fluid-filled intestines with areas of haemorrhage. Light microscopy revealed intracytoplasmic inclusions suggestive of a viral infection in a variety of organs, as well as degeneration and necrosis of these organs. Electron microscopy of ultrathin sections of the same tissues revealed iridovirus-like particles within the inclusions. Of the six specimens tested, all were positive for ranavirus major capsid protein (MCP) gene. Sequence alignments of the ranavirus MCP gene from these specimens showed 95-98% similarity with published ranavirus data. The virus, provisionally designated as Chinese giant salamander virus (CGSV), was isolated from tissue homogenates of diseased salamanders following inoculation of epithelioma papilloma cyprini cells. Sequence analysis of the MCP genes showed that the isolated virus was a ranavirus with marked sequence identity to other members of the genus Ranavirus. Koch's postulates were fulfilled by infecting healthy Chinese giant salamanders with the CGSV. These salamanders all died within 6-8 days. This is the first report of ranavirus infection associated with mass mortality in Chinese giant salamanders. PMID:21256507
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。
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.
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.
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 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
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 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 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...... 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...
A survey of current Bayesian gene mapping method
Molitor John; Marjoram Paul; Conti David; Thomas Duncan
2004-01-01
Abstract Recently, there has been much interest in the use of Bayesian statistical methods for performing genetic analyses. Many of the computational difficulties previously associated with Bayesian analysis, such as multidimensional integration, can now be easily overcome using modern high-speed computers and Markov chain Monte Carlo (MCMC) methods. Much of this new technology has been used to perform gene mapping, especially through the use of multi-locus linkage disequilibrium techniques. ...
Malyarchuk, B A; Denisova, G A; Derenko, M V
2013-07-01
Processed copies of genes generally evolve in neutral mode as pseudogenes, however, some of them might be important sources of new functional genes. The psiPGK1 pseudogene has been discovered in Schrenck salamander (Salamandrella schrenckii, Amphibia, Caudata, Hynobiidae) via polymerase chain reaction used to amplify the phosphoglycerate kinase 1 gene (PGK1). This pseudogene is an intronless copy of PGK1 gene absent of exon 6. Analysis of psiPGK1 pseudogene polymorphism has demonstrated that it lacks mutations, which results in shifts in the stop codons and reading frames, as well as that the interspecies variation of this pseudogene was inconsistent with the neutral model of evolution. In addition, the pattern of phylogeographic differentiation of the psiPGK1 variants mainly coincides with that observed in mitochondrial DNA. These observations allow it to be suggested that the psiPGK1 pseudogene is a new functional gene in the Schrenck salamander. PMID:24450152
Bank, M. S.; Crocker, J.; Wachtl, J.; Kleeman, P.; Fellers, G.; Currens, C.; Hothem, R.; Madej, M. A.
2014-12-01
Mercury (Hg) contamination of stream salamanders in the Pacific Northwest region of the United States has received little attention. Here we report total Hg (HgT) and methyl mercury (MeHg) concentrations in larval giant salamanders (Dicamptodon spp.) and surface water from forested and chaparral lotic ecosystems distributed along a latitudinal gradient throughout Northern California and Washington. To test hypotheses related to potential effects from mining land-use activities, salamander larvae were also sampled from a reference site at Whiskeytown National Recreation Area, California, and at a nearby, upstream site (Shasta county) on Bureau of Land Management land where Hg contamination from gold mining activities has been documented. HgT concentrations in whole body larvae ranged from 4.6 to 74.5 ng/g wet wt. and percent MeHg ranged from 67% to 86%. Both HgT and MeHg larval tissue concentrations were significantly higher at the mining site in comparison to measured background levels (P low in HgT and MeHg and, in comparison, watersheds with a legacy of land-use practices (i.e., mining operations) had approximately 4.5 - 5.5 times the level of HgT bioaccumulation. Moreover, trophic magnification slopes were highest in the Shasta county region where mining was present. These findings suggest that mining activities increase HgT and MeHg exposure to salamander larvae in the region and may present a threat to other higher trophically positioned organisms, and their associated food webs.
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 >...
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.
Lamb, Trip; Beamer, David A.
2012-01-01
Change in digit number, particularly digit loss, has occurred repeatedly over the evolutionary history of tetrapods. Although digit loss has been documented among distantly related species of salamanders, it is relatively uncommon in this amphibian order. For example, reduction from five to four toes appears to have evolved just three times in the morphologically and ecologically diverse family Plethodontidae. Here we report a molecular phylogenetic analysis for one of these four-toed lineage...
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].
Bicanski, Andrej; Ryczko, Dimitri; Knuesel, Jérémie; Harischandra, Nalin; Charrier, Vanessa; Ekeberg, Örjan; Cabelguen, Jean-Marie; Ijspeert, Auke Jan
2013-01-01
Vertebrate animals exhibit impressive locomotor skills. These locomotor skills are due to the complex interactions between the environment, the musculo-skeletal system and the central nervous system, in particular the spinal locomotor circuits. We are interested in decoding these interactions in the salamander, a key animal from an evolutionary point of view. It exhibits both swimming and stepping gaits and is faced with the problem of producing efficient propulsive forces using the same musc...
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 ...
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
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...
Sutton, William B; Gray, Matthew J; Hoverman, Jason T; Secrist, Richard G; Super, Paul E; Hardman, Rebecca H; Tucker, Jennifer L; Miller, Debra L
2015-06-01
Emerging pathogens are a potential contributor to global amphibian declines. Ranaviruses, which infect ectothermic vertebrates and are common in aquatic environments, have been implicated in die-offs of at least 72 amphibian species worldwide. Most studies on the subject have focused on pool-breeding amphibians, and infection trends in other amphibian species assemblages have been understudied. Our primary study objective was to evaluate hypotheses explaining ranavirus prevalence within a lungless salamander assemblage (Family Plethodontidae) in the Great Smoky Mountains National Park, USA. We sampled 566 total plethodontid salamanders representing 14 species at five sites over a 6-year period (2007-2012). We identified ranavirus-positive individuals in 11 of the 14 (78.6%) sampled species, with salamanders in the genus Desmognathus having greatest infection prevalence. Overall, we found the greatest support for site elevation and sampling year determining infection prevalence. We detected the greatest number of infections in 2007 with 82.5% of sampled individuals testing positive for ranavirus, which we attribute to record drought during this year. Infection prevalence remained relatively high in low-elevation sites in 2008 and 2009. Neither body condition nor aquatic dependence was a significant predictor of ranavirus prevalence. Overall, our results indicate that life history differences among species play a minor role determining ranavirus prevalence compared to the larger effects of site elevation and yearly fluctuations (likely due to environmental stressors) during sampling years. PMID:25537630
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.
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...
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...
Czech Academy of Sciences Publication Activity Database
Krejsa, Jiří; Věchet, S.
Bratislava: Slovak University of Technology in Bratislava, 2010, s. 217-222. ISBN 978-80-227-3353-3. [Robotics in Education . Bratislava (SK), 16.09.2010-17.09.2010] Institutional research plan: CEZ:AV0Z20760514 Keywords : mobile robot localization * bearing only beacons * Bayesian filters Subject RIV: JD - Computer Applications, Robotics
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 experimenta...
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...
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 as a...
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.
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
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.
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., III; 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
2016-01-01
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
A tutorial on Bayesian Normal linear regression
Klauenberg, Katy; Wübbeler, Gerd; Mickan, Bodo; Harris, Peter; Elster, Clemens
2015-12-01
Regression is a common task in metrology and often applied to calibrate instruments, evaluate inter-laboratory comparisons or determine fundamental constants, for example. Yet, a regression model cannot be uniquely formulated as a measurement function, and consequently the Guide to the Expression of Uncertainty in Measurement (GUM) and its supplements are not applicable directly. Bayesian inference, however, is well suited to regression tasks, and has the advantage of accounting for additional a priori information, which typically robustifies analyses. Furthermore, it is anticipated that future revisions of the GUM shall also embrace the Bayesian view. Guidance on Bayesian inference for regression tasks is largely lacking in metrology. For linear regression models with Gaussian measurement errors this tutorial gives explicit guidance. Divided into three steps, the tutorial first illustrates how a priori knowledge, which is available from previous experiments, can be translated into prior distributions from a specific class. These prior distributions have the advantage of yielding analytical, closed form results, thus avoiding the need to apply numerical methods such as Markov Chain Monte Carlo. Secondly, formulas for the posterior results are given, explained and illustrated, and software implementations are provided. In the third step, Bayesian tools are used to assess the assumptions behind the suggested approach. These three steps (prior elicitation, posterior calculation, and robustness to prior uncertainty and model adequacy) are critical to Bayesian inference. The general guidance given here for Normal linear regression tasks is accompanied by a simple, but real-world, metrological example. The calibration of a flow device serves as a running example and illustrates the three steps. It is shown that prior knowledge from previous calibrations of the same sonic nozzle enables robust predictions even for extrapolations.
Bayesian classification and regression trees for predicting incidence of cryptosporidiosis.
Directory of Open Access Journals (Sweden)
Wenbiao Hu
Full Text Available BACKGROUND: Classification and regression tree (CART models are tree-based exploratory data analysis methods which have been shown to be very useful in identifying and estimating complex hierarchical relationships in ecological and medical contexts. In this paper, a Bayesian CART model is described and applied to the problem of modelling the cryptosporidiosis infection in Queensland, Australia. METHODOLOGY/PRINCIPAL FINDINGS: We compared the results of a Bayesian CART model with those obtained using a Bayesian spatial conditional autoregressive (CAR model. Overall, the analyses indicated that the nature and magnitude of the effect estimates were similar for the two methods in this study, but the CART model more easily accommodated higher order interaction effects. CONCLUSIONS/SIGNIFICANCE: A Bayesian CART model for identification and estimation of the spatial distribution of disease risk is useful in monitoring and assessment of infectious diseases prevention and control.
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.
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...
Bayesian Magic in Asteroseismology
Kallinger, T.
2015-09-01
Only a few years ago asteroseismic observations were so rare that scientists had plenty of time to work on individual data sets. They could tune their algorithms in any possible way to squeeze out the last bit of information. Nowadays this is impossible. With missions like MOST, CoRoT, and Kepler we basically drown in new data every day. To handle this in a sufficient way statistical methods become more and more important. This is why Bayesian techniques started their triumph march across asteroseismology. I will go with you on a journey through Bayesian Magic Land, that brings us to the sea of granulation background, the forest of peakbagging, and the stony alley of model comparison.
Bayesian Nonparametric Graph Clustering
Banerjee, Sayantan; Akbani, Rehan; Baladandayuthapani, Veerabhadran
2015-01-01
We present clustering methods for multivariate data exploiting the underlying geometry of the graphical structure between variables. As opposed to standard approaches that assume known graph structures, we first estimate the edge structure of the unknown graph using Bayesian neighborhood selection approaches, wherein we account for the uncertainty of graphical structure learning through model-averaged estimates of the suitable parameters. Subsequently, we develop a nonparametric graph cluster...
Approximate Bayesian recursive estimation
Czech Academy of Sciences Publication Activity Database
Kárný, Miroslav
2014-01-01
Roč. 285, č. 1 (2014), s. 100-111. ISSN 0020-0255 R&D Projects: GA ČR GA13-13502S Institutional support: RVO:67985556 Keywords : Approximate parameter estimation * Bayesian recursive estimation * Kullback–Leibler divergence * Forgetting Subject RIV: BB - Applied Statistics, Operational Research Impact factor: 4.038, year: 2014 http://library.utia.cas.cz/separaty/2014/AS/karny-0425539.pdf
Bayesian Benchmark Dose Analysis
Fang, Qijun; Piegorsch, Walter W.; Barnes, Katherine Y.
2014-01-01
An important objective in environmental risk assessment is estimation of minimum exposure levels, called Benchmark Doses (BMDs) that induce a pre-specified Benchmark Response (BMR) in a target population. Established inferential approaches for BMD analysis typically involve one-sided, frequentist confidence limits, leading in practice to what are called Benchmark Dose Lower Limits (BMDLs). Appeal to Bayesian modeling and credible limits for building BMDLs is far less developed, however. Indee...
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...
Heteroscedastic Treed Bayesian Optimisation
Assael, John-Alexander M.; Wang, Ziyu; Shahriari, Bobak; De Freitas, Nando
2014-01-01
Optimising black-box functions is important in many disciplines, such as tuning machine learning models, robotics, finance and mining exploration. Bayesian optimisation is a state-of-the-art technique for the global optimisation of black-box functions which are expensive to evaluate. At the core of this approach is a Gaussian process prior that captures our belief about the distribution over functions. However, in many cases a single Gaussian process is not flexible enough to capture non-stat...
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.
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 Neural Word Embedding
Barkan, Oren
2016-01-01
Recently, several works in the domain of natural language processing presented successful methods for word embedding. Among them, the Skip-gram (SG) with negative sampling, known also as Word2Vec, advanced the state-of-the-art of various linguistics tasks. In this paper, we propose a scalable Bayesian neural word embedding algorithm that can be beneficial to general item similarity tasks as well. The algorithm relies on a Variational Bayes solution for the SG objective and a detailed step by ...
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.
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...
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
Unbounded Bayesian Optimization via Regularization
Shahriari, Bobak; Bouchard-Côté, Alexandre; De Freitas, Nando
2015-01-01
Bayesian optimization has recently emerged as a popular and efficient tool for global optimization and hyperparameter tuning. Currently, the established Bayesian optimization practice requires a user-defined bounding box which is assumed to contain the optimizer. However, when little is known about the probed objective function, it can be difficult to prescribe such bounds. In this work we modify the standard Bayesian optimization framework in a principled way to allow automatic resizing of t...
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...
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.
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。
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.
Decentralized Distributed Bayesian Estimation
Czech Academy of Sciences Publication Activity Database
Dedecius, Kamil; Sečkárová, Vladimíra
Praha: ÚTIA AVČR, v.v.i, 2011 - (Janžura, M.; Ivánek, J.). s. 16-16 [7th International Workshop on Data–Algorithms–Decision Making. 27.11.2011-29.11.2011, Mariánská] R&D Projects: GA ČR 102/08/0567; GA ČR GA102/08/0567 Institutional research plan: CEZ:AV0Z10750506 Keywords : estimation * distributed estimation * model Subject RIV: BB - Applied Statistics, Operational Research http://library.utia.cas.cz/separaty/2011/AS/dedecius-decentralized distributed bayesian estimation.pdf
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.
Improved iterative Bayesian unfolding
D'Agostini, G
2010-01-01
This paper reviews the basic ideas behind a Bayesian unfolding published some years ago and improves their implementation. In particular, uncertainties are now treated at all levels by probability density functions and their propagation is performed by Monte Carlo integration. Thus, small numbers are better handled and the final uncertainty does not rely on the assumption of normality. Theoretical and practical issues concerning the iterative use of the algorithm are also discussed. The new program, implemented in the R language, is freely available, together with sample scripts to play with toy models.
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.
Bayesian Inference on Gravitational Waves
Directory of Open Access Journals (Sweden)
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.
Adaptive Dynamic Bayesian Networks
Energy Technology Data Exchange (ETDEWEB)
Ng, B M
2007-10-26
A discrete-time Markov process can be compactly modeled as a dynamic Bayesian network (DBN)--a graphical model with nodes representing random variables and directed edges indicating causality between variables. Each node has a probability distribution, conditional on the variables represented by the parent nodes. A DBN's graphical structure encodes fixed conditional dependencies between variables. But in real-world systems, conditional dependencies between variables may be unknown a priori or may vary over time. Model errors can result if the DBN fails to capture all possible interactions between variables. Thus, we explore the representational framework of adaptive DBNs, whose structure and parameters can change from one time step to the next: a distribution's parameters and its set of conditional variables are dynamic. This work builds on recent work in nonparametric Bayesian modeling, such as hierarchical Dirichlet processes, infinite-state hidden Markov networks and structured priors for Bayes net learning. In this paper, we will explain the motivation for our interest in adaptive DBNs, show how popular nonparametric methods are combined to formulate the foundations for adaptive DBNs, and present preliminary results.
Bayesian analysis toolkit - BAT
International Nuclear Information System (INIS)
Statistical treatment of data is an essential part of any data analysis and interpretation. Different statistical methods and approaches can be used, however the implementation of these approaches is complicated and at times inefficient. The Bayesian analysis toolkit (BAT) is a software package developed in C++ framework that facilitates the statistical analysis of the data using Bayesian theorem. The tool evaluates the posterior probability distributions for models and their parameters using Markov Chain Monte Carlo which in turn provide straightforward parameter estimation, limit setting and uncertainty propagation. Additional algorithms, such as simulated annealing, allow extraction of the global mode of the posterior. BAT sets a well-tested environment for flexible model definition and also includes a set of predefined models for standard statistical problems. The package is interfaced to other software packages commonly used in high energy physics, such as ROOT, Minuit, RooStats and CUBA. We present a general overview of BAT and its algorithms. A few physics examples are shown to introduce the spectrum of its applications. In addition, new developments and features are summarized.
2011-09-07
... Register on June 17, 1999 (64 FR 32717), the Service would issue a permit to the Applicant authorizing take... Fish and Wildlife Service Proposed Safe Harbor Agreement for California Red-legged Frog, California... federally threatened California red-legged frog (Rana draytonii) and California tiger salamander...
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.
2011-07-22
... potential for ``take'' of one Federally listed animal, the California tiger salamander. The applicant would... include the following activities: To harass, harm, pursue, hunt, shoot, wound, kill, trap, capture or collect listed animal species, or to attempt to engage in such conduct. However, under section...
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.
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.
Blooi, M; Pasmans, F; Rouffaer, L; Haesebrouck, F; Vercammen, F; Martel, A
2015-01-01
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. PMID:26123899
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
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 ...
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.
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)
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...... represents the spatial coordinates of the grid nodes. Knowledge of how grid nodes are depicted in the observed image is described through the observation model. The prior consists of a node prior and an arc (edge) prior, both modeled as Gaussian MRFs. The node prior models variations in the positions of grid...... nodes and the arc prior models variations in row and column spacing across the grid. Grid matching is done by placing an initial rough grid over the image and applying an ensemble annealing scheme to maximize the posterior distribution of the grid. The method can be applied to noisy images with missing...
Bayesian model discrimination for glucose-insulin homeostasis
DEFF Research Database (Denmark)
Andersen, Kim Emil; Brooks, Stephen P.; Højbjerre, Malene
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......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...
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
Dose rate estimation of the Tohoku hynobiid salamander, Hynobius lichenatus, in Fukushima
International Nuclear Information System (INIS)
The radiological risks to the Tohoku hynobiid salamanders (class Amphibia), Hynobius lichenatus due to the Fukushima Dai-ichi Nuclear Power Plant accident were assessed in Fukushima Prefecture, including evacuation areas. Aquatic egg clutches (n = 1 for each sampling date and site; n = 4 in total), overwintering larvae (n = 1–5 for each sampling date and site; n = 17 in total), and terrestrial juveniles or adults (n = 1 or 3 for each sampling date and site; n = 12 in total) of H. lichenatus were collected from the end of April 2011 to April 2013. Environmental media such as litter (n = 1–5 for each sampling date and site; n = 30 in total), soil (n = 1–8 for each sampling date and site; n = 31 in total), water (n = 1 for each sampling date and site; n = 17 in total), and sediment (n = 1 for each sampling date and site; n = 17 in total) were also collected. Activity concentrations of 134Cs + 137Cs were 1.9–2800, 0.13–320, and 0.51–220 kBq (dry kg) −1 in the litter, soil, and sediment samples, respectively, and were 0.31–220 and <0.29–40 kBq (wet kg)−1 in the adult and larval salamanders, respectively. External and internal absorbed dose rates to H. lichenatus were calculated from these activity concentration data, using the ERICA Assessment Tool methodology. External dose rates were also measured in situ with glass dosimeters. There was agreement within a factor of 2 between the calculated and measured external dose rates. In the most severely contaminated habitat of this salamander, a northern part of Abukuma Mountains, the highest total dose rates were estimated to be 50 and 15 μGy h−1 for the adults and overwintering larvae, respectively. Growth and survival of H. lichenatus was not affected at a dose rate of up to 490 μGy h−1 in the previous laboratory chronic gamma-irradiation experiment, and thus growth and survival of this salamander would not be affected, even in the most severely contaminated
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...
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...
Portfolio Allocation for Bayesian Optimization
Brochu, Eric; Hoffman, Matthew W.; 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 uses Bayesian methods to sample the objective efficiently using an acquisition function which incorporates the model's estimate of the objective and the uncertainty at any given point. However, there are several differen...
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...
Bayesian Networks and Influence Diagrams
DEFF Research Database (Denmark)
Kjærulff, Uffe Bro; Madsen, Anders Læsø
Probabilistic networks, also known as Bayesian networks and influence diagrams, have become one of the most promising technologies in the area of applied artificial intelligence, offering intuitive, efficient, and reliable methods for diagnosis, prediction, decision making, classification......, 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...
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.
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.
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.
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 ...
BAT - Bayesian Analysis Toolkit
International Nuclear Information System (INIS)
One of the most vital steps in any data analysis is the statistical analysis and comparison with the prediction of a theoretical model. The many uncertainties associated with the theoretical model and the observed data require a robust statistical analysis tool. The Bayesian Analysis Toolkit (BAT) is a powerful statistical analysis software package based on Bayes' Theorem, developed to evaluate the posterior probability distribution for models and their parameters. It implements Markov Chain Monte Carlo to get the full posterior probability distribution that in turn provides a straightforward parameter estimation, limit setting and uncertainty propagation. Additional algorithms, such as Simulated Annealing, allow to evaluate the global mode of the posterior. BAT is developed in C++ and allows for a flexible definition of models. A set of predefined models covering standard statistical cases are also included in BAT. It has been interfaced to other commonly used software packages such as ROOT, Minuit, RooStats and CUBA. An overview of the software and its algorithms is provided along with several physics examples to cover a range of applications of this statistical tool. Future plans, new features and recent developments are briefly discussed.
Fenolio, Danté B; Graening, G.O; Collier, Bret A.; Stout, Jim F
2005-01-01
During a two year population ecology study in a cave environment, 15 Eurycea (=Typhlotriton) spelaea were observed ingesting bat guano. Furthermore, E. spelaea capture numbers increased significantly during the time that grey bats (Myotis grisescens) deposited fresh guano. We investigated the hypothesis that this behaviour was not incidental to the capture of invertebrate prey, but a diet switch to an energy-rich detritus in an oligotrophic environment. Stable isotope assays determined that g...
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
Harischandra, Nalin; Knuesel, Jeremie; Kozlov, Alexander; Bicanski, Andrej; Cabelguen, Jean-Marie; IJSPEERT, AUKE; Ekeberg, Örjan
2011-01-01
Here, we investigate the role of sensory feedback in gait generation and transition by using a three-dimensional, neuro-musculo-mechanical model of a salamander with realistic physical parameters. 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 ipsilaterally and con...
Nalin Harischandra; Alexander Kozlov; Andrej Bicanski; Jean-Marie Cabelguen
2011-01-01
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 a...
Belden, L. K.; Peterman, W. E.; Smith, S A; Brooks, L R; Benfield, E. F.; Black, W. P.; Yang, Z M; Wojdak, J. M.
2012-01-01
Metagonimoides oregonensis (Heterophyidae) is a little-known digenetic trematode that uses raccoons and possibly mink as definitive hosts, and stream snails and amphibians as intermediate hosts. Some variation in the life cycle and adult morphology in western and eastern populations has been previously noted. In the southern Appalachians, Pleurocera snails and stream salamanders, e.g., Desmognathus spp., are used as intermediate hosts in the life cycle. We completed a series of studies in thi...
Directory of Open Access Journals (Sweden)
Nalin Harischandra
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
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 ...
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.
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 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 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.
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....
Miller, Mark; Haig, Susan M.; Wagner, R.S.
2005-01-01
Endemic to Oregon in the northwestern US, the Oregon slender salamander (Batrachoseps wrighti) is a terrestrial plethodontid found associated with late successional mesic forests. Consequently, forest management practices such as timber harvesting may impact their persistence. Therefore, to infer possible future effects of these practices on population structure and differentiation, we used mitochondrial DNA sequences (cytochrome b) and RAPD markers to analyze 22 populations across their range. Phylogenetic analyses of sequence data (774 bp) revealed two historical lineages corresponding to northern and southern-distributed populations. Relationships among haplotypes and haplotype diversity within lineages suggested that the northern region may have more recently been colonized compared to the southern region. In contrast to the mitochondrial data, analyses of 46 RAPD loci suggested an overall pattern of isolation-by-distance in the set of populations examined and no particularly strong clustering of populations based on genetic distances. We propose two non-exclusive hypotheses to account for discrepancies between mitochondrial and nuclear data sets. First, our data may reflect an overall ancestral pattern of isolation-by-distance that has subsequently been influenced by vicariance. Alternately, our analyses may suggest that male-mediated gene flow and female philopatry are important contributors to the pattern of genetic diversity. We discuss the importance of distinguishing between these two hypotheses for the purposes of identifying conservation units and note that, regardless of the relative contribution of each mechanism towards the observed pattern of diversity, protection of habitat will likely prove critical for the long-term persistence of this species.
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…
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 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
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
Non-stationarity in GARCH models: A Bayesian analysis
Kleibergen, Frank; Dijk, Herman
1993-01-01
textabstractFirst, the non-stationarity properties of the conditional variances in the GARCH(1,1) model are analysed using the concept of infinite persistence of shocks. Given a time sequence of probabilities for increasing/decreasing conditional variances, a theoretical formula for quasi-strict non-stationarity is defined. The resulting conditions for the GARCH(1,1) model are shown to differ from the weak stationarity conditions mainly used in the literature. Bayesian statistical analysis us...
Regional fertility data analysis: A small area Bayesian approach
Eduardo A. Castro; Zhen Zhang; Arnab Bhattacharjee; Martins, José M.; Taps Maiti
2013-01-01
Accurate estimation of demographic variables such as mortality, fertility and migrations, by age groups and regions, is important for analyses and policy. However, traditional estimates based on within cohort counts are often inaccurate, particularly when the sub-populations considered are small. We use small area Bayesian statistics to develop a model for age-specific fertility rates. In turn, such small area estimation requires accurate descriptions of spatial and cross-section dependence. ...
Bayesian Fusion Algorithm for Inferring Trust in Wireless Sensor Networks
Mohammad Momani; Subhash Challa; Rami Alhmouz
2010-01-01
This paper introduces a new Bayesian fusion algorithm to combine more than one trust component (data trust and communication trust) to infer the overall trust between nodes. This research work proposes that one trust component is not enough when deciding on whether or not to trust a specific node in a wireless sensor network. This paper discusses and analyses the results from the communication trust component (binary) and the data trust component (continuous) and proves that either component ...
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.
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 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 in...
ANALYSIS OF BAYESIAN CLASSIFIER ACCURACY
Directory of Open Access Journals (Sweden)
Felipe Schneider Costa
2013-01-01
Full Text Available The naÃ¯ve Bayes classifier is considered one of the most effective classification algorithms today, competing with more modern and sophisticated classifiers. Despite being based on unrealistic (naÃ¯ve assumption that all variables are independent, given the output class, the classifier provides proper results. However, depending on the scenario utilized (network structure, number of samples or training cases, number of variables, the network may not provide appropriate results. This study uses a process variable selection, using the chi-squared test to verify the existence of dependence between variables in the data model in order to identify the reasons which prevent a Bayesian network to provide good performance. A detailed analysis of the data is also proposed, unlike other existing work, as well as adjustments in case of limit values between two adjacent classes. Furthermore, variable weights are used in the calculation of a posteriori probabilities, calculated with mutual information function. Tests were applied in both a naÃ¯ve Bayesian network and a hierarchical Bayesian network. After testing, a significant reduction in error rate has been observed. The naÃ¯ve Bayesian network presented a drop in error rates from twenty five percent to five percent, considering the initial results of the classification process. In the hierarchical network, there was not only a drop in fifteen percent error rate, but also the final result came to zero.
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 Networks and Influence Diagrams
DEFF Research Database (Denmark)
Kjærulff, Uffe Bro; Madsen, Anders Læsø
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...
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)
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.
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...
Maliarchuk, B A; Derenko, M V; Denisova, G A
2014-02-01
To elucidate the effect of natural selection on the evolution of mitochondrial DNA (mtDNA) in Asiatic salamanders of the family Hynobiidae, nucleotide sequences of 12 protein-coding genes were analyzed. Using a mixed effects model of evolution, it was found that, in spite of the pronounced effect of negative selection on the mtDNA evolution in Hynobiidae (which is typical for the animals in general), two phylogenetic clusters, the West Asian one, represented by the genera Ranodon and Paradactylodon, and North Eurasian one, represented by the genus Salamandrella, were formed under the influence of episodic positive selection. Analysis of protein sequences encoded by the mitochondrial genome also supported the influence of positive selection on the evolution of Hynobiidae at some stages of their cladogenesis. It is suggested that the signatures of adaptive evolution detected in the mtDNA of Hynobiidae were determined by the complex and long-lasting history of their formation, accompanied by adaptation to the changing environment. PMID:25711027
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.
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
Resistance to chytridiomycosis in European plethodontid salamanders of the genus Speleomantes.
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Frank Pasmans
Full Text Available North America and the neotropics harbor nearly all species of plethodontid salamanders. In contrast, this family of caudate amphibians is represented in Europe and Asia by two genera, Speleomantes and Karsenia, which are confined to small geographic ranges. Compared to neotropical and North American plethodontids, mortality attributed to chytridiomycosis caused by Batrachochytrium dendrobatidis (Bd has not been reported for European plethodontids, despite the established presence of Bd in their geographic distribution. We determined the extent to which Bd is present in populations of all eight species of European Speleomantes and show that Bd was undetectable in 921 skin swabs. We then compared the susceptibility of one of these species, Speleomantes strinatii, to experimental infection with a highly virulent isolate of Bd (BdGPL, and compared this to the susceptible species Alytes muletensis. Whereas the inoculated A. muletensis developed increasing Bd-loads over a 4-week period, none of five exposed S. strinatii were colonized by Bd beyond 2 weeks post inoculation. Finally, we determined the extent to which skin secretions of Speleomantes species are capable of killing Bd. Skin secretions of seven Speleomantes species showed pronounced killing activity against Bd over 24 hours. In conclusion, the absence of Bd in Speleomantes combined with resistance to experimental chytridiomycosis and highly efficient skin defenses indicate that the genus Speleomantes is a taxon unlikely to decline due to Bd.
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
Localization of glycine, GABA and neuropeptide containing neurons in tiger salamander retina
International Nuclear Information System (INIS)
Putative glycinergic and GABAergic neurons in the salamander retina were localized by a parallel analysis of high affinity 3H-glycine uptake and glycine-like immunoreactivity (Gly-IR) and a comparative analysis of high affinity 3H-GABA uptake, GABA, like immunoreactivity (GABA-IR), and glutamate decarboxylase immunoreactivity (GAD-IR) at the light microscopic level. Good correspondence of labeling of 3H-glycine uptake and Gly-IR as well as that of 3H-GABA uptake and GABA-IR were observed. In addition, GAD immunoreactive neurons contained GABA-IR as well. Extensive colocalization of 3H-glycine uptake and Gly-IR and that of 3H-GABA uptake, GABA-IR and perhaps GAD-IR were indicated by the similarities in the distribution, morphology and labeling frequency of neurons and lamination in the inner plexiform layer (IPL). However, the Gly-IR and the GABA-IR probes appeared to be more sensitive and can thus be a reliable marker for glycine and GABA containing neurons respectively
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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.
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
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...
Complexity analysis of accelerated MCMC methods for Bayesian inversion
Hoang, Viet Ha; Schwab, Christoph; Stuart, Andrew M.
2013-08-01
The Bayesian approach to inverse problems, in which the posterior probability distribution on an unknown field is sampled for the purposes of computing posterior expectations of quantities of interest, is starting to become computationally feasible for partial differential equation (PDE) inverse problems. Balancing the sources of error arising from finite-dimensional approximation of the unknown field, the PDE forward solution map and the sampling of the probability space under the posterior distribution are essential for the design of efficient computational Bayesian methods for PDE inverse problems. We study Bayesian inversion for a model elliptic PDE with an unknown diffusion coefficient. We provide complexity analyses of several Markov chain Monte Carlo (MCMC) methods for the efficient numerical evaluation of expectations under the Bayesian posterior distribution, given data δ. Particular attention is given to bounds on the overall work required to achieve a prescribed error level ε. Specifically, we first bound the computational complexity of ‘plain’ MCMC, based on combining MCMC sampling with linear complexity multi-level solvers for elliptic PDE. Our (new) work versus accuracy bounds show that the complexity of this approach can be quite prohibitive. Two strategies for reducing the computational complexity are then proposed and analyzed: first, a sparse, parametric and deterministic generalized polynomial chaos (gpc) ‘surrogate’ representation of the forward response map of the PDE over the entire parameter space, and, second, a novel multi-level Markov chain Monte Carlo strategy which utilizes sampling from a multi-level discretization of the posterior and the forward PDE. For both of these strategies, we derive asymptotic bounds on work versus accuracy, and hence asymptotic bounds on the computational complexity of the algorithms. In particular, we provide sufficient conditions on the regularity of the unknown coefficients of the PDE and on the
Bayesian network as a modelling tool for risk management in agriculture
DEFF Research Database (Denmark)
Rasmussen, Svend; Madsen, Anders L.; Lund, Mogens
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, and that......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...
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.
Attention in a bayesian framework
DEFF Research Database (Denmark)
Whiteley, Louise Emma; Sahani, Maneesh
2012-01-01
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...... settings, where cues shape expectations about a small number of upcoming stimuli and thus convey "prior" information about clearly defined objects. While operationally consistent with the experiments it seeks to describe, this view of attention as prior seems to miss many essential elements of both its......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...
Bayesian Sampling using Condition Indicators
DEFF Research Database (Denmark)
Faber, Michael H.; Sørensen, John Dalsgaard
2002-01-01
allows for a Bayesian formulation of the indicators whereby the experience and expertise of the inspection personnel may be fully utilized and consistently updated as frequentistic information is collected. The approach is illustrated on an example considering a concrete structure subject to corrosion......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. This...
BAYESIAN IMAGE RESTORATION, USING CONFIGURATIONS
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Thordis Linda Thorarinsdottir
2011-05-01
Full Text Available In this paper, we develop a Bayesian procedure for removing noise from images that can be viewed as noisy realisations of random sets in the plane. The procedure utilises recent advances in configuration theory for noise free random sets, where the probabilities of observing the different boundary 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 in detail for 3 X 3 and 5 X 5 configurations and examples of the performance of the procedure are given.
Bayesian Seismology of the Sun
Gruberbauer, Michael
2013-01-01
We perform a Bayesian grid-based analysis of the solar l=0,1,2 and 3 p modes obtained via BiSON in order to deliver the first Bayesian asteroseismic analysis of the solar composition problem. We do not find decisive evidence to prefer either of the contending chemical compositions, although the revised solar abundances (AGSS09) are more probable in general. We do find indications for systematic problems in standard stellar evolution models, unrelated to the consequences of inadequate modelling of the outer layers on the higher-order modes. The seismic observables are best fit by solar models that are several hundred million years older than the meteoritic age of the Sun. Similarly, meteoritic age calibrated models do not adequately reproduce the observed seismic observables. Our results suggest that these problems will affect any asteroseismic inference that relies on a calibration to the Sun.
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 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...
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
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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
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...
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 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 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 ...
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.
Skill Rating by Bayesian Inference
Di Fatta, Giuseppe; Haworth, Guy McCrossan; Regan, Kenneth W.
2009-01-01
Systems Engineering often involves computer modelling the behaviour of proposed systems and their components. Where a component is human, fallibility must be modelled by a stochastic agent. The identification of a model of decision-making over quantifiable options is investigated using the game-domain of Chess. Bayesian methods are used to infer the distribution of players’ skill levels from the moves they play rather than from their competitive results. The approach is used on large sets of ...
Topics in Nonparametric Bayesian Statistics
2003-01-01
The intersection set of Bayesian and nonparametric statistics was almost empty until about 1973, but now seems to be growing at a healthy rate. This chapter gives an overview of various theoretical and applied research themes inside this field, partly complementing and extending recent reviews of Dey, Müller and Sinha (1998) and Walker, Damien, Laud and Smith (1999). The intention is not to be complete or exhaustive, but rather to touch on research areas of interest, partly by example.
Cover Tree Bayesian Reinforcement Learning
Tziortziotis, Nikolaos; Dimitrakakis, Christos; Blekas, Konstantinos
2013-01-01
This paper proposes an online tree-based Bayesian approach for reinforcement learning. For inference, we employ a generalised context tree model. This defines a distribution on multivariate Gaussian piecewise-linear models, which can be updated in closed form. The tree structure itself is constructed using the cover tree method, which remains efficient in high dimensional spaces. We combine the model with Thompson sampling and approximate dynamic programming to obtain effective exploration po...
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 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 Optimization for Adaptive MCMC
Mahendran, Nimalan; Wang, Ziyu; Hamze, Firas; De Freitas, Nando
2011-01-01
This paper proposes a new randomized strategy for adaptive MCMC using Bayesian optimization. This approach applies to non-differentiable objective functions and trades off exploration and exploitation to reduce the number of potentially costly objective function evaluations. We demonstrate the strategy in the complex setting of sampling from constrained, discrete and densely connected probabilistic graphical models where, for each variation of the problem, one needs to adjust the parameters o...
Inference in hybrid Bayesian networks
DEFF Research Database (Denmark)
Lanseth, Helge; Nielsen, Thomas Dyhre; Rumí, Rafael;
2009-01-01
and reliability block diagrams). However, limitations in the BNs' calculation engine have prevented BNs from becoming equally popular for domains containing mixtures of both discrete and continuous variables (so-called hybrid domains). In this paper we focus on these difficulties, and summarize some of the last...... decade's research on inference in hybrid Bayesian networks. The discussions are linked to an example model for estimating human reliability....
Quantile pyramids for Bayesian nonparametrics
2009-01-01
P\\'{o}lya trees fix partitions and use random probabilities in order to construct random probability measures. With quantile pyramids we instead fix probabilities and use random partitions. For nonparametric Bayesian inference we use a prior which supports piecewise linear quantile functions, based on the need to work with a finite set of partitions, yet we show that the limiting version of the prior exists. We also discuss and investigate an alternative model based on the so-called substitut...
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 Credit Ratings (new version)
Paola Cerchiello; Paolo Giudici
2013-01-01
In this contribution we aim at improving ordinal variable selection in the context of causal models. In this regard, we propose an approach that provides a formal inferential tool to compare the explanatory power of each covariate, and, therefore, to select an effective model for classification purposes. Our proposed model is Bayesian nonparametric, and, thus, keeps the amount of model specification to a minimum. We consider the case in which information from the covariates is at the ordinal ...
Embracing Uncertainty: The Interface of Bayesian Statistics and Cognitive Psychology
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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.
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.
Quantum Inference on Bayesian Networks
Yoder, Theodore; Low, Guang Hao; Chuang, Isaac
2014-03-01
Because quantum physics is naturally probabilistic, it seems reasonable to expect physical systems to describe probabilities and their evolution in a natural fashion. Here, we use quantum computation to speedup sampling from a graphical probability model, the Bayesian network. A specialization of this sampling problem is approximate Bayesian inference, where the distribution on query variables is sampled given the values e of evidence variables. Inference is a key part of modern machine learning and artificial intelligence tasks, but is known to be NP-hard. Classically, a single unbiased sample is obtained from a Bayesian network on n variables with at most m parents per node in time (nmP(e) - 1 / 2) , depending critically on P(e) , the probability the evidence might occur in the first place. However, by implementing a quantum version of rejection sampling, we obtain a square-root speedup, taking (n2m P(e) -1/2) time per sample. The speedup is the result of amplitude amplification, which is proving to be broadly applicable in sampling and machine learning tasks. In particular, we provide an explicit and efficient circuit construction that implements the algorithm without the need for oracle access.
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...
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...
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...
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
Bayesian networks with applications in reliability analysis
Langseth, Helge
2002-01-01
A common goal of the papers in this thesis is to propose, formalize and exemplify the use of Bayesian networks as a modelling tool in reliability analysis. The papers span work in which Bayesian networks are merely used as a modelling tool (Paper I), work where models are specially designed to utilize the inference algorithms of Bayesian networks (Paper II and Paper III), and work where the focus has been on extending the applicability of Bayesian networks to very large domains (Paper IV and ...
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.
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.
Portnoy, J.W.
1990-01-01
The relationship between water chemistry and breeding success of spotted salamanders Ambystoma maculatum (Shaw) was examined in temporary woodland ponds on outer Cape Cod, Massachusetts in 1985 and 1986. Most pond waters were dilute (3median coductivity = 57 umhos cm-1 (1 umhos cm-1 = 0?1 mSm-1)), acidic (median pH = 4?82), and highly colored (median = 140 Pt-Co units). Most acidity was due to abundant organic acids. Salamander survival to hatching was over 80% at 8 of 12 ponds monitored. Complete mortality, preceded by gross abnormalities, was observed only among embryos in the most acidic spawning pond (pH 4?3-4?5) in both years. Embryo transfers between ponds and laboratory studies indicated that reduced survival was due to the interaction of low pH with high tannin-lignin concentration. The use of amphibian embryonic survival to indicate acid rain effects is complicated by multiple habitat parameters and should only be attempted in conjunction with long-term population monitoring.
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
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.
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.
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.
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 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...... intensity function, while the second approach is based on an underlying clustering and branching structure in the Hawkes process. For practical use, MCMC (Markov chain Monte Carlo) methods are employed. The two approaches are compared numerically using three examples of the Hawkes process....
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...... intensity function, while the second approach is based on an underlying clustering and branching structure in the Hawkes process. For practical use, MCMC (Markov chain Monte Carlo) methods are employed. The two approaches are compared numerically using three examples of the Hawkes process....
Collaborative Kalman Filtration: Bayesian Perspective
Czech Academy of Sciences Publication Activity Database
Dedecius, Kamil
Lisabon, Portugalsko: Institute for Systems and Technologies of Information, Control and Communication (INSTICC), 2014, s. 468-474. ISBN 978-989-758-039-0. [11th International Conference on Informatics in Control, Automation and Robotics - ICINCO 2014. Vien (AT), 01.09.2014-03.09.2014] R&D Projects: GA ČR(CZ) GP14-06678P Institutional support: RVO:67985556 Keywords : Bayesian analysis * Kalman filter * distributed estimation Subject RIV: BB - Applied Statistics, Operational Research http://library.utia.cas.cz/separaty/2014/AS/dedecius-0431324.pdf
Pooled Bayesian meta-analysis of two Polish studies on radiation-induced cancers
International Nuclear Information System (INIS)
The robust Bayesian regression method was applied to perform meta-analysis of two independent studies on influence of low ionising radiation doses on the occurrence of fatal cancers. The re-analysed data come from occupational exposure analysis of nuclear workers in Swierk (Poland) and from ecological study of cancer risk from natural background radiation in Poland. Such two different types of data were analysed, and three popular models were tested: constant, linear and quadratic dose-response dependencies. The Bayesian model selection algorithm was used for all models. The Bayesian statistics clearly indicates that the popular linear no-threshold (LNT) assumption is not valid for presented cancer risks in the range of low doses of ionising radiation. The subject of LNT hypothesis use in radiation risk prediction and assessment is also discussed. (authors)
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.
Bayesian Decision Theoretical Framework for Clustering
Chen, Mo
2011-01-01
In this thesis, we establish a novel probabilistic framework for the data clustering problem from the perspective of Bayesian decision theory. The Bayesian decision theory view justifies the important questions: what is a cluster and what a clustering algorithm should optimize. We prove that the spectral clustering (to be specific, the…
Bayesian Statistics for Biological Data: Pedigree Analysis
Stanfield, William D.; Carlton, Matthew A.
2004-01-01
The use of Bayes' formula is applied to the biological problem of pedigree analysis to show that the Bayes' formula and non-Bayesian or "classical" methods of probability calculation give different answers. First year college students of biology can be introduced to the Bayesian statistics.
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…
Nonparametric Bayesian Modeling of Complex Networks
DEFF Research Database (Denmark)
Schmidt, Mikkel Nørgaard; Mørup, Morten
2013-01-01
Modeling structure in complex networks using Bayesian nonparametrics makes it possible to specify flexible model structures and infer the adequate model complexity from the observed data. This article provides a gentle introduction to nonparametric Bayesian modeling of complex networks: Using...... for complex networks can be derived and point out relevant literature....
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 ...
Compiling Relational Bayesian Networks for Exact Inference
DEFF Research Database (Denmark)
Jaeger, Manfred; Darwiche, Adnan; Chavira, Mark
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 eva...
Bayesian analysis of exoplanet and binary orbits
Schulze-Hartung, Tim; 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.
Computational methods for Bayesian model choice
Robert, Christian P.; Wraith, Darren
2009-01-01
In this note, we shortly survey some recent approaches on the approximation of the Bayes factor used in Bayesian hypothesis testing and in Bayesian model choice. In particular, we reassess importance sampling, harmonic mean sampling, and nested sampling from a unified perspective.
Fracture prediction of cardiac lead medical devices using Bayesian networks
International Nuclear Information System (INIS)
A novel Bayesian network methodology has been developed to enable the prediction of fatigue fracture of cardiac lead medical devices. The methodology integrates in-vivo device loading measurements, patient demographics, patient activity level, in-vitro fatigue strength measurements, and cumulative damage modeling techniques. Many plausible combinations of these variables can be simulated within a Bayesian network framework to generate a family of fatigue fracture survival curves, enabling sensitivity analyses and the construction of confidence bounds on reliability predictions. The method was applied to the prediction of conductor fatigue fracture near the shoulder for two market-released cardiac defibrillation leads which had different product performance histories. The case study used recently published data describing the in-vivo curvature conditions and the in-vitro fatigue strength. The prediction results from the methodology aligned well with the observed qualitative ranking of field performance, as well as the quantitative field survival from fracture. This initial success suggests that study of further extension of this method to other medical device applications is warranted. - Highlights: • A new method to simulate the fatigue experience of an implanted cardiac lead. • Fatigue strength and use conditions are incorporated within a Bayesian network. • Confidence bounds reflect the uncertainty in all input parameters. • A case study is presented using market released cardiac leads
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.
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. PMID:26776199
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
A Bayesian foundation for individual learning under uncertainty
Directory of Open Access Journals (Sweden)
Christoph Mathys
2011-05-01
Full Text Available Computational learning models are critical for understanding mechanisms of adaptive behavior. However, the two major current frameworks, reinforcement learning (RL and Bayesian learning, both have certain limitations. For example, many Bayesian models are agnostic of inter-individual variability and involve complicated integrals, making online learning difficult. Here, we introduce a generic hierarchical Bayesian framework for individual learning under multiple forms of uncertainty (e.g., environmental volatility and perceptual uncertainty. The model assumes Gaussian random walks of states at all but the first level, with the step size determined by the next higher level. The coupling between levels is controlled by parameters that shape the influence of uncertainty on learning in a subject-specific fashion. Using variational Bayes under a mean field approximation and a novel approximation to the posterior energy function, we derive trial-by-trial update equations which (i are analytical and extremely efficient, enabling real-time learning, (ii have a natural interpretation in terms of RL, and (iii contain parameters representing processes which play a key role in current theories of learning, e.g., precision-weighting of prediction error. These parameters allow for the expression of individual differences in learning and may relate to specific neuromodulatory mechanisms in the brain. Our model is very general: it can deal with both discrete and continuous states and equally accounts for deterministic and probabilistic relations between environmental events and perceptual states (i.e., situations with and without perceptual uncertainty. These properties are illustrated by simulations and analyses of empirical time series. Overall, our framework provides a novel foundation for understanding normal and pathological learning that contextualizes RL within a generic Bayesian scheme and thus connects it to principles of optimality from probability
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
A Gibbs sampler for Bayesian analysis of site-occupancy data
Dorazio, Robert M.; Rodriguez, Daniel Taylor
2012-01-01
1. A Bayesian analysis of site-occupancy data containing covariates of species occurrence and species detection probabilities is usually completed using Markov chain Monte Carlo methods in conjunction with software programs that can implement those methods for any statistical model, not just site-occupancy models. Although these software programs are quite flexible, considerable experience is often required to specify a model and to initialize the Markov chain so that summaries of the posterior distribution can be estimated efficiently and accurately. 2. As an alternative to these programs, we develop a Gibbs sampler for Bayesian analysis of site-occupancy data that include covariates of species occurrence and species detection probabilities. This Gibbs sampler is based on a class of site-occupancy models in which probabilities of species occurrence and detection are specified as probit-regression functions of site- and survey-specific covariate measurements. 3. To illustrate the Gibbs sampler, we analyse site-occupancy data of the blue hawker, Aeshna cyanea (Odonata, Aeshnidae), a common dragonfly species in Switzerland. Our analysis includes a comparison of results based on Bayesian and classical (non-Bayesian) methods of inference. We also provide code (based on the R software program) for conducting Bayesian and classical analyses of site-occupancy data.
Analysis of KATRIN data using Bayesian inference
Riis, Anna Sejersen; Weinheimer, Christian
2011-01-01
The KATRIN (KArlsruhe TRItium Neutrino) experiment will be analyzing the tritium beta-spectrum to determine the mass of the neutrino with a sensitivity of 0.2 eV (90% C.L.). This approach to a measurement of the absolute value of the neutrino mass relies only on the principle of energy conservation and can in some sense be called model-independent as compared to cosmology and neutrino-less double beta decay. However by model independent we only mean in case of the minimal extension of the standard model. One should therefore also analyse the data for non-standard couplings to e.g. righthanded or sterile neutrinos. As an alternative to the frequentist minimization methods used in the analysis of the earlier experiments in Mainz and Troitsk we have been investigating Markov Chain Monte Carlo (MCMC) methods which are very well suited for probing multi-parameter spaces. We found that implementing the KATRIN chi squared function in the COSMOMC package - an MCMC code using Bayesian parameter inference - solved the ...
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 f...
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 f...
DEFF Research Database (Denmark)
Jelsøe, Erling; Jæger, Birgit
2015-01-01
When analysing the results of a European wide citizen consultation on sustainable consumption it is necessary to take a number of issues into account, such as the question of representativity and tensions between national and European identies and between consumer and Citizen orientations regarding...
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 ...
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.
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
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.
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...
On Bayesian System Reliability Analysis
International Nuclear Information System (INIS)
The view taken in this thesis is that reliability, the probability that a system will perform a required function for a stated period of time, depends on a person's state of knowledge. Reliability changes as this state of knowledge changes, i.e. when new relevant information becomes available. Most existing models for system reliability prediction are developed in a classical framework of probability theory and they overlook some information that is always present. Probability is just an analytical tool to handle uncertainty, based on judgement and subjective opinions. It is argued that the Bayesian approach gives a much more comprehensive understanding of the foundations of probability than the so called frequentistic school. A new model for system reliability prediction is given in two papers. The model encloses the fact that component failures are dependent because of a shared operational environment. The suggested model also naturally permits learning from failure data of similar components in non identical environments. 85 refs
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...
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.
Cooperative extensions of the Bayesian game
Ichiishi, Tatsuro
2006-01-01
This is the very first comprehensive monograph in a burgeoning, new research area - the theory of cooperative game with incomplete information with emphasis on the solution concept of Bayesian incentive compatible strong equilibrium that encompasses the concept of the Bayesian incentive compatible core. Built upon the concepts and techniques in the classical static cooperative game theory and in the non-cooperative Bayesian game theory, the theory constructs and analyzes in part the powerful n -person game-theoretical model characterized by coordinated strategy-choice with individualistic ince
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
Supra-Bayesian Combination of Probability Distributions
Czech Academy of Sciences Publication Activity Database
Sečkárová, Vladimíra
Veszprém : University of Pannonia, 2010, s. 112-117. ISBN 978-615-5044-00-7. [11th International PhD Workshop on Systems and Control. Veszprém (HU), 01.09.2010-03.09.2010] R&D Projects: GA ČR GA102/08/0567 Institutional research plan: CEZ:AV0Z10750506 Keywords : Supra-Bayesian approach * sharing of probabilistic information * Bayesian decision making Subject RIV: BC - Control Systems Theory http://library.utia.cas.cz/separaty/2010/AS/seckarova-supra-bayesian combination of probability distributions.pdf
Bayesian Soft Sensing in Cold Sheet Rolling
Czech Academy of Sciences Publication Activity Database
Dedecius, Kamil; Jirsa, Ladislav
Praha: ÚTIA AV ČR, v.v.i, 2010. s. 45-45. [6th International Workshop on Data–Algorithms–Decision Making. 2.12.2010-4.12.2010, Jindřichův Hradec] R&D Projects: GA MŠk(CZ) 7D09008 Institutional research plan: CEZ:AV0Z10750506 Keywords : soft sensor * bayesian statistics * bayesian model averaging Subject RIV: BB - Applied Statistics, Operational Research http://library.utia.cas.cz/separaty/2010/AS/dedecius-bayesian soft sensing in cold sheet rolling.pdf
Institute of Scientific and Technical Information of China (English)
无
2011-01-01
the diet composition of the lycian salamander lyciasalamandra luschani basoglui across both age and sex groups was studied.specimens were collected from a small island in the southeast aegean sea.the dominant prey group of juveniles consisted of collembola,while coleoptera dominated the diet of males and females.the number and size of prey items consumed by males and females of l.luschani basoglui were quite similar,while juveniles ate fewer items of much smaller size.the numerical abundance along with the four measures of the size of prey permitted discrimination among males,females and juveniles.although discrimination between adults and juveniles is expected due to dissimilarity in body size,discrimination between males and females remains inexplicable despite their similarity in body size.future studies should be focused on understanding how and why prey choice differs between sexes in l.luschani basoglui.
A population-based Bayesian approach to the minimal model of glucose and insulin homeostasis
DEFF Research Database (Denmark)
Andersen, Kim Emil; Højbjerre, Malene
2005-01-01
for a whole population. Traditionally it has been analysed in a deterministic set-up with only error terms on the measurements. In this work we adopt a Bayesian graphical model to describe the coupled minimal model that accounts for both measurement and process variability, and the model is extended...... to a population-based model. The estimation of the parameters are efficiently implemented in a Bayesian approach where posterior inference is made through the use of Markov chain Monte Carlo techniques. Hereby we obtain a powerful and flexible modelling framework for regularizing the ill-posed estimation problem...
A Bayesian Surrogate Model for Rapid Time Series Analysis and Application to Exoplanet Observations
Ford, Eric B; Veras, Dimitri
2011-01-01
We present a Bayesian surrogate model for the analysis of periodic or quasi-periodic time series data. We describe a computationally efficient implementation that enables Bayesian model comparison. We apply this model to simulated and real exoplanet observations. We discuss the results and demonstrate some of the challenges for applying our surrogate model to realistic exoplanet data sets. In particular, we find that analyses of real world data should pay careful attention to the effects of uneven spacing of observations and the choice of prior for the "jitter" parameter.
Application of Bayesian networks for risk analysis of MV air insulated switch operation
International Nuclear Information System (INIS)
Electricity distribution companies regard risk-based approaches as a good philosophy to address their asset management challenges, and there is an increasing trend on developing methods to support decisions where different aspects of risks are taken into consideration. This paper describes a methodology for application of Bayesian networks for risk analysis in electricity distribution system maintenance management. The methodology is used on a case analysing safety risk related to operation of MV air insulated switches. The paper summarises some challenges and benefits of using Bayesian networks as a part of distribution system maintenance management.
Directory of Open Access Journals (Sweden)
Caren S Goldberg
Full Text Available Stream ecosystems harbor many secretive and imperiled species, and studies of vertebrates in these systems face the challenges of relatively low detection rates and high costs. Environmental DNA (eDNA has recently been confirmed as a sensitive and efficient tool for documenting aquatic vertebrates in wetlands and in a large river and canal system. However, it was unclear whether this tool could be used to detect low-density vertebrates in fast-moving streams where shed cells may travel rapidly away from their source. To evaluate the potential utility of eDNA techniques in stream systems, we designed targeted primers to amplify a short, species-specific DNA fragment for two secretive stream amphibian species in the northwestern region of the United States (Rocky Mountain tailed frogs, Ascaphus montanus, and Idaho giant salamanders, Dicamptodon aterrimus. We tested three DNA extraction and five PCR protocols to determine whether we could detect eDNA of these species in filtered water samples from five streams with varying densities of these species in central Idaho, USA. We successfully amplified and sequenced the targeted DNA regions for both species from stream water filter samples. We detected Idaho giant salamanders in all samples and Rocky Mountain tailed frogs in four of five streams and found some indication that these species are more difficult to detect using eDNA in early spring than in early fall. While the sensitivity of this method across taxa remains to be determined, the use of eDNA could revolutionize surveys for rare and invasive stream species. With this study, the utility of eDNA techniques for detecting aquatic vertebrates has been demonstrated across the majority of freshwater systems, setting the stage for an innovative transformation in approaches for aquatic research.
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.
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++.
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
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++
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.
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.
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...
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...
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...
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...
Bayesian Network Models for Adaptive Testing
Czech Academy of Sciences Publication Activity Database
Plajner, Martin; Vomlel, Jiří
Achen: Sun SITE Central Europe, 2016 - (Agosta, J.; Carvalho, R.), s. 24-33. (CEUR Workshop Proceedings. Vol 1565). ISSN 1613-0073. [The Twelfth UAI Bayesian Modeling Applications Workshop (BMAW 2015). Amsterdam (NL), 16.07.2015] R&D Projects: GA ČR GA13-20012S Institutional support: RVO:67985556 Keywords : Bayesian networks * Computerized adaptive testing Subject RIV: JD - Computer Applications, Robotics http://library.utia.cas.cz/separaty/2016/MTR/plajner-0458062.pdf
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.
An Entropy Search Portfolio for Bayesian Optimization
Shahriari, Bobak; Wang, Ziyu; Hoffman, Matthew W.; Bouchard-Côté, Alexandre; De Freitas, Nando
2014-01-01
Bayesian optimization is a sample-efficient method for black-box global optimization. How- ever, the performance of a Bayesian optimization method very much depends on its exploration strategy, i.e. the choice of acquisition function, and it is not clear a priori which choice will result in superior performance. While portfolio methods provide an effective, principled way of combining a collection of acquisition functions, they are often based on measures of past performance which can be misl...
A Bayesian Framework for Active Artificial Perception
Ferreira, Joao; Lobo, Jorge; Bessiere, Pierre; Castelo-Branco, M; Dias, Jorge
2012-01-01
In this text, we present a Bayesian framework for active multimodal perception of 3D structure and motion. The design of this framework finds its inspiration in the role of the dorsal perceptual pathway of the human brain. Its composing models build upon a common egocentric spatial configuration that is naturally fitting for the integration of readings from multiple sensors using a Bayesian approach. In the process, we will contribute with efficient and robust probabilistic solutions for cycl...
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...
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.
Evaluation System for a Bayesian Optimization Service
Dewancker, Ian; McCourt, Michael; Clark, Scott; Hayes, Patrick; Johnson, Alexandra; Ke, George
2016-01-01
Bayesian optimization is an elegant solution to the hyperparameter optimization problem in machine learning. Building a reliable and robust Bayesian optimization service requires careful testing methodology and sound statistical analysis. In this talk we will outline our development of an evaluation framework to rigorously test and measure the impact of changes to the SigOpt optimization service. We present an overview of our evaluation system and discuss how this framework empowers our resea...
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 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 Approach to Handling Informative Sampling
Sikov, Anna
2015-01-01
In the case of informative sampling the sampling scheme explicitly or implicitly depends on the response variable. As a result, the sample distribution of response variable can- not be used for making inference about the population. In this research I investigate the problem of informative sampling from the Bayesian perspective. Application of the Bayesian approach permits solving the problems, which arise due to complexity of the models, being used for handling informative sampling. The main...
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
Perceptual decision making: Drift-diffusion model is equivalent to a Bayesian model
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Sebastian Bitzer
2014-02-01
Full Text Available Behavioural data obtained with perceptual decision making experiments are typically analysed with the drift-diffusion model. This parsimonious model accumulates noisy pieces of evidence towards a decision bound to explain the accuracy and reaction times of subjects. Recently, Bayesian models have been proposed to explain how the brain extracts information from noisy input as typically presented in perceptual decision making tasks. It has long been known that the drift-diffusion model is tightly linked with such functional Bayesian models but the precise relationship of the two mechanisms was never made explicit. Using a Bayesian model, we derived the equations which relate parameter values between these models. In practice we show that this equivalence is useful when fitting multi-subject data. We further show that the Bayesian model suggests different decision variables which all predict equal responses and discuss how these may be discriminated based on neural correlates of accumulated evidence. In addition, we discuss extensions to the Bayesian model which would be difficult to derive for the drift-diffusion model. We suggest that these and other extensions may be highly useful for deriving new experiments which test novel hypotheses.
Walker, Donald M.; Lawrence, Brandy R; Esterline, Dakota; Graham, Sean P.; Edelbrock, Michael A.; Wooten, Jessica A
2014-01-01
The flow of energy within an ecosystem can be considered either top-down, where predators influence consumers, or bottom-up, where producers influence consumers. Plethodon cinereus (Red-backed Salamander) is a terrestrial keystone predator who feeds on invertebrates within the ecosystem. We investigated the impact of the removal of P. cinereus on the detritivore food web in an upland deciduous forest in northwest Ohio, U.S.A. A total of eight aluminum enclosures, each containing a single P. c...
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Acely Garza-Garcia
Full Text Available BACKGROUND: Following the amputation of a limb, newts and salamanders have the capability to regenerate the lost tissues via a complex process that takes place at the site of injury. Initially these cells undergo dedifferentiation to a state competent to regenerate the missing limb structures. Crucially, dedifferentiated cells have memory of their level of origin along the proximodistal (PD axis of the limb, a property known as positional identity. Notophthalmus viridescens Prod1 is a cell-surface molecule of the three-finger protein (TFP superfamily involved in the specification of newt limb PD identity. The TFP superfamily is a highly diverse group of metazoan proteins that includes snake venom toxins, mammalian transmembrane receptors and miscellaneous signaling molecules. METHODOLOGY/PRINCIPAL FINDINGS: With the aim of identifying potential orthologs of Prod1, we have solved its 3D structure and compared it to other known TFPs using phylogenetic techniques. The analysis shows that TFP 3D structures group in different categories according to function. Prod1 clusters with other cell surface protein TFP domains including the complement regulator CD59 and the C-terminal domain of urokinase-type plasminogen activator. To infer orthology, a structure-based multiple sequence alignment of representative TFP family members was built and analyzed by phylogenetic methods. Prod1 has been proposed to be the salamander CD59 but our analysis fails to support this association. Prod1 is not a good match for any of the TFP families present in mammals and this result was further supported by the identification of the putative orthologs of both CD59 and N. viridescens Prod1 in sequence data for the salamander Ambystoma tigrinum. CONCLUSIONS/SIGNIFICANCE: The available data suggest that Prod1, and thereby its role in encoding PD identity, is restricted to salamanders. The lack of comparable limb-regenerative capability in other adult vertebrates could be
Niemiller, Matthew L.; Glorioso, Brad M.; Fenolio, Dante B.; Reynolds, R. Graham; Taylor, Steven J.; Miller, Brian T.
2016-01-01
Salamander species that live entirely in subterranean habitats have evolved adaptations that allow them to cope with perpetual darkness and limited energy resources. We conducted a 26-month mark–recapture study to better understand the individual growth and demography of a population of the Big Mouth Cave Salamander (Gyrinophilus palleucus necturoides). We employed a growth model to estimate growth rates, age at sexual maturity, and longevity, and an open population model to estimate population size, density, detectability, and survival rates. Furthermore, we examined cover use and evidence of potential predation. Individuals probably reach sexual maturity in 3–5 years and live at least nine years. Survival rates were generally high (>75%) but declined during the study. More than 30% of captured salamanders had regenerating tails or tail damage, which presumably represent predation attempts by conspecifics or crayfishes. Most salamanders (>90%) were found under cover (e.g., rocks, trash, decaying plant material). Based on 11 surveys during the study, population size estimates ranged from 21 to 104 individuals in the ca. 710 m2 study area. Previous surveys indicated that this population experienced a significant decline from the early 1970s through the 1990s, perhaps related to silvicultural and agricultural practices. However, our data suggest that this population has either recovered or stabilized during the past 20 years. Differences in relative abundance between early surveys and our survey could be associated with differences in survey methods or sampling conditions rather than an increase in population size. Regardless, our study demonstrates that this population is larger than previously thought and is in no immediate risk of extirpation, though it does appear to exhibit higher rates of predation than expected for a species believed to be an apex predator of subterranean food webs.
Smith, Jeramiah J.; Voss, S. Randal
2009-01-01
Little is known about the genetic basis of sex determination in vertebrates though considerable progress has been made in recent years. In this study, segregation analysis and linkage mapping were performed to localize an amphibian sex-determining locus (ambysex) in the tiger salamander (Ambystoma) genome. Segregation of sex phenotypes (male, female) among 2nd generation individuals of interspecific crosses (A. mexicanum x A. t. tigrinum) was consistent with Mendelian expectations, although a...
Denoël, Mathieu; Winandy, Laurane
2014-01-01
Alternative reproductive strategies are widespread in caudate amphibians. Among them, fire salamanders (Salamandra salamandra) usually rely on streams to give birth to aquatic larvae but also use ponds, whereas palmate newt larvae (Lissotriton helveticus) typically metamorphose into terrestrial juveniles, but can also reproduce in retaining their gills, a process known as paedomorphosis. Here we report repeated observations of an unusual case of coexistence of these two alternative traits in ...
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
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Mathieu Denoël
2014-06-01
Full Text Available Alternative reproductive strategies are widespread in caudate amphibians. Among them, fire salamanders (Salamandra salamandra usually rely on streams to give birth to aquatic larvae but also use ponds, whereas palmate newt larvae (Lissotriton helveticus typically metamorphose into terrestrial juveniles, but can also reproduce in retaining their gills, a process known as paedomorphosis. Here we report repeated observations of an unusual case of coexistence of these two alternative traits in the same pond (Larzac, France. The prevalence of fire salamanders in Southern Larzac was very low (pond occupancy: 0.36%. The observed abundance of fire salamander larvae and paedomorphic newts was also low in the studied pond. On one hand, the rarity of this coexistence pattern may suggest that habitat characteristics may not be optimal or that competition or predation processes might be operating. However, these hypotheses remain to be tested. On the other hand, as this is the only known case of breeding in Southern Larzac, it could be considered to be at a high risk of extirpation.
Inverse problems in the Bayesian framework
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The history of Bayesian methods dates back to the original works of Reverend Thomas Bayes and Pierre-Simon Laplace: the former laid down some of the basic principles on inverse probability in his classic article ‘An essay towards solving a problem in the doctrine of chances’ that was read posthumously in the Royal Society in 1763. Laplace, on the other hand, in his ‘Memoirs on inverse probability’ of 1774 developed the idea of updating beliefs and wrote down the celebrated Bayes’ formula in the form we know today. Although not identified yet as a framework for investigating inverse problems, Laplace used the formalism very much in the spirit it is used today in the context of inverse problems, e.g., in his study of the distribution of comets. With the evolution of computational tools, Bayesian methods have become increasingly popular in all fields of human knowledge in which conclusions need to be drawn based on incomplete and noisy data. Needless to say, inverse problems, almost by definition, fall into this category. Systematic work for developing a Bayesian inverse problem framework can arguably be traced back to the 1980s, (the original first edition being published by Elsevier in 1987), although articles on Bayesian methodology applied to inverse problems, in particular in geophysics, had appeared much earlier. Today, as testified by the articles in this special issue, the Bayesian methodology as a framework for considering inverse problems has gained a lot of popularity, and it has integrated very successfully with many traditional inverse problems ideas and techniques, providing novel ways to interpret and implement traditional procedures in numerical analysis, computational statistics, signal analysis and data assimilation. The range of applications where the Bayesian framework has been fundamental goes from geophysics, engineering and imaging to astronomy, life sciences and economy, and continues to grow. There is no question that Bayesian
Bayesian Vision for Shape Recovery
Jalobeanu, Andre
2004-01-01
We present a new Bayesian vision technique that aims at recovering a shape from two or more noisy observations taken under similar lighting conditions. The shape is parametrized by a piecewise linear height field, textured by a piecewise linear irradiance field, and we assume Gaussian Markovian priors for both shape vertices and irradiance variables. The observation process. also known as rendering, is modeled by a non-affine projection (e.g. perspective projection) followed by a convolution with a piecewise linear point spread function. and contamination by additive Gaussian noise. We assume that the observation parameters are calibrated beforehand. The major novelty of the proposed method consists of marginalizing out the irradiances considered as nuisance parameters, which is achieved by Laplace approximations. This reduces the inference to minimizing an energy that only depends on the shape vertices, and therefore allows an efficient Iterated Conditional Mode (ICM) optimization scheme to be implemented. A Gaussian approximation of the posterior shape density is computed, thus providing estimates both the geometry and its uncertainty. We illustrate the effectiveness of the new method by shape reconstruction results in a 2D case. A 3D version is currently under development and aims at recovering a surface from multiple images, reconstructing the topography by marginalizing out both albedo and shading.
BAYESIAN APPROACH OF DECISION PROBLEMS
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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 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.
Internal dosimetry of uranium isotopes using bayesian inference methods
International Nuclear Information System (INIS)
A group of personnel at Los Alamos National Laboratory is routinely monitored for the presence of uranium isotopes by urine bioassay. Samples are analysed by alpha spectroscopy, and the results are examined for evidence of an intake of uranium. Because the measurement uncertainties are often comparable to the quantities of material we wish to detect, statistical considerations are crucial for the proper interpretation of the data. The problem is further complicated by the significant, but highly non-uniform, presence of uranium in local drinking water and, in some cases, food supply. Software originally developed for internal dosimetry of plutonium has been adapted to the problem of uranium dosimetry. The software uses an unfolding algorithm to calculate an approximate Bayesian solution to the problem of characterising any intakes which may have occurred, given the history of urine bioassay results for each individual in the monitored population. The program uses biokinetic models from ICRP Publications 68 and later, and a prior probability distribution derived empirically from the body of uranium bioassay data collected at Los Alamos over the operating history of the Laboratory. For each individual, the software creates a posterior probability distribution of intake quantity and solubility type as a function of time. From this distribution, estimates are made of the cumulative committed dose (CEDE) to each individual. Results of the method are compared with those obtained using an earlier classical (non-Bayesian) algorithm for uranium dosimetry. We also discuss the problem of distinguishing occupational intakes from intake of environmental uranium, within a Bayesian framework. (author)
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.
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. PMID:27121574
Bayesian Methods for Medical Test Accuracy
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Lyle D. Broemeling
2011-05-01
Full Text Available Bayesian methods for medical test accuracy are presented, beginning with the basic measures for tests with binary scores: true positive fraction, false positive fraction, positive predictive values, and negative predictive value. The Bayesian approach is taken because of its efficient use of prior information, and the analysis is executed with a Bayesian software package WinBUGS®. The ROC (receiver operating characteristic curve gives the intrinsic accuracy of medical tests that have ordinal or continuous scores, and the Bayesian approach is illustrated with many examples from cancer and other diseases. Medical tests include X-ray, mammography, ultrasound, computed tomography, magnetic resonance imaging, nuclear medicine and tests based on biomarkers, such as blood glucose values for diabetes. The presentation continues with more specialized methods suitable for measuring the accuracies of clinical studies that have verification bias, and medical tests without a gold standard. Lastly, the review is concluded with Bayesian methods for measuring the accuracy of the combination of two or more tests.
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.
Institute of Scientific and Technical Information of China (English)
Cangsong CHEN; Jia YANG; Yunke WU; Zhongyong FAN; Weiwei LU; Shuihua CHEN; Lipeng YU
2016-01-01
Hynobius amjiensis is a critically endangered salamander species (IUCN Red List) endemic to eastern China. It currently has three known populations: one in Longwangshan, Zhejiang Province (type locality), and two in Qingliangfeng between Anhui and Zhejiang Provinces. We examined the relatively unstudied breeding ecology of this species in the field and at laboratory from March 2007 to May 2014. Adult males and females were year-round terrestrial, except for the February–April breeding season. During this period, we captured only a total of 16 breeding adults (11 males and 5 females). As few as 100 breeding females were estimated based on the number of egg sacs observed since 2007. This number was significantly reduced from the estimated number between 1992 and 1998. Males (mean total length = 16.21 cm, mean body mass = 18.8 g) were slightly smaller than females (16.51 cm, 19.2 g). Size of breeding pools ranged from 0.2 m2 to 1.2 m2 (0.1–1.2 m depths). Each female deposits a pair of egg sacs by attaching the adhesive tips of the sacs to aquatic plants or dead twigs. Fifteen pairs of egg sacs had an average length of 28.6 cm and a diameter of 3.3 cm. On average, each egg sac contained 75 eggs with a diameter of 0.3 cm. Our field survey revealed that H. amjiensis used oviposition sites in small, cool, and weakly acidic pools at high elevations (1 300–1 600 m) where peat moss was abundant. Reduction in wetland size and disappearance of suitable breeding pools suggest that this salamander species is under threat of extinction, particularly at Longwangshan, where 5 of the 9 breeding pools have either dried up or disappeared. Combined size of the remaining 4 pools is less than 2 m2. We urge immediate implementation of more effective conservation measures and suggest that preservation priority should be given to habitat that contains suitable breeding pools.
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.
Bayesian statistic methods and theri application in probabilistic simulation models
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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)
Bayesian analysis of inflationary features in Planck and SDSS data
Benetti, Micol
2016-01-01
We perform a Bayesian analysis to study possible features in the primordial inflationary power spectrum of scalar perturbations. In particular, we analyse the possibility of detecting the imprint of these primordial features in the anisotropy temperature power spectrum of the Cosmic Microwave Background (CMB) and also in the matter power spectrum P (k). We use the most recent CMB data provided by the Planck Collaboration and P (k) measurements from the eleventh data release of the Sloan Digital Sky Survey. We focus our analysis on a class of potentials whose features are localised at different intervals of angular scales, corresponding to multipoles in the ranges 10 < l < 60 (Oscill-1) and 150 < l < 300 (Oscill-2). Our results show that one of the step-potentials (Oscill-1) provides a better fit to the CMB data than does the featureless LCDM scenario, with a moderate Bayesian evidence in favor of the former. Adding the P (k) data to the analysis weakens the evidence of the Oscill-1 potential relat...
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.)
AIC, BIC, Bayesian evidence against the interacting dark energy model
Energy Technology Data Exchange (ETDEWEB)
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
International Nuclear Information System (INIS)
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
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...
BAMBI: blind accelerated multimodal Bayesian inference
Graff, Philip; Hobson, Michael P; Lasenby, Anthony
2011-01-01
In this paper we present an algorithm for rapid Bayesian analysis that combines the benefits of nested sampling and artificial neural networks. The blind accelerated multimodal Bayesian inference (BAMBI) algorithm implements the MultiNest package for nested sampling as well as the training of an artificial neural network (NN) to learn the likelihood function. In the case of computationally expensive likelihoods, this allows the substitution of a much more rapid approximation in order to increase significantly the speed of the analysis. We begin by demonstrating, with a few toy examples, the ability of a NN to learn complicated likelihood surfaces. BAMBI's ability to decrease running time for Bayesian inference is then demonstrated in the context of estimating cosmological parameters from WMAP and other observations. We show that valuable speed increases are achieved in addition to obtaining NNs trained on the likelihood functions for the different model and data combinations. These NNs can then be used for an...
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 Inference Methods for Sparse Channel Estimation
DEFF Research Database (Denmark)
Pedersen, Niels Lovmand
2013-01-01
inference algorithms based on the proposed prior representation for sparse channel estimation in orthogonal frequency-division multiplexing receivers. The inference algorithms, which are mainly obtained from variational Bayesian methods, exploit the underlying sparse structure of wireless channel responses......This thesis deals with sparse Bayesian learning (SBL) with application to radio channel estimation. As opposed to the classical approach for sparse signal representation, we focus on the problem of inferring complex signals. Our investigations within SBL constitute the basis for the development of...... Bayesian inference algorithms for sparse channel estimation. Sparse inference methods aim at finding the sparse representation of a signal given in some overcomplete dictionary of basis vectors. Within this context, one of our main contributions to the field of SBL is a hierarchical representation of...
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.
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...
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...
Revisiting k-means: New Algorithms via Bayesian Nonparametrics
Kulis, Brian; Jordan, Michael I.
2011-01-01
Bayesian models offer great flexibility for clustering applications---Bayesian nonparametrics can be used for modeling infinite mixtures, and hierarchical Bayesian models can be utilized for sharing clusters across multiple data sets. For the most part, such flexibility is lacking in classical clustering methods such as k-means. In this paper, we revisit the k-means clustering algorithm from a Bayesian nonparametric viewpoint. Inspired by the asymptotic connection between k-means and mixtures...
An Improved Algorithm of Bayesian Text Categorization
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Tao Dong
2011-08-01
Full Text Available Text categorization is a fundamental methodology of text mining and a hot topic of the research of data mining and web mining in recent years. It plays an important role in building traditional information retrieval, web indexing architecture, Web information retrieval, and so on. This paper presents an improved algorithm of text categorization that combines the feature weighting technique with Naïve Bayesian classifier. Experimental results show that using the improved Gini index algorithm to feature weight can improve the performance of Naïve Bayesian classifier effectively. This algorithm obtains good application in the sensitive information recognition system.
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.
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 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.…
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
A SAS Interface for Bayesian Analysis with WinBUGS
Zhang, Zhiyong; McArdle, John J.; Wang, Lijuan; Hamagami, Fumiaki
2008-01-01
Bayesian methods are becoming very popular despite some practical difficulties in implementation. To assist in the practical application of Bayesian methods, we show how to implement Bayesian analysis with WinBUGS as part of a standard set of SAS routines. This implementation procedure is first illustrated by fitting a multiple regression model…
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...
Directory of Open Access Journals (Sweden)
Niewiarowski Peter H
2006-07-01
Full Text Available Abstract Background In eastern North America two common colour morphs exist in most populations of redback salamanders (Plethodon cinereus. Previous studies have indicated that the different morphs may be adapted to different thermal niches and the morphological variation has been linked to standard metabolic rate at 15°C in one population of P. cinereus. It has therefore been hypothesized that a correlated response to selection on metabolic rate across thermal niches maintains the colour polymorphism in P. cinereus. This study tests that hypothesis. Results We found that the two colour morphs do sometimes differ in their maintenance metabolic rate (MMR profiles, but that the pattern is not consistent across populations or seasons. We also found that when MMR profiles differ between morphs those differences do not indicate that distinct niches exist. Field censuses showed that the two colour morphs are sometimes found at different substrate temperatures and that this difference is also dependent on census location and season. Conclusion While these morphs sometimes differ in their maintenance energy expenditures, the differences in MMR profile in this study are not consistent with maintenance of the polymorphism via a simple correlated response to selection across multiple niches. When present, differences in MMR profile do not indicate the existence of multiple thermal niches that consistently mirror colour polymorphism. We suggest that while a relationship between colour morph and thermal niche selection appears to exist it is neither simple nor consistent.
International Nuclear Information System (INIS)
Temperature has been shown to affect body color in several species of amphibians. The interaction between color and temperature may also change over larval ontogeny, perhaps because of age-related or seasonal changes in selection pressures on color. We quantified the effects of temperature on the color of the salamander sister species Ambystoma barbouri and Ambystoma texanum over larval ontogeny. We found that early-stage larvae responded to cold temperatures with a dark color relative to that of the warm temperature response. Both species then exhibited an ontogenetic shift in larval color, with larvae becoming lighter with age. Interestingly, older larvae showed decreased plasticity in color change to temperature when compared with younger stages. Older A. texanum larvae exhibited a reversal in the direction of color change, with cold temperatures inducing a lighter color relative to warm temperatures. We suggest that the overall pattern of color change (a plastic color response to temperature for young larvae, a progressive lightening of larvae over development, and an apparent loss of color plasticity to temperature over ontogeny) can be plausibly explained by seasonal changes in environmental factors (temperature, ultraviolet radiation) selecting for body color. (author)
Tyler, T.; Liss, W.J.; Hoffman, Robert L.; Ganio, L.
1998-01-01
Introduced fish have been implicated as reducing abundance or eliminating ambystomatid salamanders from montane lakes in western North America. We tested the null hypotheses that survivorship, growth, and refuge use of larvae reared for 30 d did not differ between artificial ponds with trout and without trout. Larval survivorship for both A. macrodactylum and A. gracile was significantly lower in ponds with trout than in fishless ponds. Both species had significantly lower snout-vent lengths in ponds with trout than in fishless ponds at the conclusion of the experiments. Only A. gracile had significantly lower body weight in ponds with trout than in ponds without trout. For both species, substrate locations of larvae were significantly influenced by trout at the conclusion of the experiments. Larvae of both species were found in a narrower range of substrates in ponds with fish than in control ponds. Our findings support inferences from field studies that the presence of trout have negative impacts on larval A. macrodactylum and A. gracile.
Calfee, Robin D.; Little, Edward E.; Pearl, Christopher A.; Hoffman, Robert L.
2010-01-01
Solar ultraviolet radiation (UV) has received much attention as a factor that could play a role in amphibian population declines. UV can be hazardous to some amphibians, but the resultant effects depend on a variety of environmental and behavioral factors. In this study, the potential effects of UV on the Northwestern Salamander, Ambystoma gracile, from three lakes were assessed in the laboratory using a solar simulator. We measured the survival of embryos and the survival and growth of larvae exposed to four UV treatments in controlled laboratory studies, the UV absorbance of egg jelly, oviposition depths in the lakes, and UV absorbance in water samples from the three lakes. Hatching success of embryos decreased in the higher UV treatments as compared to the control treatments, and growth of surviving larvae was significantly reduced in the higher UVB irradiance treatments. The egg jelly exhibited a small peak of absorbance within the UVB range (290–320 nm). The magnitude of UV absorbance differed among egg jellies from the three lakes. Oviposition depths at the three sites averaged 1.10 m below the water surface. Approximately 66% of surface UVB radiation was attenuated at 10-cm depth in all three lakes. Results of this study indicate that larvae may be sensitive to UVB exposure under laboratory conditions; however, in field conditions the depths of egg deposition in the lakes, absorbance of UV radiation by the water column, and the potential for behavioral adjustments may mitigate severe effects of UV radiation.
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
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.
Definition of Valid Proteomic Biomarkers: A Bayesian Solution
Harris, Keith; Girolami, Mark; Mischak, Harald
Clinical proteomics is suffering from high hopes generated by reports on apparent biomarkers, most of which could not be later substantiated via validation. This has brought into focus the need for improved methods of finding a panel of clearly defined biomarkers. To examine this problem, urinary proteome data was collected from healthy adult males and females, and analysed to find biomarkers that differentiated between genders. We believe that models that incorporate sparsity in terms of variables are desirable for biomarker selection, as proteomics data typically contains a huge number of variables (peptides) and few samples making the selection process potentially unstable. This suggests the application of a two-level hierarchical Bayesian probit regression model for variable selection which assumes a prior that favours sparseness. The classification performance of this method is shown to improve that of the Probabilistic K-Nearest Neighbour model.
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...
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
Integer variables estimation problems: the Bayesian approach
Directory of Open Access Journals (Sweden)
G. Venuti
1997-06-01
Full Text Available In geodesy as well as in geophysics there are a number of examples where the unknown parameters are partly constrained to be integer numbers, while other parameters have a continuous range of possible values. In all such situations the ordinary least square principle, with integer variates fixed to the most probable integer value, can lead to paradoxical results, due to the strong non-linearity of the manifold of admissible values. On the contrary an overall estimation procedure assigning the posterior distribution to all variables, discrete and continuous, conditional to the observed quantities, like the so-called Bayesian approach, has the advantage of weighting correctly the possible errors in choosing different sets of integer values, thus providing a more realistic and stable estimate even of the continuous parameters. In this paper, after a short recall of the basics of Bayesian theory in section 2, we present the natural Bayesian solution to the problem of assessing the estimable signal from noisy observations in section 3 and the Bayesian solution to cycle slips detection and repair for a stream of GPS measurements in section 4. An elementary synthetic example is discussed in section 3 to illustrate the theory presented and more elaborate, though synthetic, examples are discussed in section 4 where realistic streams of GPS observations, with cycle slips, are simulated and then back processed.
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 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 is l...
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.
Explanation mode for Bayesian automatic object recognition
Hazlett, Thomas L.; Cofer, Rufus H.; Brown, Harold K.
1992-09-01
One of the more useful techniques to emerge from AI is the provision of an explanation modality used by the researcher to understand and subsequently tune the reasoning of an expert system. Such a capability, missing in the arena of statistical object recognition, is not that difficult to provide. Long standing results show that the paradigm of Bayesian object recognition is truly optimal in a minimum probability of error sense. To a large degree, the Bayesian paradigm achieves optimality through adroit fusion of a wide range of lower informational data sources to give a higher quality decision--a very 'expert system' like capability. When various sources of incoming data are represented by C++ classes, it becomes possible to automatically backtrack the Bayesian data fusion process, assigning relative weights to the more significant datums and their combinations. A C++ object oriented engine is then able to synthesize 'English' like textural description of the Bayesian reasoning suitable for generalized presentation. Key concepts and examples are provided based on an actual object recognition problem.
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.
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
On Bayesian Nonparametric Continuous Time Series Models
Karabatsos, George; Walker, Stephen G.
2013-01-01
This paper is a note on the use of Bayesian nonparametric mixture models for continuous time series. We identify a key requirement for such models, and then establish that there is a single type of model which meets this requirement. As it turns out, the model is well known in multiple change-point problems.
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
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 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 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
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.
Optimized Bayesian dynamic advising theory and algorithms
Karny, Miroslav
2006-01-01
Written by one of the world''s leading groups in the area of Bayesian identification, control, and decision making, this book provides the theoretical and algorithmic basis of optimized probabilistic advising. It is accompanied by a CD that contains a specialized Matlab-based Mixtools toolbox, and examples illustrating the important areas.
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,...
An Approximate Bayesian Fundamental Frequency Estimator
DEFF Research Database (Denmark)
Nielsen, Jesper Kjær; Christensen, Mads Græsbøll; Jensen, Søren Holdt
Joint fundamental frequency and model order estimation is an important problem in several applications such as speech and music processing. In this paper, we develop an approximate estimation algorithm of these quantities using Bayesian inference. The inference about the fundamental frequency and...
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. The...
Sensitivity to Sampling in Bayesian Word Learning
Xu, Fei; Tenenbaum, Joshua B.
2007-01-01
We report a new study testing our proposal that word learning may be best explained as an approximate form of Bayesian inference (Xu & Tenenbaum, in press). Children are capable of learning word meanings across a wide range of communicative contexts. In different contexts, learners may encounter different sampling processes generating the examples…
International Nuclear Information System (INIS)
In Bayesian inference, the initial knowledge regarding the value of a parameter, before additional data are considered, is represented as a prior probability distribution. This paper describes the derivation of a prior distribution of intake that was used for the Bayesian analysis of plutonium and uranium worker doses in a recent epidemiology study. The chosen distribution is log- normal with a geometric standard deviation of 6 and a median value that is derived for each worker based on the duration of the work history and the number of reported acute intakes. The median value is a function of the work history and a constant related to activity in air concentration, M, which is derived separately for uranium and plutonium. The value of M is based primarily on measurements of plutonium and uranium in air derived from historical personal air sampler (PAS) data. However, there is significant uncertainty on the value of M that results from paucity of PAS data and from extrapolating these measurements to actual intakes. This paper compares posterior and prior distributions of intake and investigates the sensitivity of the Bayesian analyses to the assumed value of M. It is found that varying M by a factor of 10 results in a much smaller factor of 2 variation in mean intake and lung dose for both plutonium and uranium. It is concluded that if a log-normal distribution is considered to adequately represent worker intakes, then the Bayesian posterior distribution of dose is relatively insensitive to the value assumed of M. (authors)
A Bayesian Decision-Theoretic Approach to Logically-Consistent Hypothesis Testing
Directory of Open Access Journals (Sweden)
Gustavo Miranda da Silva
2015-09-01
Full Text Available This work addresses an important issue regarding the performance of simultaneous test procedures: the construction of multiple tests that at the same time are optimal from a statistical perspective and that also yield logically-consistent results that are easy to communicate to practitioners of statistical methods. For instance, if hypothesis A implies hypothesis B, is it possible to create optimal testing procedures that reject A whenever they reject B? Unfortunately, several standard testing procedures fail in having such logical consistency. Although this has been deeply investigated under a frequentist perspective, the literature lacks analyses under a Bayesian paradigm. In this work, we contribute to the discussion by investigating three rational relationships under a Bayesian decision-theoretic standpoint: coherence, invertibility and union consonance. We characterize and illustrate through simple examples optimal Bayes tests that fulfill each of these requisites separately. We also explore how far one can go by putting these requirements together. We show that although fairly intuitive tests satisfy both coherence and invertibility, no Bayesian testing scheme meets the desiderata as a whole, strengthening the understanding that logical consistency cannot be combined with statistical optimality in general. Finally, we associate Bayesian hypothesis testing with Bayes point estimation procedures. We prove the performance of logically-consistent hypothesis testing by means of a Bayes point estimator to be optimal only under very restrictive conditions.
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...
Institute of Scientific and Technical Information of China (English)
罗庆华; 谢文海; 王朝群; 陈秋宇; 王金平; 朱深海
2013-01-01
In order to ascertain the development strategy for Chinese giant salamander (Andrias davidianus) industry in Zhangjiajie City, the internal conditions and external circumstances of Chinese giant salamander industry in Zhangjiajie City were analyzed systematically by SWOT analysis, and the basic model on the development strategy was set up. After four strategies were discriminated and discussed detailed, it was selected as the development strategy that SO strategy was main and WT strategy was supplemented, because its strength(S) was more than weakness in internal conditions, its opportunity(O) was more than its threat(T) in external circumstances and weakness and threat must been valued. The implementation ways of development strategy were explored, they were thought the feasible implement approaches that resource protection of Chinese giant salamander was strengthened, standardized mass production was advanced, industrial chain was stretched, related industries were advanced, brand strategy was implemented and service system was improved. It can provide reference for strategy decision and planning for Chinese giant salamander industry in Zhangjiajie City.%为了明确张家界市大鲵产业发展战略，应用SWOT分析法，对张家界市大鲵产业内部条件的和外部环境进行了系统分析，构建了产业发展战略模型。对4种战略进行甄别与选择，认为：张家界市大鲵产业的内部优势大于劣势；外部机遇大于威胁；同时，必须重视产业劣势与威胁的存在，张家界市大鲵产业发展战略应以增长型战略(SO)为主，以防御型战略(WT)为辅。探讨大鲵产业战略的实现途径，认为加强大鲵资源保护、推进标准化规模生产、延伸产业链、推进产业关联、实施品牌战略与健全服务体系为其可行的实施途径。为张家界市大鲵产业战略决策与产业规划提供借鉴。
Steinfartz, Sebastian; Vicario, Saverio; Arntzen, J W; Caccone, Adalgisa
2007-03-15
The monophyly of European newts of the genus Triturus within the family Salamandridae has for decades rested on presumably homologous behavioral and morphological characters. Molecular data challenge this hypothesis, but the phylogenetic position of Triturus within the Salamandridae has not yet been convincingly resolved. We addressed this issue and the temporal divergence of Triturus within the Salamandridae with novel Bayesian approaches applied to DNA sequence data from three mitochondrial genes (12S, 16S and cytb). We included 38 salamandrid species comprising all 13 recognized species of Triturus and 16 out of 17 salamandrid genera. A clade comprising all the "Newts" can be separated from the "True Salamanders" and Salamandrina clades. Within the "Newts" well-supported clades are: Tylototriton-Pleurodeles, the "New World Newts" (Notophthalmus-Taricha), and the "Modern Eurasian Newts" (Cynops, Pachytriton, Paramesotriton=together the "Modern Asian Newts", Calotriton, Euproctus, Neurergus and Triturus species). We found that Triturus is a non-monophyletic species assemblage, which includes four groups that are themselves monophyletic: (i) the "Large-Bodied Triturus" (six species), (ii) the "Small-Bodied Triturus" (five species), (iii) T. alpestris and (iv) T. vittatus. We estimated that the last common ancestor of Triturus existed around 64 million years ago (mya) while the root of the Salamandridae dates back to 95 mya. This was estimated using a fossil-based molecular dating approach and an explicit framework to select calibration points that least underestimated their corresponding nodes. Using the molecular phylogeny we mapped the evolution of life history and courtship traits in Triturus and found that several Triturus-specific courtship traits evolved independently. PMID:16969762
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
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
Pereira, Ricardo J; Martínez-Solano, Iñigo; Buckley, David
2016-04-01
Ecological models predict that, in the face of climate change, taxa occupying steep altitudinal gradients will shift their distributions, leading to the contraction or extinction of the high-elevation (cold-adapted) taxa. However, hybridization between ecomorphologically divergent taxa commonly occurs in nature and may lead to alternative evolutionary outcomes, such as genetic merger or gene flow at specific genes. We evaluate this hypothesis by studying patterns of divergence and gene flow across three replicate contact zones between high- and low-elevation ecomorphs of the fire salamander (Salamandra salamandra) that have experienced altitudinal range shifts over the current postglacial period. Strong population structure with high genetic divergence in mitochondrial DNA suggests that vicariant evolution has occurred over several glacial-interglacial cycles and that it has led to cryptic differentiation within ecomorphs. In current parapatric boundaries, we do not find evidence for local extinction and replacement upon postglacial expansion. Instead, parapatric taxa recurrently show discordance between mitochondrial and nuclear markers, suggesting nuclear-mediated gene flow across contact zones. Isolation with migration models support this hypothesis by showing significant gene flow across all five parapatric boundaries. Together, our results suggest that, while some genomic regions, such as the mitochondria, may follow morphologic species traits and retreat to isolated mountain tops, other genomic regions, such as nuclear markers, may flow across parapatric boundaries, sometimes leading to a complete genetic merger. We show that despite high ecologic and morphologic divergence over prolonged periods of time, hybridization allows for evolutionary outcomes alternative to extinction and replacement of taxa in response to climate change. PMID:26850834
Calfee, R.D.; Little, E.E.; Pearl, C.A.; Hoffman, R.L.
2010-01-01
Solar ultraviolet radiation (UV) has received much attention as a factor that could play a role in amphibian population declines. UV can be hazardous to some amphibians, but the resultant effects depend on a variety of environmental and behavioral factors. In this study, the potential effects of UV on the Northwestern Salamander, Ambystoma gracile, from three lakes were assessed in the laboratory using a solar simulator. We measured the survival of embryos and the survival and growth of larvae exposed to four UV treatments in controlled laboratory studies, the UV absorbance of egg jelly, oviposition depths in the lakes, and UV absorbance in water samples from the three lakes. Hatching success of embryos decreased in the higher UV treatments as compared to the control treatments, and growth of surviving larvae was significantly reduced in the higher UVB irradiance treatments. The egg jelly exhibited a small peak of absorbance within the UVB range (290-320 nm). The magnitude of UV absorbance differed among egg jellies from the three lakes. Oviposition depths at the three sites averaged 1.10 m below the water surface. Approximately 66 of surface UVB radiation was attenuated at 10-cm depth in all three lakes. Results of this study indicate that larvae may be sensitive to UVB exposure under laboratory conditions; however, in field conditions the depths of egg deposition in the lakes, absorbance of UV radiation by the water column, and the potential for behavioral adjustments may mitigate severe effects of UV radiation. Copyright 2010 Society for the Study of Amphibians and Reptiles.
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.
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.
The NIFTY way of Bayesian signal inference
International Nuclear Information System (INIS)
We introduce NIFTY, 'Numerical Information Field Theory', a software package for the development of Bayesian signal inference algorithms that operate independently from any underlying spatial grid and its resolution. A large number of Bayesian and Maximum Entropy methods for 1D signal reconstruction, 2D imaging, as well as 3D tomography, appear formally similar, but one often finds individualized implementations that are neither flexible nor easily transferable. Signal inference in the framework of NIFTY can be done in an abstract way, such that algorithms, prototyped in 1D, can be applied to real world problems in higher-dimensional settings. NIFTY as a versatile library is applicable and already has been applied in 1D, 2D, 3D and spherical settings. A recent application is the D3PO algorithm targeting the non-trivial task of denoising, deconvolving, and decomposing photon observations in high energy astronomy
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.
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...
A Bayesian Probabilistic Framework for Rain Detection
Directory of Open Access Journals (Sweden)
Chen Yao
2014-06-01
Full Text Available Heavy rain deteriorates the video quality of outdoor imaging equipments. In order to improve video clearness, image-based and sensor-based methods are adopted for rain detection. In earlier literature, image-based detection methods fall into spatio-based and temporal-based categories. In this paper, we propose a new image-based method by exploring spatio-temporal united constraints in a Bayesian framework. In our framework, rain temporal motion is assumed to be Pathological Motion (PM, which is more suitable to time-varying character of rain steaks. Temporal displaced frame discontinuity and spatial Gaussian mixture model are utilized in the whole framework. Iterated expectation maximization solving method is taken for Gaussian parameters estimation. Pixels state estimation is finished by an iterated optimization method in Bayesian probability formulation. The experimental results highlight the advantage of our method in rain detection.
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...
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 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.
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...
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 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...
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.
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.
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.
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
Social optimality in quantum Bayesian games
Iqbal, Azhar; Chappell, James M.; Abbott, Derek
2015-10-01
A significant aspect of the study of quantum strategies is the exploration of the game-theoretic solution concept of the Nash equilibrium in relation to the quantization of a game. Pareto optimality is a refinement on the set of Nash equilibria. A refinement on the set of Pareto optimal outcomes is known as social optimality in which the sum of players' payoffs is maximized. This paper analyzes social optimality in a Bayesian game that uses the setting of generalized Einstein-Podolsky-Rosen experiments for its physical implementation. We show that for the quantum Bayesian game a direct connection appears between the violation of Bell's inequality and the social optimal outcome of the game and that it attains a superior socially optimal outcome.
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...... mechanism efficiently combines distributed learner models without the need to exchange internal structure of local Bayesian networks, nor local evidence between the involved platforms....
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.
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
Quantum-like Representation of Bayesian Updating
Asano, Masanari; Ohya, Masanori; Tanaka, Yoshiharu; Khrennikov, Andrei; Basieva, Irina
2011-03-01
Recently, applications of quantum mechanics to coginitive psychology have been discussed, see [1]-[11]. It was known that statistical data obtained in some experiments of cognitive psychology cannot be described by classical probability model (Kolmogorov's model) [12]-[15]. Quantum probability is one of the most advanced mathematical models for non-classical probability. In the paper of [11], we proposed a quantum-like model describing decision-making process in a two-player game, where we used the generalized quantum formalism based on lifting of density operators [16]. In this paper, we discuss the quantum-like representation of Bayesian inference, which has been used to calculate probabilities for decision making under uncertainty. The uncertainty is described in the form of quantum superposition, and Bayesian updating is explained as a reduction of state by quantum measurement.
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...
Advanced Bayesian Method for Planetary Surface Navigation
Center, Julian
2015-01-01
Autonomous Exploration, Inc., has developed an advanced Bayesian statistical inference method that leverages current computing technology to produce a highly accurate surface navigation system. The method combines dense stereo vision and high-speed optical flow to implement visual odometry (VO) to track faster rover movements. The Bayesian VO technique improves performance by using all image information rather than corner features only. The method determines what can be learned from each image pixel and weighs the information accordingly. This capability improves performance in shadowed areas that yield only low-contrast images. The error characteristics of the visual processing are complementary to those of a low-cost inertial measurement unit (IMU), so the combination of the two capabilities provides highly accurate navigation. The method increases NASA mission productivity by enabling faster rover speed and accuracy. On Earth, the technology will permit operation of robots and autonomous vehicles in areas where the Global Positioning System (GPS) is degraded or unavailable.
Bayesian Predictive Distribution for the Magnitude of the Largest Aftershock
Shcherbakov, R.
2014-12-01
Aftershock sequences, which follow large earthquakes, last hundreds of days and are characterized by well defined frequency-magnitude and spatio-temporal distributions. The largest aftershocks in a sequence constitute significant hazard and can inflict additional damage to infrastructure. Therefore, the estimation of the magnitude of possible largest aftershocks in a sequence is of high importance. In this work, we propose a statistical model based on Bayesian analysis and extreme value statistics to describe the distribution of magnitudes of the largest aftershocks in a sequence. We derive an analytical expression for a Bayesian predictive distribution function for the magnitude of the largest expected aftershock and compute the corresponding confidence intervals. We assume that the occurrence of aftershocks can be modeled, to a good approximation, by a non-homogeneous Poisson process with a temporal event rate given by the modified Omori law. We also assume that the frequency-magnitude statistics of aftershocks can be approximated by Gutenberg-Richter scaling. We apply our analysis to 19 prominent aftershock sequences, which occurred in the last 30 years, in order to compute the Bayesian predictive distributions and the corresponding confidence intervals. In the analysis, we use the information of the early aftershocks in the sequences (in the first 1, 10, and 30 days after the main shock) to estimate retrospectively the confidence intervals for the magnitude of the expected largest aftershocks. We demonstrate by analysing 19 past sequences that in many cases we are able to constrain the magnitudes of the largest aftershocks. For example, this includes the analysis of the Darfield (Christchurch) aftershock sequence. The proposed analysis can be used for the earthquake hazard assessment and forecasting associated with the occurrence of large aftershocks. The improvement in instrumental data associated with early aftershocks can greatly enhance the analysis and
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 ...
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...
Centralized Bayesian reliability modelling with sensor networks
Czech Academy of Sciences Publication Activity Database
Dedecius, Kamil; Sečkárová, Vladimíra
2013-01-01
Roč. 19, č. 5 (2013), s. 471-482. ISSN 1387-3954 R&D Projects: GA MŠk 7D12004 Grant ostatní: GA MŠk(CZ) SVV-265315 Keywords : Bayesian modelling * Sensor network * Reliability Subject RIV: BD - Theory of Information Impact factor: 0.984, year: 2013 http://library.utia.cas.cz/separaty/2013/AS/dedecius-0392551.pdf
Characteristic imsets for learning Bayesian network structure
Czech Academy of Sciences Publication Activity Database
Hemmecke, R.; Lindner, S.; Studený, Milan
2012-01-01
Roč. 53, č. 9 (2012), s. 1336-1349. ISSN 0888-613X R&D Projects: GA MŠk(CZ) 1M0572; GA ČR GA201/08/0539 Institutional support: RVO:67985556 Keywords : learning Bayesian network structure * essential graph * standard imset * characteristic imset * LP relaxation of a polytope Subject RIV: BA - General Mathematics Impact factor: 1.729, year: 2012 http://library.utia.cas.cz/separaty/2012/MTR/studeny-0382596.pdf
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...
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...
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...
Constrained bayesian inference of project performance models
Sunmola, Funlade
2013-01-01
Project performance models play an important role in the management of project success. When used for monitoring projects, they can offer predictive ability such as indications of possible delivery problems. Approaches for monitoring project performance relies on available project information including restrictions imposed on the project, particularly the constraints of cost, quality, scope and time. We study in this paper a Bayesian inference methodology for project performance modelling in ...
Dual Control for Approximate Bayesian Reinforcement Learning
Klenske, Edgar D.; Hennig, Philipp
2015-01-01
Control of non-episodic, finite-horizon dynamical systems with uncertain dynamics poses a tough and elementary case of the exploration-exploitation trade-off. Bayesian reinforcement learning, reasoning about the effect of actions and future observations, offers a principled solution, but is intractable. We review, then extend an old approximate approach from control theory---where the problem is known as dual control---in the context of modern regression methods, specifically generalized line...
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...
A Theory of Bayesian Decision Making
Karni, Edi
2009-01-01
This paper presents a complete, choice-based, axiomatic Bayesian decision theory. It introduces a new choice set consisting of information-contingent plans for choosing actions and bets and subjective expected utility model with effect-dependent utility functions and action-dependent subjective probabilities which, in conjunction with the updating of the probabilities using Bayes' rule, gives rise to a unique prior and a set of action-dependent posterior probabilities representing the decisio...
A Bayesian framework for robotic programming
Lebeltel, Olivier; Diard, Julien; Bessiere, Pierre; Mazer, Emmanuel
2000-01-01
We propose an original method for programming robots based on Bayesian inference and learning. This method formally deals with problems of uncertainty and incomplete information that are inherent to the field. Indeed, the principal difficulties of robot programming comes from the unavoidable incompleteness of the models used. We present the formalism for describing a robotic task as well as the resolution methods. This formalism is inspired by the theory of probability, suggested by the physi...
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.
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...
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). ...
Summary Statistics in Approximate Bayesian Computation
Prangle, Dennis
2015-01-01
This document is due to appear as a chapter of the forthcoming Handbook of Approximate Bayesian Computation (ABC) edited by S. Sisson, Y. Fan, and M. Beaumont. Since the earliest work on ABC, it has been recognised that using summary statistics is essential to produce useful inference results. This is because ABC suffers from a curse of dimensionality effect, whereby using high dimensional inputs causes large approximation errors in the output. It is therefore crucial to find low dimensional ...
Bayesian Semiparametric Modeling of Realized Covariance Matrices
Jin, Xin; John M Maheu
2014-01-01
This paper introduces several new Bayesian nonparametric models suitable for capturing the unknown conditional distribution of realized covariance (RCOV) matrices. Existing dynamic Wishart models are extended to countably infinite mixture models of Wishart and inverse-Wishart distributions. In addition to mixture models with constant weights we propose models with time-varying weights to capture time dependence in the unknown distribution. Each of our models can be combined with returns...
BEAST: Bayesian evolutionary analysis by sampling trees
Drummond Alexei J; Rambaut Andrew
2007-01-01
Abstract Background The evolutionary analysis of molecular sequence variation is a statistical enterprise. This is reflected in the increased use of probabilistic models for phylogenetic inference, multiple sequence alignment, and molecular population genetics. Here we present BEAST: a fast, flexible software architecture for Bayesian analysis of molecular sequences related by an evolutionary tree. A large number of popular stochastic models of sequence evolution are provided and tree-based m...
BEAST: Bayesian evolutionary analysis by sampling trees
Drummond, Alexei J.; Rambaut, Andrew
2007-01-01
Background: The evolutionary analysis of molecular sequence variation is a statistical enterprise. This is reflected in the increased use of probabilistic models for phylogenetic inference, multiple sequence alignment, and molecular population genetics. Here we present BEAST: a fast, flexible software architecture for Bayesian analysis of molecular sequences related by an evolutionary tree. A large number of popular stochastic models of sequence evolution are provided and tree-based models su...
Benchmarking dynamic Bayesian network structure learning algorithms
Trabelsi, Ghada; Leray, Philippe; Ben Ayed, Mounir; Alimi, Adel
2012-01-01
Dynamic Bayesian Networks (DBNs) are probabilistic graphical models dedicated to modeling multivariate time series. Two-time slice BNs (2-TBNs) are the most current type of these models. Static BN structure learning is a well-studied domain. Many approaches have been proposed and the quality of these algorithms has been studied over a range of di erent standard networks and methods of evaluation. To the best of our knowledge, all studies about DBN structure learning use their own benchmarks a...
Bayesian Multi-Scale Optimistic Optimization
Wang, Ziyu; Shakibi, Babak; Jin, Lin; De Freitas, Nando
2014-01-01
Bayesian optimization is a powerful global optimization technique for expensive black-box functions. One of its shortcomings is that it requires auxiliary optimization of an acquisition function at each iteration. This auxiliary optimization can be costly and very hard to carry out in practice. Moreover, it creates serious theoretical concerns, as most of the convergence results assume that the exact optimum of the acquisition function can be found. In this paper, we introduce a new technique...
Bayesian mixture models for Poisson astronomical images
Guglielmetti, Fabrizia; Fischer, Rainer; Dose, Volker
2012-01-01
Astronomical images in the Poisson regime are typically characterized by a spatially varying cosmic background, large variety of source morphologies and intensities, data incompleteness, steep gradients in the data, and few photon counts per pixel. The Background-Source separation technique is developed with the aim to detect faint and extended sources in astronomical images characterized by Poisson statistics. The technique employs Bayesian mixture models to reliably detect the background as...
Complex Bayesian models: construction, and sampling strategies
Huston, Carolyn Marie
2011-01-01
Bayesian models are useful tools for realistically modeling processes occurring in the real world. In particular, we consider models for spatio-temporal data where the response vector is compositional, ie. has components that sum-to-one. A unique multivariate conditional hierarchical model (MVCAR) is proposed. Statistical methods for MVCAR models are well developed and we extend these tools for use with a discrete compositional response. We harness the advantages of an MVCAR model when the re...
The variational Bayes approximation in Bayesian filtering
Czech Academy of Sciences Publication Activity Database
Šmídl, Václav; Quinn, A.
Bryan : IEEE, 2006, s. 1-4. ISBN 1-4244-0469-X. [IEEE International Conference on Acoustics , Speech and Signal Processing. Toulouse (FR), 14.05.2006-19.05.2006] R&D Projects: GA AV ČR 1ET100750401; GA MŠk 1M0572 Institutional research plan: CEZ:AV0Z10750506 Keywords : variational Bayes * Bayesian filtering Subject RIV: BD - Theory of Information
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...
On-line Bayesian System Identification
Romeres, Diego; Prando, Giulia; Pillonetto, Gianluigi; Chiuso, Alessandro
2016-01-01
We consider an on-line system identification setting, in which new data become available at given time steps. In order to meet real-time estimation requirements, we propose a tailored Bayesian system identification procedure, in which the hyper-parameters are still updated through Marginal Likelihood maximization, but after only one iteration of a suitable iterative optimization algorithm. Both gradient methods and the EM algorithm are considered for the Marginal Likelihood optimization. We c...
Dynamic Bayesian Networks for Cue Integration
Paul Maier; Frederike Petzschner
2012-01-01
If we want to understand how humans use contextual cues to solve tasks such as estimating distances from optic flow during path integration, our models need to represent the available information and formally describe how these representations are processed. In particular the temporal dynamics need to be incorporated, since it has been shown that humans exploit short-term experience gained in previous trials (Petzschner und Glasauer, 2011). Existing studies often use a Bayesian approach to mo...
The Bayesian Second Law of Thermodynamics
Bartolotta, Anthony; Carroll, Sean M.; Leichenauer, Stefan; Pollack, Jason
2015-01-01
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...