Energy Technology Data Exchange (ETDEWEB)
Stahle, David (Tree-Ring Laboratory, University of Arkansas)
2003-02-12
The original presettlement forests of North America have been dramatically altered, but thousands of unmolested ancient forests survive on remote or noncommercial terrain, including dry-site eastern hardwoods such as chestnut oak and post oak, the pinyon-juniper woodlands of the semiarid West, oak woodlands of California and in northeast Mexico, and the boreal forests of Canada and Alaska. Long tree-ring chronologies derived from these ancient forest remnants provide irreplaceable archives of environmental variability which are crucial for evaluating present and future change. Temperature sensitive tree -ring chronologies from cold treeline environments place 20th century warming into long historical perspective, and moisture sensitive tree-ring chronologies provide analogs to the decadal moisture regimes of the 20th century. These tree-ring data suggests that the 16th century megadrought was the most severe-sustained drought to impact North America in 1500 years, and had huge environmental and social impacts at the dawn of European settlement.
Diversity of Ancient Woody Species in Urban Forests
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Fornal-Pieniak Beata
2014-06-01
Full Text Available Mostly parks and forest are the most important ‘green islands’ in urban ecological network. Urban forests are belong to green areas and collected many plant species. The main aim of the article was characteristic of ancient plant species in urban forests in Tarnów. The field studies were carried out in years 2011-2012. It covered 80 phytosociological records on the area 500 m2 in herb layer of urban forests and in forest nature on oak-hornbeam. The results showed that many ancient plant species were growing in urban forest but less than in nature reserves
Dating ancient Chinese celadon porcelain by neutron activation analysis and bayesian classification
International Nuclear Information System (INIS)
Dating ancient Chinese porcelain is one of the most important and difficult problems in porcelain archaeological field. Eighteen elements in bodies of ancient celadon porcelains fired in Southern Song to Yuan period (AD 1127-1368) and Ming dynasty (AD 1368-1644), including La, Sm, U, Ce, etc., were determined by neutron activation analysis (NAA). After the outliers of experimental data were excluded and multivariate normal distribution was tested, and Bayesian classification was used for dating of 165 ancient celadon porcelain samples. The results show that 98.2% of total ancient celadon porcelain samples are classified correctly. It means that NAA and Bayesian classification are very useful for dating ancient porcelain. (authors)
Directory of Open Access Journals (Sweden)
Duo ePeng
2014-11-01
Full Text Available Sucrose transporters (SUTs are essential for the export and efficient movement of sucrose from source leaves to sink organs in plants. The angiosperm SUT family was previously classified into three or four distinct groups, Types I, II (subgroup IIB and III, with dicot-specific Type I and monocot-specific Type IIB functioning in phloem loading. To shed light on the underlying drivers of SUT evolution, Bayesian phylogenetic inference was undertaken using 41 sequenced plant genomes, including seven basal lineages at key evolutionary junctures. Our analysis supports four phylogenetically and structurally distinct SUT subfamilies, originating from two ancient groups (AG1 and AG2 that diverged early during terrestrial colonization. In both AG1 and AG2, multiple intron acquisition events in the progenitor vascular plant established the gene structures of modern SUTs. Tonoplastic Type III and plasmalemmal Type II represent evolutionarily conserved descendants of AG1 and AG2, respectively. Type I and Type IIB were previously thought to evolve after the dicot-monocot split. We show, however, that divergence of Type I from Type III SUT predated basal angiosperms, likely associated with evolution of vascular cambium and phloem transport. Type I SUT was subsequently lost in monocots along with vascular cambium, and independent evolution of Type IIB coincided with modified monocot vasculature. Both Type I and Type IIB underwent lineage-specific expansion. In multiple unrelated taxa, the newly-derived SUTs exhibit biased expression in reproductive tissues, suggesting a functional link between phloem loading and reproductive fitness. Convergent evolution of Type I and Type IIB for SUT function in phloem loading and reproductive organs supports the idea that differential vascular development in dicots and monocots is a strong driver for SUT family evolution in angiosperms.
Vacik, Harald; Huber, Patrick; Hujala, Teppo; Kurtilla, Mikko; Wolfslehner, Bernhard
2015-04-01
It is an integral element of the European understanding of sustainable forest management to foster the design and marketing of forest products, non-wood forest products (NWFPs) and services that go beyond the production of timber. Despite the relevance of NWFPs in Europe, forest management and planning methods have been traditionally tailored towards wood and wood products, because most forest management models and silviculture techniques were developed to ensure a sustained production of timber. Although several approaches exist which explicitly consider NWFPs as management objectives in forest planning, specific models are needed for the assessment of their production potential in different environmental contexts and for different management regimes. Empirical data supporting a comprehensive assessment of the potential of NWFPs are rare, thus making development of statistical models particularly problematic. However, the complex causal relationships between the sustained production of NWFPs, the available ecological resources, as well as the organizational and the market potential of forest management regimes are well suited for knowledge-based expert models. Bayesian belief networks (BBNs) are a kind of probabilistic graphical model that have become very popular to practitioners and scientists mainly due to the powerful probability theory involved, which makes BBNs suitable to deal with a wide range of environmental problems. In this contribution we present the development of a Bayesian belief network to assess the potential of NWFPs for small scale forest owners. A three stage iterative process with stakeholder and expert participation was used to develop the Bayesian Network within the frame of the StarTree Project. The group of participants varied in the stages of the modelling process. A core team, consisting of one technical expert and two domain experts was responsible for the entire modelling process as well as for the first prototype of the network
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M. Bagnara
2014-10-01
Full Text Available Forest models are being increasingly used to study ecosystem functioning, through the reproduction of carbon fluxes and productivity in very different forests all over the world. Over the last two decades, the need for simple and "easy to use" models for practical applications, characterized by few parameters and equations, has become clear, and some have been developed for this purpose. These models aim to represent the main drivers underlying forest ecosystem processes while being applicable to the widest possible range of forest ecosystems. Recently, it has also become clear that model performance should not be assessed only in terms of accuracy of estimations and predictions, but also in terms of estimates of model uncertainties. Therefore, the Bayesian approach has increasingly been applied to calibrate forest models, with the aim of estimating the uncertainty of their results, and of comparing their performances. Some forest models, considered to be user-friendly, rely on a multiplicative or quasi-multiplicative mathematical structure, which is known to cause problems during the calibration process, mainly due to high correlations between parameters. In a Bayesian framework using a Markov Chain Monte Carlo sampling this is likely to impair the reaching of a proper convergence of the chains and the sampling from the correct posterior distribution. Here we show two methods to reach proper convergence when using a forest model with a multiplicative structure, applying different algorithms with different number of iterations during the Markov Chain Monte Carlo or a two-steps calibration. The results showed that recently proposed algorithms for adaptive calibration do not confer a clear advantage over the Metropolis–Hastings Random Walk algorithm for the forest model used here. Moreover, the calibration remains time consuming and mathematically difficult, so advantages of using a fast and user-friendly model can be lost due to the calibration
Dawson, Andria; Paciorek, Christopher J.; McLachlan, Jason S.; Goring, Simon; Williams, John W.; Jackson, Stephen T.
2016-04-01
Mitigation of climate change and adaptation to its effects relies partly on how effectively land-atmosphere interactions can be quantified. Quantifying composition of past forest ecosystems can help understand processes governing forest dynamics in a changing world. Fossil pollen data provide information about past forest composition, but rigorous interpretation requires development of pollen-vegetation models (PVMs) that account for interspecific differences in pollen production and dispersal. Widespread and intensified land-use over the 19th and 20th centuries may have altered pollen-vegetation relationships. Here we use STEPPS, a Bayesian hierarchical spatial PVM, to estimate key process parameters and associated uncertainties in the pollen-vegetation relationship. We apply alternate dispersal kernels, and calibrate STEPPS using a newly developed Euro-American settlement-era calibration data set constructed from Public Land Survey data and fossil pollen samples matched to the settlement-era using expert elicitation. Models based on the inverse power-law dispersal kernel outperformed those based on the Gaussian dispersal kernel, indicating that pollen dispersal kernels are fat tailed. Pine and birch have the highest pollen productivities. Pollen productivity and dispersal estimates are generally consistent with previous understanding from modern data sets, although source area estimates are larger. Tests of model predictions demonstrate the ability of STEPPS to predict regional compositional patterns.
Long, Siobhan
2003-01-01
On June 21, 2003, Raincoast Books released the Canadian edition of Harry Potter and the Order of the Phoenix, the fifth installment of the extremely popular series of novels by J.K. Rowling. Raincoast was the only one of fifty-five publishers of Harry Potter worldwide to print the book on 100-percent post-consumer recycled, ancient-forest-friendly paper. Raincoast decided to publicize its commitment to printing on ancient-forest-friendly paper by launching a media campaign on the subject just...
Technical Note: Approximate Bayesian parameterization of a complex tropical forest model
Hartig, F.; Dislich, C.; Wiegand, T.; Huth, A.
2013-08-01
Inverse parameter estimation of process-based models is a long-standing problem in ecology and evolution. A key problem of inverse parameter estimation is to define a metric that quantifies how well model predictions fit to the data. Such a metric can be expressed by general cost or objective functions, but statistical inversion approaches are based on a particular metric, the probability of observing the data given the model, known as the likelihood. Deriving likelihoods for dynamic models requires making assumptions about the probability for observations to deviate from mean model predictions. For technical reasons, these assumptions are usually derived without explicit consideration of the processes in the simulation. Only in recent years have new methods become available that allow generating likelihoods directly from stochastic simulations. Previous applications of these approximate Bayesian methods have concentrated on relatively simple models. Here, we report on the application of a simulation-based likelihood approximation for FORMIND, a parameter-rich individual-based model of tropical forest dynamics. We show that approximate Bayesian inference, based on a parametric likelihood approximation placed in a conventional MCMC, performs well in retrieving known parameter values from virtual field data generated by the forest model. We analyze the results of the parameter estimation, examine the sensitivity towards the choice and aggregation of model outputs and observed data (summary statistics), and show results from using this method to fit the FORMIND model to field data from an Ecuadorian tropical forest. Finally, we discuss differences of this approach to Approximate Bayesian Computing (ABC), another commonly used method to generate simulation-based likelihood approximations. Our results demonstrate that simulation-based inference, which offers considerable conceptual advantages over more traditional methods for inverse parameter estimation, can
Technical Note: Approximate Bayesian parameterization of a process-based tropical forest model
Hartig, F.; Dislich, C.; Wiegand, T.; Huth, A.
2014-02-01
Inverse parameter estimation of process-based models is a long-standing problem in many scientific disciplines. A key question for inverse parameter estimation is how to define the metric that quantifies how well model predictions fit to the data. This metric can be expressed by general cost or objective functions, but statistical inversion methods require a particular metric, the probability of observing the data given the model parameters, known as the likelihood. For technical and computational reasons, likelihoods for process-based stochastic models are usually based on general assumptions about variability in the observed data, and not on the stochasticity generated by the model. Only in recent years have new methods become available that allow the generation of likelihoods directly from stochastic simulations. Previous applications of these approximate Bayesian methods have concentrated on relatively simple models. Here, we report on the application of a simulation-based likelihood approximation for FORMIND, a parameter-rich individual-based model of tropical forest dynamics. We show that approximate Bayesian inference, based on a parametric likelihood approximation placed in a conventional Markov chain Monte Carlo (MCMC) sampler, performs well in retrieving known parameter values from virtual inventory data generated by the forest model. We analyze the results of the parameter estimation, examine its sensitivity to the choice and aggregation of model outputs and observed data (summary statistics), and demonstrate the application of this method by fitting the FORMIND model to field data from an Ecuadorian tropical forest. Finally, we discuss how this approach differs from approximate Bayesian computation (ABC), another method commonly used to generate simulation-based likelihood approximations. Our results demonstrate that simulation-based inference, which offers considerable conceptual advantages over more traditional methods for inverse parameter estimation
Technical Note: Approximate Bayesian parameterization of a complex tropical forest model
Directory of Open Access Journals (Sweden)
F. Hartig
2013-08-01
Full Text Available Inverse parameter estimation of process-based models is a long-standing problem in ecology and evolution. A key problem of inverse parameter estimation is to define a metric that quantifies how well model predictions fit to the data. Such a metric can be expressed by general cost or objective functions, but statistical inversion approaches are based on a particular metric, the probability of observing the data given the model, known as the likelihood. Deriving likelihoods for dynamic models requires making assumptions about the probability for observations to deviate from mean model predictions. For technical reasons, these assumptions are usually derived without explicit consideration of the processes in the simulation. Only in recent years have new methods become available that allow generating likelihoods directly from stochastic simulations. Previous applications of these approximate Bayesian methods have concentrated on relatively simple models. Here, we report on the application of a simulation-based likelihood approximation for FORMIND, a parameter-rich individual-based model of tropical forest dynamics. We show that approximate Bayesian inference, based on a parametric likelihood approximation placed in a conventional MCMC, performs well in retrieving known parameter values from virtual field data generated by the forest model. We analyze the results of the parameter estimation, examine the sensitivity towards the choice and aggregation of model outputs and observed data (summary statistics, and show results from using this method to fit the FORMIND model to field data from an Ecuadorian tropical forest. Finally, we discuss differences of this approach to Approximate Bayesian Computing (ABC, another commonly used method to generate simulation-based likelihood approximations. Our results demonstrate that simulation-based inference, which offers considerable conceptual advantages over more traditional methods for inverse parameter
Institute of Scientific and Technical Information of China (English)
DING Ping; SHEN ChengDe; WANG Ning; YI WeiXi; LIU KeXin; DING XingFang; FU DongPo
2009-01-01
We present the carbon isotopic composition of the total organic carbon (TOC) and fine roots in the sedimentary profile from the underground ancient forest in Sihui to study the climatic and environ-mental changes from 4.5 ka BP to 0.6 ka BP. Results show that C3 plant was the main vegetation from 4.5 ka BP to 0.6 ka BP in this region. The ancient forest began to develop in the wetland st around 4 ks BP and disappeared together with the wetland at about 3.0 ka BP, implying that the climate had changed greatly at around 3.0 ka BP. As indicated by the simulation results, the content of atmospheric CO2 increased slightly during 3.5 ka BP and 3.0 ka BP, implying climate warming during that period. The interval of radiocarbon age between 3.0 ka BP and 1.2 ka BP was possibly caused by the strong erosion when the block was lifted in the neotectonic movement. From 1.2 ks BP to 0.6 ka BP, the region re-mained in terrestrial sedimentary environment, and the surface plant biomass declined gradually. Drought caused by the climate change was the likely cause for the disappearance of the ancient forest. South transition of Intertropical Convergence Zone (ITCZ) was probably the main mechanism for the climate change.
Institute of Scientific and Technical Information of China (English)
无
2009-01-01
We present the carbon isotopic composition of the total organic carbon(TOC) and fine roots in the sedimentary profile from the underground ancient forest in Sihui to study the climatic and environmental changes from 4.5 ka BP to 0.6 ka BP.Results show that C3 plant was the main vegetation from 4.5 ka BP to 0.6 ka BP in this region.The ancient forest began to develop in the wetland at around 4 ka BP and disappeared together with the wetland at about 3.0 ka BP,implying that the climate had changed greatly at around 3.0 ka BP.As indicated by the simulation results,the content of atmospheric CO2 increased slightly during 3.5 ka BP and 3.0 ka BP,implying climate warming during that period.The interval of radiocarbon age between 3.0 ka BP and 1.2 ka BP was possibly caused by the strong erosion when the block was lifted in the neotectonic movement.From 1.2 ka BP to 0.6 ka BP,the region remained in terrestrial sedimentary environment,and the surface plant biomass declined gradually.Drought caused by the climate change was the likely cause for the disappearance of the ancient forest.South transition of Intertropical Convergence Zone(ITCZ) was probably the main mechanism for the climate change.
Pollination biology of the urban populations of an ancient forest, spring ephemeral plant
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Maciej A. Ziemiański
2016-04-01
Full Text Available Habitat fragmentation, caused by, among all, agriculture and urbanization, is one of the most important drivers of plant biodiversity decline worldwide. One of the signs of deteriorating zoogamous plant reproduction is pollen limitation, often associated with a decline in pollinator diversity and abundance. Various authors predict that the most vulnerable taxa are outbreeding plant species characterized by specialist pollination systems. We have, therefore, focused on self-incompatible Corydalis solida, an ancient forest, spring ephemeral plant, growing in three remnant urban populations in the city of Warsaw (Poland. Over two years, we checked for pollen limitation and recorded insect diversity and abundance for C. solida flowers. Our study populations composed of self-incompatible individuals were mainly visited by generalist pollinators, and produced more seeds when supplementally pollinated. Pollen limitation, however, was greater during 1 year with an early spring onset, when we observed a decline in floral visitors diversity and activity. This was probably an effect of phenological mismatch between plants and their pollinators, in this case, mostly social bees, i.e., over-wintered bumblebee queens and Apis mellifera. We conclude that for outbreeding zoogamous spring ephemerals, such as C. solida serviced by generalist pollinators, changing climatic conditions may override the effects of habitat fragmentation and influence their reproductive success.
Forests, fields, and the edge of sustainability at the ancient Maya city of Tikal.
Lentz, David L; Dunning, Nicholas P; Scarborough, Vernon L; Magee, Kevin S; Thompson, Kim M; Weaver, Eric; Carr, Christopher; Terry, Richard E; Islebe, Gerald; Tankersley, Kenneth B; Grazioso Sierra, Liwy; Jones, John G; Buttles, Palma; Valdez, Fred; Ramos Hernandez, Carmen E
2014-12-30
Tikal has long been viewed as one of the leading polities of the ancient Maya realm, yet how the city was able to maintain its substantial population in the midst of a tropical forest environment has been a topic of unresolved debate among researchers for decades. We present ecological, paleoethnobotanical, hydraulic, remote sensing, edaphic, and isotopic evidence that reveals how the Late Classic Maya at Tikal practiced intensive forms of agriculture (including irrigation, terrace construction, arboriculture, household gardens, and short fallow swidden) coupled with carefully controlled agroforestry and a complex system of water retention and redistribution. Empirical evidence is presented to demonstrate that this assiduously managed anthropogenic ecosystem of the Classic period Maya was a landscape optimized in a way that provided sustenance to a relatively large population in a preindustrial, low-density urban community. This landscape productivity optimization, however, came with a heavy cost of reduced environmental resiliency and a complete reliance on consistent annual rainfall. Recent speleothem data collected from regional caves showed that persistent episodes of unusually low rainfall were prevalent in the mid-9th century A.D., a time period that coincides strikingly with the abandonment of Tikal and the erection of its last dated monument in A.D. 869. The intensified resource management strategy used at Tikal-already operating at the landscape's carrying capacity-ceased to provide adequate food, fuel, and drinking water for the Late Classic populace in the face of extended periods of drought. As a result, social disorder and abandonment ensued.
Impact of ancient charcoal kilns on chemical properties of several forest soils after 2 centuries
Dufey, Joseph; Hardy, Brieuc; Cornelis, Jean-Thomas
2014-05-01
Pyrogenic carbon plays a major role in soil biogeochemical processes and carbon budgets. Until the early 19th century, charcoal was the unique combustible used for iron metallurgy in Wallonia (Belgium). Traditional charcoal kilns were built directly in the forest: wood logs were piled into a mound and isolated from air oxygen with a covering of vegetation residues and soil before setting fire, inducing wood pyrolysis. Nowadays, ancient wood-charring platforms are still easy to identify on the forest floor as heightened domes of 10 meters in diameter characterized by a very dark topsoil horizon containing charcoal dust and fragments. Our goal is to assess the effects of wood charring at mound kiln sites on the properties of various forest soil types in Wallonia (Belgium), after two centuries. We sampled soil by horizon in 18 ancient kiln sites to 1.20 meter depth. The adjacent charcoal-unaffected soils were sampled the same way. We also collected recent charcoal fragments and topsoil samples from a still active charcoal kiln located close to Dole (France) to apprehend the evolution of soil properties over time. The pH, total carbon (C) and nitrogen (N) content, available phosphorus (Pav), cation exchange capacity at pH 7 (CEC), exchangeable cations (Ca++, Mg++, K+, Na+) and loss on ignition at 550°C (LI550) were measured on each soil sample. We separated the soil profiles in 5 groups based on the nature of soil substrate and pedogenesis for interpretation of the results. We show that the total carbon stock is significantly increased at kiln sites due to higher C concentrations and greater depth of the organo-mineral horizon. The C/N ratio in charcoal-enriched soil horizons is significantly higher than in the neighboring reference soils but clearly attenuated compared to pure wood-charcoal fragments. The CEC is higher in the charcoal-enriched soil horizons, not only due to higher C concentrations but also to increased CEC by carbon unit at kiln sites. The high
Gonzalez-Redin, Julen; Luque, Sandra; Poggio, Laura; Smith, Ron; Gimona, Alessandro
2016-01-01
An integrated methodology, based on linking Bayesian belief networks (BBN) with GIS, is proposed for combining available evidence to help forest managers evaluate implications and trade-offs between forest production and conservation measures to preserve biodiversity in forested habitats. A Bayesian belief network is a probabilistic graphical model that represents variables and their dependencies through specifying probabilistic relationships. In spatially explicit decision problems where it is difficult to choose appropriate combinations of interventions, the proposed integration of a BBN with GIS helped to facilitate shared understanding of the human-landscape relationships, while fostering collective management that can be incorporated into landscape planning processes. Trades-offs become more and more relevant in these landscape contexts where the participation of many and varied stakeholder groups is indispensable. With these challenges in mind, our integrated approach incorporates GIS-based data with expert knowledge to consider two different land use interests - biodiversity value for conservation and timber production potential - with the focus on a complex mountain landscape in the French Alps. The spatial models produced provided different alternatives of suitable sites that can be used by policy makers in order to support conservation priorities while addressing management options. The approach provided provide a common reasoning language among different experts from different backgrounds while helped to identify spatially explicit conflictive areas. PMID:26597639
Forests, fields, and the edge of sustainability at the ancient Maya city of Tikal
Lentz, David L.; Dunning, Nicholas P.; Scarborough, Vernon L.; Magee, Kevin S.; Thompson, Kim M.; Weaver, Eric; Terry, Richard E.; Islebe, Gerald; Tankersley, Kenneth B.; Grazioso Sierra, Liwy; Jones, John G.; Buttles, Palma; Valdez, Fred; Ramos Hernandez, Carmen E.
2014-01-01
Tikal has long been viewed as one of the leading polities of the ancient Maya realm, yet how the city was able to maintain its substantial population in the midst of a tropical forest environment has been a topic of unresolved debate among researchers for decades. We present ecological, paleoethnobotanical, hydraulic, remote sensing, edaphic, and isotopic evidence that reveals how the Late Classic Maya at Tikal practiced intensive forms of agriculture (including irrigation, terrace construction, arboriculture, household gardens, and short fallow swidden) coupled with carefully controlled agroforestry and a complex system of water retention and redistribution. Empirical evidence is presented to demonstrate that this assiduously managed anthropogenic ecosystem of the Classic period Maya was a landscape optimized in a way that provided sustenance to a relatively large population in a preindustrial, low-density urban community. This landscape productivity optimization, however, came with a heavy cost of reduced environmental resiliency and a complete reliance on consistent annual rainfall. Recent speleothem data collected from regional caves showed that persistent episodes of unusually low rainfall were prevalent in the mid-9th century A.D., a time period that coincides strikingly with the abandonment of Tikal and the erection of its last dated monument in A.D. 869. The intensified resource management strategy used at Tikal—already operating at the landscape’s carrying capacity—ceased to provide adequate food, fuel, and drinking water for the Late Classic populace in the face of extended periods of drought. As a result, social disorder and abandonment ensued. PMID:25512500
Linden, Daniel W; Roloff, Gary J
2015-08-01
Pilot studies are often used to design short-term research projects and long-term ecological monitoring programs, but data are sometimes discarded when they do not match the eventual survey design. Bayesian hierarchical modeling provides a convenient framework for integrating multiple data sources while explicitly separating sample variation into observation and ecological state processes. Such an approach can better estimate state uncertainty and improve inferences from short-term studies in dynamic systems. We used a dynamic multistate occupancy model to estimate the probabilities of occurrence and nesting for white-headed woodpeckers Picoides albolarvatus in recent harvest units within managed forests of northern California, USA. Our objectives were to examine how occupancy states and state transitions were related to forest management practices, and how the probabilities changed over time. Using Gibbs variable selection, we made inferences using multiple model structures and generated model-averaged estimates. Probabilities of white-headed woodpecker occurrence and nesting were high in 2009 and 2010, and the probability that nesting persisted at a site was positively related to the snag density in harvest units. Prior-year nesting resulted in higher probabilities of subsequent occurrence and nesting. We demonstrate the benefit of forest management practices that increase the density of retained snags in harvest units for providing white-headed woodpecker nesting habitat. While including an additional year of data from our pilot study did not drastically alter management recommendations, it changed the interpretation of the mechanism behind the observed dynamics. Bayesian hierarchical modeling has the potential to maximize the utility of studies based on small sample sizes while fully accounting for measurement error and both estimation and model uncertainty, thereby improving the ability of observational data to inform conservation and management strategies
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Dirk W. te Velde
2006-12-01
Full Text Available Commercialization of non-timber forest products (NTFPs has been widely promoted as a means of sustainably developing tropical forest resources, in a way that promotes forest conservation while supporting rural livelihoods. However, in practice, NTFP commercialization has often failed to deliver the expected benefits. Progress in analyzing the causes of such failure has been hindered by the lack of a suitable framework for the analysis of NTFP case studies, and by the lack of predictive theory. We address these needs by developing a probabilistic model based on a livelihood framework, enabling the impact of NTFP commercialization on livelihoods to be predicted. The framework considers five types of capital asset needed to support livelihoods: natural, human, social, physical, and financial. Commercialization of NTFPs is represented in the model as the conversion of one form of capital asset into another, which is influenced by a variety of socio-economic, environmental, and political factors. Impacts on livelihoods are determined by the availability of the five types of assets following commercialization. The model, implemented as a Bayesian Belief Network, was tested using data from participatory research into 19 NTFP case studies undertaken in Mexico and Bolivia. The model provides a novel tool for diagnosing the causes of success and failure in NTFP commercialization, and can be used to explore the potential impacts of policy options and other interventions on livelihoods. The potential value of this approach for the development of NTFP theory is discussed.
Forests, fields, and the edge of sustainability at the ancient Maya city of Tikal
Lentz, David L.; Dunning, Nicholas P.; Scarborough, Vernon L.; Magee, Kevin S.; Thompson, Kim M.; Weaver, Eric; Carr, Christopher; Terry, Richard E.; Islebe, Gerald; Tankersley, Kenneth B.; Grazioso Sierra, Liwy; Jones, John G.; Buttles, Palma; Valdez, Fred; Ramos Hernandez, Carmen E.
2014-01-01
The rise of complex societies and sustainable land use associated with urban centers has been a major focus for anthropologists, geographers, and ecologists. Here we present a quantitative assessment of the agricultural, agroforestry, and water management strategies of the inhabitants of the prominent ancient Maya city of Tikal, and how their land use practices effectively sustained a low-density urban population for many centuries. Our findings also reveal, however, that the productive lands...
Mark H. Huff; Turley, Marianne C.; Randy Molina; Russ Holmes; Steve Morey; Hohenlohe, Paul A.; Bruce G. Marcot; John A. Laurence
2006-01-01
We developed a set of decision-aiding models as Bayesian belief networks (BBNs) that represented a complex set of evaluation guidelines used to determine the appropriate conservation of hundreds of potentially rare species on federally-administered lands in the Pacific Northwest United States. The models were used in a structured assessment and paneling procedure as part of an adaptive management process that evaluated new scientific information under the Northwest Forest Plan. The models wer...
Bryson, Robert W; Savary, Warren E; Zellmer, Amanda J; Bury, R Bruce; McCormack, John E
2016-08-01
The California Floristic Province (CFP) in western North America is a globally significant biodiversity hotspot. Elucidating patterns of endemism and the historical drivers of this diversity has been an important challenge of comparative phylogeography for over two decades. We generated phylogenomic data using ddRADseq to examine genetic structure in Uroctonus forest scorpions, an ecologically restricted and dispersal-limited organism widely distributed across the CFP north to the Columbia River. We coupled our genetic data with species distribution models (SDMs) to determine climatically suitable areas for Uroctonus both now and during the Last Glacial Maximum. Based on our analyses, Uroctonus is composed of two major genetic groups that likely diverged over 2 million years ago. Each of these groups itself contains numerous genetic groups that reveal a pattern of vicariance and microendemism across the CFP. Migration rates among these populations are low. SDMs suggest forest scorpion habitat has remained relatively stable over the last 21 000 years, consistent with the genetic data. Our results suggest tectonic plate rafting, mountain uplift, river drainage formation and climate-induced habitat fragmentation have all likely played a role in the diversification of Uroctonus. The intricate pattern of genetic fragmentation revealed across a temporal continuum highlights the potential of low-dispersing species to shed light on small-scale patterns of biodiversity and the underlying processes that have generated this diversity in biodiversity hotspots. PMID:27238387
Insect leaf-chewing damage tracks herbivore richness in modern and ancient forests.
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Mónica R Carvalho
Full Text Available The fossil record demonstrates that past climate changes and extinctions significantly affected the diversity of insect leaf-feeding damage, implying that the richness of damage types reflects that of the unsampled damage makers, and that the two are correlated through time. However, this relationship has not been quantified for living leaf-chewing insects, whose richness and mouthpart convergence have obscured their value for understanding past and present herbivore diversity. We hypothesized that the correlation of leaf-chewing damage types (DTs and damage maker richness is directly observable in living forests. Using canopy access cranes at two lowland tropical rainforest sites in Panamá to survey 24 host-plant species, we found significant correlations between the numbers of leaf chewing insect species collected and the numbers of DTs observed to be made by the same species in feeding experiments, strongly supporting our hypothesis. Damage type richness was largely driven by insect species that make multiple DTs. Also, the rank-order abundances of DTs recorded at the Panamá sites and across a set of latest Cretaceous to middle Eocene fossil floras were highly correlated, indicating remarkable consistency of feeding-mode distributions through time. Most fossil and modern host-plant pairs displayed high similarity indices for their leaf-chewing DTs, but informative differences and trends in fossil damage composition became apparent when endophytic damage was included. Our results greatly expand the potential of insect-mediated leaf damage for interpreting insect herbivore richness and compositional heterogeneity from fossil floras and, equally promisingly, in living forests.
Finley, A. O.; Banerjee, S.; Cook, B. D.
2010-12-01
Recent advances in remote sensing, specifically waveform Light Detection and Ranging (LiDAR) sensors, provide the data needed to quantify forest variables at a fine spatial resolution over large domains. Of particular interest is LiDAR data from NASA's Laser Vegetation Imaging Sensor (LVIS), upcoming Deformation, Ecosystem Structure, and Dynamics of Ice (DESDynI) missions, and NSF's National Ecological Observatory Network planned Airborne Observation Platform. A central challenge to using these data is to couple field measurements of forest variables (e.g., species, indices of structural complexity, light competition, or drought stress) with the high-dimensional LiDAR signal through a model, which allows prediction of the tree-level variables at locations where only the remotely sensed data area are available. It is common to model the high-dimensional signal vector as a mixture of a relatively small number of Gaussian distributions. The parameters from these Gaussian distributions, or indices derived from the parameters, can then be used as regressors in a regression model. These approaches retain only a small amount of information contained in the signal. Further, it is not known a priori which features of the signal explain the most variability in the response variables. It is possible to fully exploit the information in the signal by treating it as an object, thus, we define a framework to couple a spatial latent factor model with forest variables using a fully Bayesian functional spatial data analysis. Our proposed modeling framework explicitly: 1) reduces the dimensionality of signals in an optimal way (i.e., preserves the information that describes the maximum variability in response variable); 2) propagates uncertainty in data and parameters through to prediction, and; 3) acknowledges and leverages spatial dependence among the regressors and model residuals to meet statistical assumptions and improve prediction. The proposed modeling framework is
Finley, Andrew O.; Banerjee, Sudipto; Cook, Bruce D.; Bradford, John B.
2013-01-01
In this paper we detail a multivariate spatial regression model that couples LiDAR, hyperspectral and forest inventory data to predict forest outcome variables at a high spatial resolution. The proposed model is used to analyze forest inventory data collected on the US Forest Service Penobscot Experimental Forest (PEF), ME, USA. In addition to helping meet the regression model's assumptions, results from the PEF analysis suggest that the addition of multivariate spatial random effects improves model fit and predictive ability, compared with two commonly applied modeling approaches. This improvement results from explicitly modeling the covariation among forest outcome variables and spatial dependence among observations through the random effects. Direct application of such multivariate models to even moderately large datasets is often computationally infeasible because of cubic order matrix algorithms involved in estimation. We apply a spatial dimension reduction technique to help overcome this computational hurdle without sacrificing richness in modeling.
Spake, Rebecca; van der Linde, Sietse; Newton, Adrian C.; Suz, Laura M.; Bidartondo, Martin I.; Doncaster, C. Patrick
2016-01-01
Setting aside overmature planted forests is currently seen as an option for preserving species associated with old-growth forests, such as those with dispersal limitation. Few data exist, however, on the utility of set-aside plantations for this purpose, or the value of this habitat type for biodiversity relative to old-growth semi-natural ecosystems. Here, we evaluate the contribution of forest type relative to habitat characteristics in determining species richness and composition in seven ...
Directory of Open Access Journals (Sweden)
Mark H. Huff
2006-12-01
Full Text Available We developed a set of decision-aiding models as Bayesian belief networks (BBNs that represented a complex set of evaluation guidelines used to determine the appropriate conservation of hundreds of potentially rare species on federally-administered lands in the Pacific Northwest United States. The models were used in a structured assessment and paneling procedure as part of an adaptive management process that evaluated new scientific information under the Northwest Forest Plan. The models were not prescriptive but helped resource managers and specialists to evaluate complicated and at times conflicting conservation guidelines and to reduce bias and uncertainty in evaluating the scientific data. We concluded that applying the BBN modeling framework to complex and equivocal evaluation guidelines provided a set of clear, intuitive decision-aiding tools that greatly aided the species evaluation and conservation process.
DEFF Research Database (Denmark)
Willerslev, Eske; Cooper, Alan
2004-01-01
ancient DNA, palaeontology, palaeoecology, archaeology, population genetics, DNA damage and repair......ancient DNA, palaeontology, palaeoecology, archaeology, population genetics, DNA damage and repair...
Ancient deforestation revisited.
Hughes, J Donald
2011-01-01
The image of the classical Mediterranean environment of the Greeks and Romans had a formative influence on the art, literature, and historical perception of modern Europe and America. How closely does is this image congruent with the ancient environment as it in reality existed? In particular, how forested was the ancient Mediterranean world, was there deforestation, and if so, what were its effects? The consensus of historians, geographers, and other scholars from the mid-nineteenth century through the first three quarters of the twentieth century was that human activities had depleted the forests to a major extent and caused severe erosion. My research confirmed this general picture. Since then, revisionist historians have questioned these conclusions, maintaining instead that little environmental damage was done to forests and soils in ancient Greco-Roman times. In a reconsideration of the question, this paper looks at recent scientific work providing proxy evidence for the condition of forests at various times in ancient history. I look at three scientific methodologies, namely anthracology, palynology, and computer modeling. Each of these avenues of research offers support for the concept of forest change, both in abundance and species composition, and episodes of deforestation and erosion, and confirms my earlier work.
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
Evers, Virginia
This four-week fourth grade social studies unit dealing with religious dimensions in ancient Egyptian culture was developed by the Public Education Religion Studies Center at Wright State University. It seeks to help students understand ancient Egypt by looking at the people, the culture, and the people's world view. The unit begins with outlines…
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
DEFF Research Database (Denmark)
Der Sarkissian, Clio; Allentoft, Morten Erik; Avila Arcos, Maria del Carmen;
2015-01-01
, archaic hominins, ancient pathogens and megafaunal species. Those have revealed important functional and phenotypic information, as well as unexpected adaptation, migration and admixture patterns. As such, the field of aDNA has entered the new era of genomics and has provided valuable information when...
DEFF Research Database (Denmark)
Ho, Simon Y W; Gilbert, M Thomas P
2010-01-01
the technical challenges that face researchers in the field. We catalogue the diverse sequencing methods and source materials used to obtain ancient mitogenomic sequences, summarise the associated genetic and phylogenetic studies that have been conducted, and evaluate the future prospects of the field....
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
Swamy, Ashwin Balegar
This thesis involves development of an interactive GIS (Geographic Information System) based application, which gives information about the ancient history of Egypt. The astonishing architecture, the strange burial rituals and their civilization were some of the intriguing questions that motivated me towards developing this application. The application is a historical timeline starting from 3100 BC, leading up to 664 BC, focusing on the evolution of the Egyptian dynasties. The tool holds information regarding some of the famous monuments which were constructed during that era and also about the civilizations that co-existed. It also provides details about the religions followed by their kings. It also includes the languages spoken during those periods. The tool is developed using JAVA, a programing language and MOJO (Map Objects Java Objects) a product of ESRI (Environmental Science Research Institute) to create map objects, to provide geographic information. JAVA Swing is used for designing the user interface. HTML (Hyper Text Markup Language) pages are created to provide the user with more information related to the historic period. CSS (Cascade Style Sheets) and JAVA Scripts are used with HTML5 to achieve creative display of content. The tool is kept simple and easy for the user to interact with. The tool also includes pictures and videos for the user to get a feel of the historic period. The application is built to motivate people to know more about one of the prominent and ancient civilization of the Mediterranean world.
Introduction to Bayesian statistics
Bolstad, William M
2016-01-01
There is a strong upsurge in the use of Bayesian methods in applied statistical analysis, yet most introductory statistics texts only present frequentist methods. Bayesian statistics has many important advantages that students should learn about if they are going into fields where statistics will be used. In this Third Edition, four newly-added chapters address topics that reflect the rapid advances in the field of Bayesian staistics. The author continues to provide a Bayesian treatment of introductory statistical topics, such as scientific data gathering, discrete random variables, robust Bayesian methods, and Bayesian approaches to inferenfe cfor discrete random variables, bionomial proprotion, Poisson, normal mean, and simple linear regression. In addition, newly-developing topics in the field are presented in four new chapters: Bayesian inference with unknown mean and variance; Bayesian inference for Multivariate Normal mean vector; Bayesian inference for Multiple Linear RegressionModel; and Computati...
Bayesian artificial intelligence
Korb, Kevin B
2003-01-01
As the power of Bayesian techniques has become more fully realized, the field of artificial intelligence has embraced Bayesian methodology and integrated it to the point where an introduction to Bayesian techniques is now a core course in many computer science programs. Unlike other books on the subject, Bayesian Artificial Intelligence keeps mathematical detail to a minimum and covers a broad range of topics. The authors integrate all of Bayesian net technology and learning Bayesian net technology and apply them both to knowledge engineering. They emphasize understanding and intuition but also provide the algorithms and technical background needed for applications. Software, exercises, and solutions are available on the authors' website.
Bayesian artificial intelligence
Korb, Kevin B
2010-01-01
Updated and expanded, Bayesian Artificial Intelligence, Second Edition provides a practical and accessible introduction to the main concepts, foundation, and applications of Bayesian networks. It focuses on both the causal discovery of networks and Bayesian inference procedures. Adopting a causal interpretation of Bayesian networks, the authors discuss the use of Bayesian networks for causal modeling. They also draw on their own applied research to illustrate various applications of the technology.New to the Second EditionNew chapter on Bayesian network classifiersNew section on object-oriente
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.
DEFF Research Database (Denmark)
Jensen, Finn Verner; Nielsen, Thomas Dyhre
2016-01-01
Mathematically, a Bayesian graphical model is a compact representation of the joint probability distribution for a set of variables. The most frequently used type of Bayesian graphical models are Bayesian networks. The structural part of a Bayesian graphical model is a graph consisting of nodes...... and edges. The nodes represent variables, which may be either discrete or continuous. An edge between two nodes A and B indicates a direct influence between the state of A and the state of B, which in some domains can also be interpreted as a causal relation. The wide-spread use of Bayesian networks...... is largely due to the availability of efficient inference algorithms for answering probabilistic queries about the states of the variables in the network. Furthermore, to support the construction of Bayesian network models, learning algorithms are also available. We give an overview of the Bayesian network...
Phytolith assemblages along a gradient of ancient human disturbance in western Amazonia
Directory of Open Access Journals (Sweden)
Crystal eMcmichael
2015-12-01
Full Text Available The ecological status of prehistoric Amazonian forests remains widely debated. The concept of ancient Amazonia as a pristine wilderness is largely discredited, but the alternative hypothesis of extensive anthropogenic landscape remains untested in many regions. We assessed the degree of ancient human impacts across western Amazonia based on archaeological and paleoecological data using methodologies that would allow inter-regional comparisons. We also aimed to establish baselines for estimating the legacies of ancient disturbances on modern vegetation. We analyzed charcoal and phytolith assemblages from soil samples from an archaeological site, sites in close proximity to archaeological sites, sites from riverine and interfluvial forests, and a biological research station believed to contain some of the least disturbed forests within Amazonia. We then quantitatively compared phytolith assemblages within and between the surveyed regions. Palm enrichment was evident at the archaeological site, and the biological station survey contained little to no evidence of ancient human activity. The other sites exhibited a gradient of ancient disturbance across the landscape. The phytolith assemblages showed statistically significant between-region variations that indicated our metrics were sufficiently sensitive to detecting ancient disturbance. Our data highlight the spatial heterogeneity of ancient human disturbances in Amazonian forests. The quantification of these disturbances provides empirical data and a more concrete link between the composition of the modern forest and ancient disturbance regimes. Accounting for ancient disturbances will allow a deeper understanding of the landscape heterogeneity observed in the modern forests.
Apps for Ancient Civilizations
Thompson, Stephanie
2011-01-01
This project incorporates technology and a historical emphasis on science drawn from ancient civilizations to promote a greater understanding of conceptual science. In the Apps for Ancient Civilizations project, students investigate an ancient culture to discover how people might have used science and math smartphone apps to make their lives…
Understanding Computational Bayesian Statistics
Bolstad, William M
2011-01-01
A hands-on introduction to computational statistics from a Bayesian point of view Providing a solid grounding in statistics while uniquely covering the topics from a Bayesian perspective, Understanding Computational Bayesian Statistics successfully guides readers through this new, cutting-edge approach. With its hands-on treatment of the topic, the book shows how samples can be drawn from the posterior distribution when the formula giving its shape is all that is known, and how Bayesian inferences can be based on these samples from the posterior. These ideas are illustrated on common statistic
Bayesian statistics an introduction
Lee, Peter M
2012-01-01
Bayesian Statistics is the school of thought that combines prior beliefs with the likelihood of a hypothesis to arrive at posterior beliefs. The first edition of Peter Lee’s book appeared in 1989, but the subject has moved ever onwards, with increasing emphasis on Monte Carlo based techniques. This new fourth edition looks at recent techniques such as variational methods, Bayesian importance sampling, approximate Bayesian computation and Reversible Jump Markov Chain Monte Carlo (RJMCMC), providing a concise account of the way in which the Bayesian approach to statistics develops as wel
Frühwirth-Schnatter, Sylvia
1990-01-01
In the paper at hand we apply it to Bayesian statistics to obtain "Fuzzy Bayesian Inference". In the subsequent sections we will discuss a fuzzy valued likelihood function, Bayes' theorem for both fuzzy data and fuzzy priors, a fuzzy Bayes' estimator, fuzzy predictive densities and distributions, and fuzzy H.P.D .-Regions. (author's abstract)
Yuan, Ying; MacKinnon, David P.
2009-01-01
In this article, we propose Bayesian analysis of mediation effects. Compared with conventional frequentist mediation analysis, the Bayesian approach has several advantages. First, it allows researchers to incorporate prior information into the mediation analysis, thus potentially improving the efficiency of estimates. Second, under the Bayesian…
von der Linden, Wolfgang; Dose, Volker; von Toussaint, Udo
2014-06-01
Preface; Part I. Introduction: 1. The meaning of probability; 2. Basic definitions; 3. Bayesian inference; 4. Combinatrics; 5. Random walks; 6. Limit theorems; 7. Continuous distributions; 8. The central limit theorem; 9. Poisson processes and waiting times; Part II. Assigning Probabilities: 10. Transformation invariance; 11. Maximum entropy; 12. Qualified maximum entropy; 13. Global smoothness; Part III. Parameter Estimation: 14. Bayesian parameter estimation; 15. Frequentist parameter estimation; 16. The Cramer-Rao inequality; Part IV. Testing Hypotheses: 17. The Bayesian way; 18. The frequentist way; 19. Sampling distributions; 20. Bayesian vs frequentist hypothesis tests; Part V. Real World Applications: 21. Regression; 22. Inconsistent data; 23. Unrecognized signal contributions; 24. Change point problems; 25. Function estimation; 26. Integral equations; 27. Model selection; 28. Bayesian experimental design; Part VI. Probabilistic Numerical Techniques: 29. Numerical integration; 30. Monte Carlo methods; 31. Nested sampling; Appendixes; References; Index.
Discovering the Ancient Maya from Space
Sever, T. L.
2008-01-01
The Pet6n region of northern Guatemala contains some of the most significant Mayan archeological sites in Latin America. It was in this region that the Maya civilization began, flourished, and abruptly disappeared. Remote sensing technology is helping to locate and map ancient Maya sites that are threatened today by accelerating deforestation and looting. Thematic Mapper, IKONOS, and QuickBird satellite, and airborne STAR-3i and AIRSAR radar data, combined with Global Positioning System (GPS) technology, are successfully detecting ancient Maya features such as sites, roadways, canals, and water reservoirs. Satellite imagery is also being used to map the bajos, which are seasonally flooded swamps that cover over 40% of the land surface. Through the use of various airborne and satellite sensor systems we have been able to detect and map ancient causeways, temples, reservoirs, and land forms, and locate these features on the ground through GPS technology. Recently, we have discovered that there is a strong relationship between a tropical forest vegetation signature in satellite imagery and the location of archeological sites. We believe that the use of limestone and lime plasters in ancient Maya construction affects the moisture, nutrition, and plant species of the surface vegetation. We have mapped these vegetation signatures in the imagery and verified through field survey that they are indicative of archeological sites. Through the use of remote sensing and GIS technology it is possible to identify unrecorded archeological features in a dense tropical forest environment and monitor these cultural features for their protection.
Barrow, Robin
1982-01-01
Defends the value and relevance of the study of ancient history and classics in history curricula. The unique homogeneity of the classical period contributes to its instructional manageability. A year-long, secondary-level course on fifth-century Greece and Rome is described to illustrate effective approaches to teaching ancient history. (AM)
Granade, Christopher; Cory, D G
2015-01-01
In recent years, Bayesian methods have been proposed as a solution to a wide range of issues in quantum state and process tomography. State-of- the-art Bayesian tomography solutions suffer from three problems: numerical intractability, a lack of informative prior distributions, and an inability to track time-dependent processes. Here, we solve all three problems. First, we use modern statistical methods, as pioneered by Husz\\'ar and Houlsby and by Ferrie, to make Bayesian tomography numerically tractable. Our approach allows for practical computation of Bayesian point and region estimators for quantum states and channels. Second, we propose the first informative priors on quantum states and channels. Finally, we develop a method that allows online tracking of time-dependent states and estimates the drift and diffusion processes affecting a state. We provide source code and animated visual examples for our methods.
Noncausal Bayesian Vector Autoregression
DEFF Research Database (Denmark)
Lanne, Markku; Luoto, Jani
We propose a Bayesian inferential procedure for the noncausal vector autoregressive (VAR) model that is capable of capturing nonlinearities and incorporating effects of missing variables. In particular, we devise a fast and reliable posterior simulator that yields the predictive distribution...
Bayesian Lensing Shear Measurement
Bernstein, Gary M
2013-01-01
We derive an estimator of weak gravitational lensing shear from background galaxy images that avoids noise-induced biases through a rigorous Bayesian treatment of the measurement. The Bayesian formalism requires a prior describing the (noiseless) distribution of the target galaxy population over some parameter space; this prior can be constructed from low-noise images of a subsample of the target population, attainable from long integrations of a fraction of the survey field. We find two ways to combine this exact treatment of noise with rigorous treatment of the effects of the instrumental point-spread function and sampling. The Bayesian model fitting (BMF) method assigns a likelihood of the pixel data to galaxy models (e.g. Sersic ellipses), and requires the unlensed distribution of galaxies over the model parameters as a prior. The Bayesian Fourier domain (BFD) method compresses galaxies to a small set of weighted moments calculated after PSF correction in Fourier space. It requires the unlensed distributi...
Ancient and modern environmental DNA
DEFF Research Database (Denmark)
Pedersen, Mikkel Winther; Overballe-Petersen, Søren; Ermini, Luca;
2015-01-01
DNA obtained from environmental samples such as sediments, ice or water (environmental DNA, eDNA), represents an important source of information on past and present biodiversity. It has revealed an ancient forest in Greenland, extended by several thousand years the survival dates for mainland...... woolly mammoth in Alaska, and pushed back the dates for spruce survival in Scandinavian ice-free refugia during the last glaciation. More recently, eDNA was used to uncover the past 50 000 years of vegetation history in the Arctic, revealing massive vegetation turnover at the Pleistocene...... knowledge of biogeography. However, the approach remains marred by biases related to DNA behaviour in environmental settings, incomplete reference databases and false positive results due to contamination. We provide a review of the field....
Malicious Bayesian Congestion Games
Gairing, Martin
2008-01-01
In this paper, we introduce malicious Bayesian congestion games as an extension to congestion games where players might act in a malicious way. In such a game each player has two types. Either the player is a rational player seeking to minimize her own delay, or - with a certain probability - the player is malicious in which case her only goal is to disturb the other players as much as possible. We show that such games do in general not possess a Bayesian Nash equilibrium in pure strategies (i.e. a pure Bayesian Nash equilibrium). Moreover, given a game, we show that it is NP-complete to decide whether it admits a pure Bayesian Nash equilibrium. This result even holds when resource latency functions are linear, each player is malicious with the same probability, and all strategy sets consist of singleton sets. For a slightly more restricted class of malicious Bayesian congestion games, we provide easy checkable properties that are necessary and sufficient for the existence of a pure Bayesian Nash equilibrium....
Esotericism Ancient and Modern
Frazer, Michael
2006-01-01
Leo Strauss presents at least two distinct accounts of the idea that the authors in the political-philosophical canon have often masked their true teachings. A weaker account of esotericism, dependent on the contingent fact of persecution, is attributed to the moderns, while a stronger account, stemming from a necessary conflict between philosophy and society, is attributed to the ancients. Although most interpreters agree that Strauss here sides with the ancients, this view fails to consider...
Bayesian least squares deconvolution
Ramos, A Asensio
2015-01-01
Aims. To develop a fully Bayesian least squares deconvolution (LSD) that can be applied to the reliable detection of magnetic signals in noise-limited stellar spectropolarimetric observations using multiline techniques. Methods. We consider LSD under the Bayesian framework and we introduce a flexible Gaussian Process (GP) prior for the LSD profile. This prior allows the result to automatically adapt to the presence of signal. We exploit several linear algebra identities to accelerate the calculations. The final algorithm can deal with thousands of spectral lines in a few seconds. Results. We demonstrate the reliability of the method with synthetic experiments and we apply it to real spectropolarimetric observations of magnetic stars. We are able to recover the magnetic signals using a small number of spectral lines, together with the uncertainty at each velocity bin. This allows the user to consider if the detected signal is reliable. The code to compute the Bayesian LSD profile is freely available.
Bayesian least squares deconvolution
Asensio Ramos, A.; Petit, P.
2015-11-01
Aims: We develop a fully Bayesian least squares deconvolution (LSD) that can be applied to the reliable detection of magnetic signals in noise-limited stellar spectropolarimetric observations using multiline techniques. Methods: We consider LSD under the Bayesian framework and we introduce a flexible Gaussian process (GP) prior for the LSD profile. This prior allows the result to automatically adapt to the presence of signal. We exploit several linear algebra identities to accelerate the calculations. The final algorithm can deal with thousands of spectral lines in a few seconds. Results: We demonstrate the reliability of the method with synthetic experiments and we apply it to real spectropolarimetric observations of magnetic stars. We are able to recover the magnetic signals using a small number of spectral lines, together with the uncertainty at each velocity bin. This allows the user to consider if the detected signal is reliable. The code to compute the Bayesian LSD profile is freely available.
Hybrid Batch Bayesian Optimization
Azimi, Javad; Fern, Xiaoli
2012-01-01
Bayesian Optimization aims at optimizing an unknown non-convex/concave function that is costly to evaluate. We are interested in application scenarios where concurrent function evaluations are possible. Under such a setting, BO could choose to either sequentially evaluate the function, one input at a time and wait for the output of the function before making the next selection, or evaluate the function at a batch of multiple inputs at once. These two different settings are commonly referred to as the sequential and batch settings of Bayesian Optimization. In general, the sequential setting leads to better optimization performance as each function evaluation is selected with more information, whereas the batch setting has an advantage in terms of the total experimental time (the number of iterations). In this work, our goal is to combine the strength of both settings. Specifically, we systematically analyze Bayesian optimization using Gaussian process as the posterior estimator and provide a hybrid algorithm t...
Loredo, T J
2004-01-01
I describe a framework for adaptive scientific exploration based on iterating an Observation--Inference--Design cycle that allows adjustment of hypotheses and observing protocols in response to the results of observation on-the-fly, as data are gathered. The framework uses a unified Bayesian methodology for the inference and design stages: Bayesian inference to quantify what we have learned from the available data and predict future data, and Bayesian decision theory to identify which new observations would teach us the most. When the goal of the experiment is simply to make inferences, the framework identifies a computationally efficient iterative ``maximum entropy sampling'' strategy as the optimal strategy in settings where the noise statistics are independent of signal properties. Results of applying the method to two ``toy'' problems with simulated data--measuring the orbit of an extrasolar planet, and locating a hidden one-dimensional object--show the approach can significantly improve observational eff...
Bayesian Exploratory Factor Analysis
DEFF Research Database (Denmark)
Conti, Gabriella; Frühwirth-Schnatter, Sylvia; Heckman, James J.;
2014-01-01
This paper develops and applies a Bayesian approach to Exploratory Factor Analysis that improves on ad hoc classical approaches. Our framework relies on dedicated factor models and simultaneously determines the number of factors, the allocation of each measurement to a unique factor, and the corr......This paper develops and applies a Bayesian approach to Exploratory Factor Analysis that improves on ad hoc classical approaches. Our framework relies on dedicated factor models and simultaneously determines the number of factors, the allocation of each measurement to a unique factor......, and the corresponding factor loadings. Classical identification criteria are applied and integrated into our Bayesian procedure to generate models that are stable and clearly interpretable. A Monte Carlo study confirms the validity of the approach. The method is used to produce interpretable low dimensional aggregates...
Bayesian multiple target tracking
Streit, Roy L
2013-01-01
This second edition has undergone substantial revision from the 1999 first edition, recognizing that a lot has changed in the multiple target tracking field. One of the most dramatic changes is in the widespread use of particle filters to implement nonlinear, non-Gaussian Bayesian trackers. This book views multiple target tracking as a Bayesian inference problem. Within this framework it develops the theory of single target tracking, multiple target tracking, and likelihood ratio detection and tracking. In addition to providing a detailed description of a basic particle filter that implements
Bayesian and frequentist inequality tests
David M. Kaplan; Zhuo, Longhao
2016-01-01
Bayesian and frequentist criteria are fundamentally different, but often posterior and sampling distributions are asymptotically equivalent (and normal). We compare Bayesian and frequentist hypothesis tests of inequality restrictions in such cases. For finite-dimensional parameters, if the null hypothesis is that the parameter vector lies in a certain half-space, then the Bayesian test has (frequentist) size $\\alpha$; if the null hypothesis is any other convex subspace, then the Bayesian test...
A. Korattikara; V. Rathod; K. Murphy; M. Welling
2015-01-01
We consider the problem of Bayesian parameter estimation for deep neural networks, which is important in problem settings where we may have little data, and/ or where we need accurate posterior predictive densities p(y|x, D), e.g., for applications involving bandits or active learning. One simple ap
Bayesian logistic regression analysis
Van Erp, H.R.N.; Van Gelder, P.H.A.J.M.
2012-01-01
In this paper we present a Bayesian logistic regression analysis. It is found that if one wishes to derive the posterior distribution of the probability of some event, then, together with the traditional Bayes Theorem and the integrating out of nuissance parameters, the Jacobian transformation is an
Loredo, Thomas J.
2004-04-01
I describe a framework for adaptive scientific exploration based on iterating an Observation-Inference-Design cycle that allows adjustment of hypotheses and observing protocols in response to the results of observation on-the-fly, as data are gathered. The framework uses a unified Bayesian methodology for the inference and design stages: Bayesian inference to quantify what we have learned from the available data and predict future data, and Bayesian decision theory to identify which new observations would teach us the most. When the goal of the experiment is simply to make inferences, the framework identifies a computationally efficient iterative ``maximum entropy sampling'' strategy as the optimal strategy in settings where the noise statistics are independent of signal properties. Results of applying the method to two ``toy'' problems with simulated data-measuring the orbit of an extrasolar planet, and locating a hidden one-dimensional object-show the approach can significantly improve observational efficiency in settings that have well-defined nonlinear models. I conclude with a list of open issues that must be addressed to make Bayesian adaptive exploration a practical and reliable tool for optimizing scientific exploration.
DEFF Research Database (Denmark)
Antoniou, Constantinos; Harrison, Glenn W.; Lau, Morten I.;
2015-01-01
A large literature suggests that many individuals do not apply Bayes’ Rule when making decisions that depend on them correctly pooling prior information and sample data. We replicate and extend a classic experimental study of Bayesian updating from psychology, employing the methods of experimental...
Bayesian Independent Component Analysis
DEFF Research Database (Denmark)
Winther, Ole; Petersen, Kaare Brandt
2007-01-01
In this paper we present an empirical Bayesian framework for independent component analysis. The framework provides estimates of the sources, the mixing matrix and the noise parameters, and is flexible with respect to choice of source prior and the number of sources and sensors. Inside the engine...
DEFF Research Database (Denmark)
Hartelius, Karsten; Carstensen, Jens Michael
2003-01-01
A method for locating distorted grid structures in images is presented. The method is based on the theories of template matching and Bayesian image restoration. The grid is modeled as a deformable template. Prior knowledge of the grid is described through a Markov random field (MRF) model which...
[Psychiatry in ancient Mexico].
Calderón Narváez, G
1992-12-01
Using studies on prehispanic and early post-conquest documents of Ancient Mexico--such as the Badianus Manuscript, also known as Libellus de Medicinalibus Indorum Herbis, and Brother Bernardino de Sahagún's famous work History of the Things of the New Spain, a description of some existing medical and psychiatric problems, and treatments Ancient Aztecs resorted to, is presented. The structure of the Aztec family, their problems with the excessive ingestion of alcoholic beverages, and the punishments native authorities had implemented in order to check alcoholism up are also described. PMID:1341125
Bisha Eugena
2015-01-01
Since in ancient times, in all human cultures, children transfered from biological parents to parents that want them to create family, for political alliances, for inheritance, for a future marriage, or to care for elderly parents. The practice of adoption was fairly common in different places and periods. Adoption is mention on Bible and Quran. Greeks, Romans, Egyptians and Babylonians had adoption systems.
Digital Repository Service at National Institute of Oceanography (India)
Tripati, S.
which plied between Kalinga and south east Asian countries. Nanda Raja, is said to have attacked Kalinga with the intention of getting access to the sea for the landlocked Kingdom of Magadha (Bihar). The ancient texa Artha Sastra (3rd-4th century B...
Printing Ancient Terracotta Warriors
Gadecki, Victoria L.
2010-01-01
Standing in awe in Xian, China, at the Terra Cotta warrior archaeological site, the author thought of sharing this experience and excitement with her sixth-grade students. She decided to let her students carve patterns of the ancient soldiers to understand their place in Chinese history. They would make block prints and print multiple soldiers on…
Creative Ventures: Ancient Civilizations.
Stark, Rebecca
The open-ended activities in this book are designed to extend the imagination and creativity of students and encourage students to examine their feelings and values about historic eras. Civilizations addressed include ancient Egypt, Greece, Rome, Mayan, Stonehenge, and Mesopotamia. The activities focus upon the cognitive and affective pupil…
Ancient Egyptian surgical heritage.
Saber, Aly
2010-12-01
Egyptian medicine influenced the medicine of neighboring cultures, including the culture of ancient Greece. From Greece, its influence spread onward, thereby affecting Western civilization significantly. The oldest extant Egyptian medical texts are six papyri: The Edwin Smith Surgical Papyrus and the Ebers Medical Papyrus are famous. PMID:21208098
Turk, Laraine D.
"Ancient Egypt," an upper-division, non-required history course covering Egypt from pre-dynastic time through the Roman domination is described. General descriptive information is presented first, including the method of grading, expectation of student success rate, long-range course objectives, procedures for revising the course, major course…
Ancient Egypt: Personal Perspectives.
Wolinski, Arelene
This teacher resource book provides information on ancient Egypt via short essays, photographs, maps, charts, and drawings. Egyptian social and religious life, including writing, art, architecture, and even the practice of mummification, is conveniently summarized for the teacher or other practitioner in a series of one to three page articles with…
Institute of Scientific and Technical Information of China (English)
WANGTONG
2004-01-01
LIJIANG is a small city onthe Yunnan-Guizhou Plateau in southern Chinawith an 800-year history.Word of its ancient language and music, and unique natural scenery has spread over the decades, and Lijiang is now known throughout the world. It was added
Probability and Bayesian statistics
1987-01-01
This book contains selected and refereed contributions to the "Inter national Symposium on Probability and Bayesian Statistics" which was orga nized to celebrate the 80th birthday of Professor Bruno de Finetti at his birthplace Innsbruck in Austria. Since Professor de Finetti died in 1985 the symposium was dedicated to the memory of Bruno de Finetti and took place at Igls near Innsbruck from 23 to 26 September 1986. Some of the pa pers are published especially by the relationship to Bruno de Finetti's scientific work. The evolution of stochastics shows growing importance of probability as coherent assessment of numerical values as degrees of believe in certain events. This is the basis for Bayesian inference in the sense of modern statistics. The contributions in this volume cover a broad spectrum ranging from foundations of probability across psychological aspects of formulating sub jective probability statements, abstract measure theoretical considerations, contributions to theoretical statistics an...
DEFF Research Database (Denmark)
Mørup, Morten; Schmidt, Mikkel N
2012-01-01
Many networks of scientific interest naturally decompose into clusters or communities with comparatively fewer external than internal links; however, current Bayesian models of network communities do not exert this intuitive notion of communities. We formulate a nonparametric Bayesian model...... for community detection consistent with an intuitive definition of communities and present a Markov chain Monte Carlo procedure for inferring the community structure. A Matlab toolbox with the proposed inference procedure is available for download. On synthetic and real networks, our model detects communities...... consistent with ground truth, and on real networks, it outperforms existing approaches in predicting missing links. This suggests that community structure is an important structural property of networks that should be explicitly modeled....
Brody, Samuel; Lapata, Mirella
2009-01-01
Sense induction seeks to automatically identify word senses directly from a corpus. A key assumption underlying previous work is that the context surrounding an ambiguous word is indicative of its meaning. Sense induction is thus typically viewed as an unsupervised clustering problem where the aim is to partition a word’s contexts into different classes, each representing a word sense. Our work places sense induction in a Bayesian context by modeling the contexts of the ambiguous word as samp...
Bayesian Generalized Rating Curves
Helgi Sigurðarson 1985
2014-01-01
A rating curve is a curve or a model that describes the relationship between water elevation, or stage, and discharge in an observation site in a river. The rating curve is fit from paired observations of stage and discharge. The rating curve then predicts discharge given observations of stage and this methodology is applied as stage is substantially easier to directly observe than discharge. In this thesis a statistical rating curve model is proposed working within the framework of Bayesian...
Efficient Bayesian Phase Estimation
Wiebe, Nathan; Granade, Chris
2016-07-01
We introduce a new method called rejection filtering that we use to perform adaptive Bayesian phase estimation. Our approach has several advantages: it is classically efficient, easy to implement, achieves Heisenberg limited scaling, resists depolarizing noise, tracks time-dependent eigenstates, recovers from failures, and can be run on a field programmable gate array. It also outperforms existing iterative phase estimation algorithms such as Kitaev's method.
Bayesian theory and applications
Dellaportas, Petros; Polson, Nicholas G; Stephens, David A
2013-01-01
The development of hierarchical models and Markov chain Monte Carlo (MCMC) techniques forms one of the most profound advances in Bayesian analysis since the 1970s and provides the basis for advances in virtually all areas of applied and theoretical Bayesian statistics. This volume guides the reader along a statistical journey that begins with the basic structure of Bayesian theory, and then provides details on most of the past and present advances in this field. The book has a unique format. There is an explanatory chapter devoted to each conceptual advance followed by journal-style chapters that provide applications or further advances on the concept. Thus, the volume is both a textbook and a compendium of papers covering a vast range of topics. It is appropriate for a well-informed novice interested in understanding the basic approach, methods and recent applications. Because of its advanced chapters and recent work, it is also appropriate for a more mature reader interested in recent applications and devel...
Wiegerinck, Wim; Schoenaker, Christiaan; Duane, Gregory
2016-04-01
Recently, methods for model fusion by dynamically combining model components in an interactive ensemble have been proposed. In these proposals, fusion parameters have to be learned from data. One can view these systems as parametrized dynamical systems. We address the question of learnability of dynamical systems with respect to both short term (vector field) and long term (attractor) behavior. In particular we are interested in learning in the imperfect model class setting, in which the ground truth has a higher complexity than the models, e.g. due to unresolved scales. We take a Bayesian point of view and we define a joint log-likelihood that consists of two terms, one is the vector field error and the other is the attractor error, for which we take the L1 distance between the stationary distributions of the model and the assumed ground truth. In the context of linear models (like so-called weighted supermodels), and assuming a Gaussian error model in the vector fields, vector field learning leads to a tractable Gaussian solution. This solution can then be used as a prior for the next step, Bayesian attractor learning, in which the attractor error is used as a log-likelihood term. Bayesian attractor learning is implemented by elliptical slice sampling, a sampling method for systems with a Gaussian prior and a non Gaussian likelihood. Simulations with a partially observed driven Lorenz 63 system illustrate the approach.
Bayesian optimization for materials design
Frazier, Peter I.; Wang, Jialei
2015-01-01
We introduce Bayesian optimization, a technique developed for optimizing time-consuming engineering simulations and for fitting machine learning models on large datasets. Bayesian optimization guides the choice of experiments during materials design and discovery to find good material designs in as few experiments as possible. We focus on the case when materials designs are parameterized by a low-dimensional vector. Bayesian optimization is built on a statistical technique called Gaussian pro...
Bayesian Posteriors Without Bayes' Theorem
Hill, Theodore P
2012-01-01
The classical Bayesian posterior arises naturally as the unique solution of several different optimization problems, without the necessity of interpreting data as conditional probabilities and then using Bayes' Theorem. For example, the classical Bayesian posterior is the unique posterior that minimizes the loss of Shannon information in combining the prior and the likelihood distributions. These results, direct corollaries of recent results about conflations of probability distributions, reinforce the use of Bayesian posteriors, and may help partially reconcile some of the differences between classical and Bayesian statistics.
Gupta, Patrick Das
2014-01-01
The Indo-aryans of ancient India observed stars and constellations for ascertaining auspicious times for sacrificial rites ordained by vedas. It is but natural that they would have recounted in the vedic texts about comets. In Rigveda ($\\sim $ 1700 - 1500 BC) and Atharvaveda ($\\sim $ 1150 BC), there are references to dhumaketus and ketus, which stand for comets in Sanskrit. Varahamihira in 550 AD and Ballala Sena ($\\sim $ 1100 - 1200 AD) have described a large number of comets recorded by ancient seers such as Parashara, Vriddha Garga, Narada, Garga, etc. In this article, I conjecture that an episode narrated in Mahabharata of a radiant king, Nahusha, ruling the heavens, and later turning into a serpent after he had kicked the seer Agastya (also the star Canopus), is a mythological retelling of a cometary event.
Warinner, Christina; Speller, Camilla; Collins, Matthew J.; Lewis, Cecil M.
2015-01-01
Very recently, we discovered a vast new microbial self: the human microbiome. Our native microbiota interface with our biology and culture to influence our health, behavior, and quality of life, and yet we know very little about their origin, evolution, or ecology. With the advent of industrialization, globalization, and modern sanitation, it is intuitive that we have changed our relationship with microbes, but we have little information about the ancestral state of our microbiome, and therefore, we lack a foundation for characterizing this change. High-throughput sequencing has opened up new opportunities in the field of paleomicrobiology, allowing us to investigate the evolution of the complex microbial ecologies that inhabit our bodies. By focusing on recent coprolite and dental calculus research, we explore how emerging research on ancient human microbiomes is changing the way we think about ancient disease and how archaeological studies can contribute to a medical understanding of health and nutrition today. PMID:25559298
Budde, K B; González-Martínez, S C; Hardy, O J; Heuertz, M
2013-07-01
Understanding the history of forests and their species' demographic responses to past disturbances is important for predicting impacts of future environmental changes. Tropical rainforests of the Guineo-Congolian region in Central Africa are believed to have survived the Pleistocene glacial periods in a few major refugia, essentially centred on mountainous regions close to the Atlantic Ocean. We tested this hypothesis by investigating the phylogeographic structure of a widespread, ancient rainforest tree species, Symphonia globulifera L. f. (Clusiaceae), using plastid DNA sequences (chloroplast DNA [cpDNA], psbA-trnH intergenic spacer) and nuclear microsatellites (simple sequence repeats, SSRs). SSRs identified four gene pools located in Benin, West Cameroon, South Cameroon and Gabon, and São Tomé. This structure was also apparent at cpDNA. Approximate Bayesian Computation detected recent bottlenecks approximately dated to the last glacial maximum in Benin, West Cameroon and São Tomé, and an older bottleneck in South Cameroon and Gabon, suggesting a genetic effect of Pleistocene cycles of forest contraction. CpDNA haplotype distribution indicated wide-ranging long-term persistence of S. globulifera both inside and outside of postulated forest refugia. Pollen flow was four times greater than that of seed in South Cameroon and Gabon, which probably enabled rapid population recovery after bottlenecks. Furthermore, our study suggested ecotypic differentiation-coastal or swamp vs terra firme-in S. globulifera. Comparison with other tree phylogeographic studies in Central Africa highlighted the relevance of species-specific responses to environmental change in forest trees. PMID:23572126
Congdon, Peter
2014-01-01
This book provides an accessible approach to Bayesian computing and data analysis, with an emphasis on the interpretation of real data sets. Following in the tradition of the successful first edition, this book aims to make a wide range of statistical modeling applications accessible using tested code that can be readily adapted to the reader's own applications. The second edition has been thoroughly reworked and updated to take account of advances in the field. A new set of worked examples is included. The novel aspect of the first edition was the coverage of statistical modeling using WinBU
Computationally efficient Bayesian tracking
Aughenbaugh, Jason; La Cour, Brian
2012-06-01
In this paper, we describe the progress we have achieved in developing a computationally efficient, grid-based Bayesian fusion tracking system. In our approach, the probability surface is represented by a collection of multidimensional polynomials, each computed adaptively on a grid of cells representing state space. Time evolution is performed using a hybrid particle/grid approach and knowledge of the grid structure, while sensor updates use a measurement-based sampling method with a Delaunay triangulation. We present an application of this system to the problem of tracking a submarine target using a field of active and passive sonar buoys.
Bayesian nonparametric data analysis
Müller, Peter; Jara, Alejandro; Hanson, Tim
2015-01-01
This book reviews nonparametric Bayesian methods and models that have proven useful in the context of data analysis. Rather than providing an encyclopedic review of probability models, the book’s structure follows a data analysis perspective. As such, the chapters are organized by traditional data analysis problems. In selecting specific nonparametric models, simpler and more traditional models are favored over specialized ones. The discussed methods are illustrated with a wealth of examples, including applications ranging from stylized examples to case studies from recent literature. The book also includes an extensive discussion of computational methods and details on their implementation. R code for many examples is included in on-line software pages.
Bayesian Geostatistical Design
DEFF Research Database (Denmark)
Diggle, Peter; Lophaven, Søren Nymand
2006-01-01
locations to, or deletion of locations from, an existing design, and prospective design, which consists of choosing positions for a new set of sampling locations. We propose a Bayesian design criterion which focuses on the goal of efficient spatial prediction whilst allowing for the fact that model......This paper describes the use of model-based geostatistics for choosing the set of sampling locations, collectively called the design, to be used in a geostatistical analysis. Two types of design situation are considered. These are retrospective design, which concerns the addition of sampling...
Institute of Scientific and Technical Information of China (English)
2012-01-01
The typical style and features of mountains and waters in Caoshi Ancient Town,have hitherto been well preserved. Caoshi Ancient Town boasts superior base of the natural eco-environment and deep-rooted background of regional culture,where mountains,waters,shoals,towns and other landscape elements are merged harmoniously,the transportation and geographical conditions have been fundamentally changed. Ancient towns,old temples,ancient forests,ancient wells and ancient piers are unique in different ways,with characteristics of tourism resources such as long history and ancient folklore. It should seize the historical opportunity of China vigorously developing rural tourism based on the construction of the new socialist countryside,to make characteristic agricultural economy gain ground; assume the leading role to drive the development of tourism economy in surrounding areas; correctly handle the relationship between development and protection to walk the path of sustainable development of tourism.
Across and within-forest effects on breeding success in Mediterranean Great Tits Parus major
Atienzar, Francisco; Visser, Marcel E.; Greno, Jose L.; Holleman, Leonard J. M.; Belda, Eduardo J.; Barba, Emilio
2010-01-01
Forest type and habitat structure can have profound effects on different aspects of avian life histories. These effects may, however, strongly differ across and within forests that vary in vegetation composition and structure, especially when an ancient forest has been replaced by a new forest. To t
Inference in hybrid Bayesian networks
DEFF Research Database (Denmark)
Lanseth, Helge; Nielsen, Thomas Dyhre; Rumí, Rafael;
2009-01-01
Since the 1980s, Bayesian Networks (BNs) have become increasingly popular for building statistical models of complex systems. This is particularly true for boolean systems, where BNs often prove to be a more efficient modelling framework than traditional reliability-techniques (like fault trees...... decade's research on inference in hybrid Bayesian networks. The discussions are linked to an example model for estimating human reliability....
Laios, K; Tsoukalas, G; Kontaxaki, M-I; Karamanou, M; Androutsos, G
2014-01-01
The theme of suicide appears several times in ancient Greek literature. However, each such reference acquires special significance depending on the field from which it originates. Most of the information found in mythology, but the suicide in a mythological tale, although in terms of motivation and mental situation of heroes may be in imitation of similar incidents of real life, in fact is linked with the principles of the ancient Greek religion. In ancient drama and mainly in tragedies suicide conduces to the tragic hypostasis of the heroes and to the evolution of the plot and also is a tool in order to be presented the ideas of poets for the relations of the gods, the relation among gods and men and the relation among the men. In ancient Greek philosophy there were the deniers of suicide, who were more concerned about the impact of suicide on society and also these who accepted it, recognizing the right of the individual to put an end to his life, in order to avoid personal misfortunes. Real suicides will be found mostly from historical sources, but most of them concern leading figures of the ancient world. Closer to the problem of suicide in the everyday life of antiquity are ancient Greek medicines, who studied the phenomenon more general without references to specific incidents. Doctors did not approve in principal the suicide and dealt with it as insane behavior in the development of the mental diseases, of melancholia and mania. They considered that the discrepancy of humors in the organ of logic in the human body will cause malfunction, which will lead to the absurdity and consequently to suicide, either due to excessive concentration of black bile in melancholia or due to yellow bile in mania. They believed that greater risk to commit suicide had women, young people and the elderly. As therapy they used the drugs of their time with the intention to induce calm and repression in the ill person, therefore they mainly used mandragora. In general, we would say
Laios, K; Tsoukalas, G; Kontaxaki, M-I; Karamanou, M; Androutsos, G
2014-01-01
The theme of suicide appears several times in ancient Greek literature. However, each such reference acquires special significance depending on the field from which it originates. Most of the information found in mythology, but the suicide in a mythological tale, although in terms of motivation and mental situation of heroes may be in imitation of similar incidents of real life, in fact is linked with the principles of the ancient Greek religion. In ancient drama and mainly in tragedies suicide conduces to the tragic hypostasis of the heroes and to the evolution of the plot and also is a tool in order to be presented the ideas of poets for the relations of the gods, the relation among gods and men and the relation among the men. In ancient Greek philosophy there were the deniers of suicide, who were more concerned about the impact of suicide on society and also these who accepted it, recognizing the right of the individual to put an end to his life, in order to avoid personal misfortunes. Real suicides will be found mostly from historical sources, but most of them concern leading figures of the ancient world. Closer to the problem of suicide in the everyday life of antiquity are ancient Greek medicines, who studied the phenomenon more general without references to specific incidents. Doctors did not approve in principal the suicide and dealt with it as insane behavior in the development of the mental diseases, of melancholia and mania. They considered that the discrepancy of humors in the organ of logic in the human body will cause malfunction, which will lead to the absurdity and consequently to suicide, either due to excessive concentration of black bile in melancholia or due to yellow bile in mania. They believed that greater risk to commit suicide had women, young people and the elderly. As therapy they used the drugs of their time with the intention to induce calm and repression in the ill person, therefore they mainly used mandragora. In general, we would say
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.
Dance in Ancient Greek Culture
Spalva, Rita
2015-01-01
The greatness and harmony of ancient Greece has had an impact upon the development of the Western European culture to this day. The ancient Greek culture has influenced contemporary literature genres and systems of philosophy, principles of architecture, sculpture and drama and has formed basis for such sciences as astronomy and mathematics. The art of ancient Greece with its penchant for beauty and clarity has been the example of the humanity’s search for an aesthetic ideal. Despite only bei...
Implementing Bayesian Vector Autoregressions Implementing Bayesian Vector Autoregressions
Directory of Open Access Journals (Sweden)
Richard M. Todd
1988-03-01
Full Text Available Implementing Bayesian Vector Autoregressions This paper discusses how the Bayesian approach can be used to construct a type of multivariate forecasting model known as a Bayesian vector autoregression (BVAR. In doing so, we mainly explain Doan, Littermann, and Sims (1984 propositions on how to estimate a BVAR based on a certain family of prior probability distributions. indexed by a fairly small set of hyperparameters. There is also a discussion on how to specify a BVAR and set up a BVAR database. A 4-variable model is used to iliustrate the BVAR approach.
DEFF Research Database (Denmark)
Climate, and human responses to it, have a strongly interconnected relationship. This when climate change occurs, the result of either natural or human causes, societies should react and adapt to these. But do they? If so, what is the nature of that change, and are the responses positive...... or negative for the long-term survival of social groups? In this volume, scholars from diverse disciplines including archaeology, geology and climate sciences explore scientific and material evidence for climate changes in the past, their causes, their effects on ancient societies and how those societies...
Dantzig, Tobias
2006-01-01
More than a history of mathematics, this lively book traces mathematical ideas and processes to their sources, stressing the methods used by the masters of the ancient world. Author Tobias Dantzig portrays the human story behind mathematics, showing how flashes of insight in the minds of certain gifted individuals helped mathematics take enormous forward strides. Dantzig demonstrates how the Greeks organized their precursors' melange of geometric maxims into an elegantly abstract deductive system. He also explains the ways in which some of the famous mathematical brainteasers of antiquity led
Sparavigna, Amelia Carolina
2011-01-01
It is commonly believed that the ancient Romans were the first to create and use concrete. This is not true, as we can easily learn from the Latin literature itself. For sure, Romans were able to prepare high-quality hydraulic cements, comparable with the modern Portland cements. In this paper, we will see that the use of concrete is quite older, ranging back to the Homeric times. For instance, it was used for the floors of some courts and galleries of the Mycenaean palace at Tiryns
Dynamic Bayesian diffusion estimation
Dedecius, K
2012-01-01
The rapidly increasing complexity of (mainly wireless) ad-hoc networks stresses the need of reliable distributed estimation of several variables of interest. The widely used centralized approach, in which the network nodes communicate their data with a single specialized point, suffers from high communication overheads and represents a potentially dangerous concept with a single point of failure needing special treatment. This paper's aim is to contribute to another quite recent method called diffusion estimation. By decentralizing the operating environment, the network nodes communicate just within a close neighbourhood. We adopt the Bayesian framework to modelling and estimation, which, unlike the traditional approaches, abstracts from a particular model case. This leads to a very scalable and universal method, applicable to a wide class of different models. A particularly interesting case - the Gaussian regressive model - is derived as an example.
Book review: Bayesian analysis for population ecology
Link, William A.
2011-01-01
Brian Dennis described the field of ecology as “fertile, uncolonized ground for Bayesian ideas.” He continued: “The Bayesian propagule has arrived at the shore. Ecologists need to think long and hard about the consequences of a Bayesian ecology. The Bayesian outlook is a successful competitor, but is it a weed? I think so.” (Dennis 2004)
Exploring Ancient Skies A Survey of Ancient and Cultural Astronomy
Kelley, David H
2011-01-01
Exploring Ancient Skies brings together the methods of archaeology and the insights of modern astronomy to explore the science of astronomy as it was practiced in various cultures prior to the invention of the telescope. The book reviews an enormous and growing body of literature on the cultures of the ancient Mediterranean, the Far East, and the New World (particularly Mesoamerica), putting the ancient astronomical materials into their archaeological and cultural contexts. The authors begin with an overview of the field and proceed to essential aspects of naked-eye astronomy, followed by an examination of specific cultures. The book concludes by taking into account the purposes of ancient astronomy: astrology, navigation, calendar regulation, and (not least) the understanding of our place and role in the universe. Skies are recreated to display critical events as they would have appeared to ancient observers—events such as the supernova of 1054 A.D., the "lion horoscope," and the Star of Bethlehem. Explori...
Authenticity in ancient DNA studies
DEFF Research Database (Denmark)
Gilbert, M Thomas P; Willerslev, Eske
2006-01-01
Ancient DNA studies represent a powerful tool that can be used to obtain genetic insights into the past. However, despite the publication of large numbers of apparently successful ancient DNA studies, a number of problems exist with the field that are often ignored. Therefore, questions exist as ...
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
Tamil merchant in ancient Mesopotamia.
Directory of Open Access Journals (Sweden)
Malliya Gounder Palanichamy
Full Text Available Recent analyses of ancient Mesopotamian mitochondrial genomes have suggested a genetic link between the Indian subcontinent and Mesopotamian civilization. There is no consensus on the origin of the ancient Mesopotamians. They may be descendants of migrants, who founded regional Mesopotamian groups like that of Terqa or they may be merchants who were involved in trans Mesopotamia trade. To identify the Indian source population showing linkage to the ancient Mesopotamians, we screened a total of 15,751 mitochondrial DNAs (11,432 from the literature and 4,319 from this study representing all major populations of India. Our results although suggest that south India (Tamil Nadu and northeast India served as the source of the ancient Mesopotamian mtDNA gene pool, mtDNA of these ancient Mesopotamians probably contributed by Tamil merchants who were involved in the Indo-Roman trade.
Tamil merchant in ancient Mesopotamia.
Palanichamy, Malliya Gounder; Mitra, Bikash; Debnath, Monojit; Agrawal, Suraksha; Chaudhuri, Tapas Kumar; Zhang, Ya-Ping
2014-01-01
Recent analyses of ancient Mesopotamian mitochondrial genomes have suggested a genetic link between the Indian subcontinent and Mesopotamian civilization. There is no consensus on the origin of the ancient Mesopotamians. They may be descendants of migrants, who founded regional Mesopotamian groups like that of Terqa or they may be merchants who were involved in trans Mesopotamia trade. To identify the Indian source population showing linkage to the ancient Mesopotamians, we screened a total of 15,751 mitochondrial DNAs (11,432 from the literature and 4,319 from this study) representing all major populations of India. Our results although suggest that south India (Tamil Nadu) and northeast India served as the source of the ancient Mesopotamian mtDNA gene pool, mtDNA of these ancient Mesopotamians probably contributed by Tamil merchants who were involved in the Indo-Roman trade. PMID:25299580
Irregular-Time Bayesian Networks
Ramati, Michael
2012-01-01
In many fields observations are performed irregularly along time, due to either measurement limitations or lack of a constant immanent rate. While discrete-time Markov models (as Dynamic Bayesian Networks) introduce either inefficient computation or an information loss to reasoning about such processes, continuous-time Markov models assume either a discrete state space (as Continuous-Time Bayesian Networks), or a flat continuous state space (as stochastic dif- ferential equations). To address these problems, we present a new modeling class called Irregular-Time Bayesian Networks (ITBNs), generalizing Dynamic Bayesian Networks, allowing substantially more compact representations, and increasing the expressivity of the temporal dynamics. In addition, a globally optimal solution is guaranteed when learning temporal systems, provided that they are fully observed at the same irregularly spaced time-points, and a semiparametric subclass of ITBNs is introduced to allow further adaptation to the irregular nature of t...
Mapping the Ancient Maya Landscape from Space
Sever, Tom
2003-01-01
This project uses new satellite and airborne imagery in combination with remote sensing, GIS, and GPS technology to understand the dynamics of how the Maya successfully interacted with their karst topographic landscape for several centuries in the northern Peten region of Guatemala. The ancient Maya attained one of the greatest population densities in human history in the tropical forest of the Peten, Guatemala, and it was in this region that the Maya civilization began, flourished, and abruptly disappeared for unknown reasons around AD 800. How the Maya were able to successfully manage water and feed this dense population is not known at this time. However, a recent NASA-funded project was the first to investigate large seasonal swamps (bajos) that make up 40 percent of the landscape. Through the use of remote sensing, ancient Maya features such as cities, roadways, canals and water reservoirs have been detected and verified through ground reconnaissance. The results of this research cast new light on the adaptation of the ancient Maya to their environment. Micro-environmental variation within the wetlands was elucidated and the different vegetational associations identified in the satellite imagery. More than 70 new archeological sites within and at the edges of the bajo were mapped and tested. Modification of the landscape by the Maya in the form of dams and reservoirs in the Holmul River and its tributaries and possible drainage canals in bajos was demonstrated. The recent acquisition of one-meter IKONOS imagery and high resolution STAR-3i radar imagery (2.5m backscatter/ 10m DEM), opens new possibilities for understanding how a civilization was able to survive for centuries upon a karst topographic landscape and their human-induced effects upon the local climate. This understanding is critical for the current population that is presently experiencing rapid population growth and destroying the landscape through non-traditional farming and grazing techniques
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...
Deng, Kehui
Timekeeping was essential in the agricultural society of ancient China. The use of sundials for timekeeping was associated with the use of the gnomon, which had its origin in remote antiquity. This chapter studies three sundials (guiyi 晷仪) from the Qin and Han dynasties, the shorter shadow plane sundial (duanying ping yi 短影平仪) invented by Yuan Chong in the Sui Dynasty, and the sundial chart (guiyingtu 晷影图) invented by Zeng Minxing in the Southern Song dynasty. This chapter also introduces Guo Shoujing's hemispherical sundial (yang yi 仰仪). A circular stone sundial discovered at the Small Wild Goose Pagoda in Xi'an is also mentioned. It is dated from the Sui and Tang dynasties. A brief survey of sundials from the Qing dynasty shows various types of sundials.
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.
Dynamic Batch Bayesian Optimization
Azimi, Javad; Fern, Xiaoli
2011-01-01
Bayesian optimization (BO) algorithms try to optimize an unknown function that is expensive to evaluate using minimum number of evaluations/experiments. Most of the proposed algorithms in BO are sequential, where only one experiment is selected at each iteration. This method can be time inefficient when each experiment takes a long time and more than one experiment can be ran concurrently. On the other hand, requesting a fix-sized batch of experiments at each iteration causes performance inefficiency in BO compared to the sequential policies. In this paper, we present an algorithm that asks a batch of experiments at each time step t where the batch size p_t is dynamically determined in each step. Our algorithm is based on the observation that the sequence of experiments selected by the sequential policy can sometimes be almost independent from each other. Our algorithm identifies such scenarios and request those experiments at the same time without degrading the performance. We evaluate our proposed method us...
Nonparametric Bayesian Classification
Coram, M A
2002-01-01
A Bayesian approach to the classification problem is proposed in which random partitions play a central role. It is argued that the partitioning approach has the capacity to take advantage of a variety of large-scale spatial structures, if they are present in the unknown regression function $f_0$. An idealized one-dimensional problem is considered in detail. The proposed nonparametric prior uses random split points to partition the unit interval into a random number of pieces. This prior is found to provide a consistent estimate of the regression function in the $\\L^p$ topology, for any $1 \\leq p < \\infty$, and for arbitrary measurable $f_0:[0,1] \\rightarrow [0,1]$. A Markov chain Monte Carlo (MCMC) implementation is outlined and analyzed. Simulation experiments are conducted to show that the proposed estimate compares favorably with a variety of conventional estimators. A striking resemblance between the posterior mean estimate and the bagged CART estimate is noted and discussed. For higher dimensions, a ...
Did the ancient Egyptians migrate to ancient Nigeria?
Jock M. Agai
2014-01-01
Literatures concerning the history of West African peoples published from 1900 to 1970 debate�the possible migrations of the Egyptians into West Africa. Writers like Samuel Johnson and�Lucas Olumide believe that the ancient Egyptians penetrated through ancient Nigeria but Leo�Frobenius and Geoffrey Parrinder frowned at this opinion. Using the works of these early�20th century writers of West African history together with a Yoruba legend which teaches�about the origin of their earliest ancesto...
[Ancient Egyptian Odontology].
Berghult, B
1999-01-01
In ancient Egypt during the reign of Pharaoh Djoser, circa 2650 BC, the Step Pyramid was constructed by Imhotep. He was later worshiped as the God of Medicine. One of his contemporaries was the powerful writer Hesy who is reproduced on a panel showing a rebus of a swallow, a tusk and an arrow. He is therefore looked upon as being the first depicted odontologist. The art of writing begun in Egypt in about 3100 BC and the medical texts we know from different papyri were copied with hieratic signs around 1900-1100 BC. One of the most famous is the Papyrus Ebers. It was purchased by professor Ebers on a research travel to Luxor in 1873. Two years later a beautiful facsimile in color was published and the best translation came in 1958 in German. The text includes 870 remedies and some of them are related to teeth and oral troubles like pain in the mouth, gingivitis, periodontitis and cavities in the teeth. The most common oral pain was probably pulpitis caused by extreme attrition due to the high consumption of bread contaminated with soil and/or quern minerals. Another text is the Papyrus Edwin Smith with four surgical cases of dental interest. The "toothworms" that were presumed to bring about decayed teeth have not been identified in the medical texts. It was not until 1889 W.D. Miller presented a scientific explanation that cavities were caused by bacteria. In spite of extensive research only a few evidence of prosthetic and invasive treatments have been found and these dental artifacts have probably been made post mortem. Some of the 150 identified doctors were associated with treatments of disorders of the mouth. The stele of Seneb from Sa'is during the 26th dynasty of Psamtik, 664-525 BC, shows a young man who probably was a dental healer well known to Pharaoh and his court. Clement of Alexandria mentions circa 200 AD that the written knowledge of the old Egyptians was gathered in 42 collections of papyri. Number 37-42 contained the medical writings. The
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
Ancient Astronomical Monuments of Athens
Theodossiou, E.; Manimanis, V. N.
2010-07-01
In this work, four ancient monuments of astronomical significance found in Athens and still kept in the same city in good condition are presented. The first one is the conical sundial on the southern slope of the Acropolis. The second one is the Tower of the Winds and its vertical sundials in the Roman Forum of Athens, a small octagonal marble tower with sundials on all 8 of its sides, plus a water-clock inside the tower. The third monument-instrument is the ancient clepsydra of Athens, one of the findings from the Ancient Agora of Athens, a unique water-clock dated from 400 B.C. Finally, the fourth one is the carved ancient Athenian calendar over the main entrance of the small Byzantine temple of the 8th Century, St. Eleftherios, located to the south of the temple of the Annunciation of Virgin Mary, the modern Cathedral of the city of Athens.
Aylesworth, Grant R.
Although there is little doubt that the ancient Maya of Mesoamerica laid their cities out based, in part, on astronomical considerations, the proliferation of "cosmograms" in contemporary scholarly discourse has complicated matters for the acceptance of rigorous archaeoastronomical research.
Reconstructing ancient genomes and epigenomes
DEFF Research Database (Denmark)
Orlando, Ludovic Antoine Alexandre; Gilbert, M. Thomas P.; Willerslev, Eske
2015-01-01
DNA studies have now progressed to whole-genome sequencing for an increasing number of ancient individuals and extinct species, as well as to epigenomic characterization. Such advances have enabled the sequencing of specimens of up to 1 million years old, which, owing to their extensive DNA damage and...... contamination, were previously not amenable to genetic analyses. In this Review, we discuss these varied technical challenges and solutions for sequencing ancient genomes and epigenomes....
Orthopedic surgery in ancient Egypt
Blomstedt, Patric
2014-01-01
Background — Ancient Egypt might be considered the cradle of medicine. The modern literature is, however, sometimes rather too enthusiastic regarding the procedures that are attributed an Egyptian origin. I briefly present and analyze the claims regarding orthopedic surgery in Egypt, what was actually done by the Egyptians, and what may have been incorrectly ascribed to them. Methods — I reviewed the original sources and also the modern literature regarding surgery in ancient Egypt, concentra...
Effects of tree species composition on within-forest distribution of understorey species
Oijen, van D.; Feijen, M.; Hommel, P.W.F.M.; Ouden, den J.; Waal, de R.W.
2005-01-01
Question: Do tree species, with different litter qualities, affect the within-forest distribution of forest understorey species on intermediate to base-rich soils? Since habitat loss and fragmentation have caused ancient forest species to decline, those species are the main focus of this study. Loca
Attention in a bayesian framework
DEFF Research Database (Denmark)
Whiteley, Louise Emma; Sahani, Maneesh
2012-01-01
The behavioral phenomena of sensory attention are thought to reflect the allocation of a limited processing resource, but there is little consensus on the nature of the resource or why it should be limited. Here we argue that a fundamental bottleneck emerges naturally within Bayesian models...... of perception, and use this observation to frame a new computational account of the need for, and action of, attention - unifying diverse attentional phenomena in a way that goes beyond previous inferential, probabilistic and Bayesian models. Attentional effects are most evident in cluttered environments......, and include both selective phenomena, where attention is invoked by cues that point to particular stimuli, and integrative phenomena, where attention is invoked dynamically by endogenous processing. However, most previous Bayesian accounts of attention have focused on describing relatively simple experimental...
Probability biases as Bayesian inference
Directory of Open Access Journals (Sweden)
Andre; C. R. Martins
2006-11-01
Full Text Available In this article, I will show how several observed biases in human probabilistic reasoning can be partially explained as good heuristics for making inferences in an environment where probabilities have uncertainties associated to them. Previous results show that the weight functions and the observed violations of coalescing and stochastic dominance can be understood from a Bayesian point of view. We will review those results and see that Bayesian methods should also be used as part of the explanation behind other known biases. That means that, although the observed errors are still errors under the be understood as adaptations to the solution of real life problems. Heuristics that allow fast evaluations and mimic a Bayesian inference would be an evolutionary advantage, since they would give us an efficient way of making decisions. %XX In that sense, it should be no surprise that humans reason with % probability as it has been observed.
Bayesian Methods and Universal Darwinism
Campbell, John
2010-01-01
Bayesian methods since the time of Laplace have been understood by their practitioners as closely aligned to the scientific method. Indeed a recent champion of Bayesian methods, E. T. Jaynes, titled his textbook on the subject Probability Theory: the Logic of Science. Many philosophers of science including Karl Popper and Donald Campbell have interpreted the evolution of Science as a Darwinian process consisting of a 'copy with selective retention' algorithm abstracted from Darwin's theory of Natural Selection. Arguments are presented for an isomorphism between Bayesian Methods and Darwinian processes. Universal Darwinism, as the term has been developed by Richard Dawkins, Daniel Dennett and Susan Blackmore, is the collection of scientific theories which explain the creation and evolution of their subject matter as due to the operation of Darwinian processes. These subject matters span the fields of atomic physics, chemistry, biology and the social sciences. The principle of Maximum Entropy states that system...
Bayesian modeling using WinBUGS
Ntzoufras, Ioannis
2009-01-01
A hands-on introduction to the principles of Bayesian modeling using WinBUGS Bayesian Modeling Using WinBUGS provides an easily accessible introduction to the use of WinBUGS programming techniques in a variety of Bayesian modeling settings. The author provides an accessible treatment of the topic, offering readers a smooth introduction to the principles of Bayesian modeling with detailed guidance on the practical implementation of key principles. The book begins with a basic introduction to Bayesian inference and the WinBUGS software and goes on to cover key topics, including: Markov Chain Monte Carlo algorithms in Bayesian inference Generalized linear models Bayesian hierarchical models Predictive distribution and model checking Bayesian model and variable evaluation Computational notes and screen captures illustrate the use of both WinBUGS as well as R software to apply the discussed techniques. Exercises at the end of each chapter allow readers to test their understanding of the presented concepts and all ...
Bayesian test and Kuhn's paradigm
Institute of Scientific and Technical Information of China (English)
Chen Xiaoping
2006-01-01
Kuhn's theory of paradigm reveals a pattern of scientific progress,in which normal science alternates with scientific revolution.But Kuhn underrated too much the function of scientific test in his pattern,because he focuses all his attention on the hypothetico-deductive schema instead of Bayesian schema.This paper employs Bayesian schema to re-examine Kuhn's theory of paradigm,to uncover its logical and rational components,and to illustrate the tensional structure of logic and belief,rationality and irrationality,in the process of scientific revolution.
Perception, illusions and Bayesian inference.
Nour, Matthew M; Nour, Joseph M
2015-01-01
Descriptive psychopathology makes a distinction between veridical perception and illusory perception. In both cases a perception is tied to a sensory stimulus, but in illusions the perception is of a false object. This article re-examines this distinction in light of new work in theoretical and computational neurobiology, which views all perception as a form of Bayesian statistical inference that combines sensory signals with prior expectations. Bayesian perceptual inference can solve the 'inverse optics' problem of veridical perception and provides a biologically plausible account of a number of illusory phenomena, suggesting that veridical and illusory perceptions are generated by precisely the same inferential mechanisms.
3D Bayesian contextual classifiers
DEFF Research Database (Denmark)
Larsen, Rasmus
2000-01-01
We extend a series of multivariate Bayesian 2-D contextual classifiers to 3-D by specifying a simultaneous Gaussian distribution for the feature vectors as well as a prior distribution of the class variables of a pixel and its 6 nearest 3-D neighbours.......We extend a series of multivariate Bayesian 2-D contextual classifiers to 3-D by specifying a simultaneous Gaussian distribution for the feature vectors as well as a prior distribution of the class variables of a pixel and its 6 nearest 3-D neighbours....
Bayesian methods for proteomic biomarker development
Directory of Open Access Journals (Sweden)
Belinda Hernández
2015-12-01
In this review we provide an introduction to Bayesian inference and demonstrate some of the advantages of using a Bayesian framework. We summarize how Bayesian methods have been used previously in proteomics and other areas of bioinformatics. Finally, we describe some popular and emerging Bayesian models from the statistical literature and provide a worked tutorial including code snippets to show how these methods may be applied for the evaluation of proteomic biomarkers.
Bayesian variable order Markov models: Towards Bayesian predictive state representations
C. Dimitrakakis
2009-01-01
We present a Bayesian variable order Markov model that shares many similarities with predictive state representations. The resulting models are compact and much easier to specify and learn than classical predictive state representations. Moreover, we show that they significantly outperform a more st
Did the ancient Egyptians migrate to ancient Nigeria?
Directory of Open Access Journals (Sweden)
Jock M. Agai
2014-01-01
Full Text Available Literatures concerning the history of West African peoples published from 1900 to 1970 debate�the possible migrations of the Egyptians into West Africa. Writers like Samuel Johnson and�Lucas Olumide believe that the ancient Egyptians penetrated through ancient Nigeria but Leo�Frobenius and Geoffrey Parrinder frowned at this opinion. Using the works of these early�20th century writers of West African history together with a Yoruba legend which teaches�about the origin of their earliest ancestor(s, this researcher investigates the theories that the�ancient Egyptians had contact with the ancient Nigerians and particularly with the Yorubas.Intradisciplinary and/or interdisciplinary implications: There is an existing ideology�amongst the Yorubas and other writers of Yoruba history that the original ancestors of�the Yorubas originated in ancient Egypt hence there was migration between Egypt and�Yorubaland. This researcher contends that even if there was migration between Egypt and�Nigeria, such migration did not take place during the predynastic and dynastic period as�speculated by some scholars. The subject is open for further research.
Bayesian networks and food security - An introduction
Stein, A.
2004-01-01
This paper gives an introduction to Bayesian networks. Networks are defined and put into a Bayesian context. Directed acyclical graphs play a crucial role here. Two simple examples from food security are addressed. Possible uses of Bayesian networks for implementation and further use in decision sup
Bayesian Model Averaging for Propensity Score Analysis
Kaplan, David; Chen, Jianshen
2013-01-01
The purpose of this study is to explore Bayesian model averaging in the propensity score context. Previous research on Bayesian propensity score analysis does not take into account model uncertainty. In this regard, an internally consistent Bayesian framework for model building and estimation must also account for model uncertainty. The…
A Bayesian Nonparametric Approach to Test Equating
Karabatsos, George; Walker, Stephen G.
2009-01-01
A Bayesian nonparametric model is introduced for score equating. It is applicable to all major equating designs, and has advantages over previous equating models. Unlike the previous models, the Bayesian model accounts for positive dependence between distributions of scores from two tests. The Bayesian model and the previous equating models are…
Forest crimes as a threat to sustainable forest management
Directory of Open Access Journals (Sweden)
S. Özden
2016-08-01
Full Text Available From ancient times to the present day, forest public relations has been an issue on the agenda. This relationship’s purpose was initially needed for shelter and nutrition; however today this process has changed with urbanization, overpopulation and understanding the new functions of forests. When land ownership became a tool of production, offenses occurred in order to convert forestlands to agricultural lands. So the vast majority of the world’s forests have been lost for this reason. Today, deforestation is occurring in tropical countries that are expecting to gain agricultural area. The purpose of this study is to investigate the relationship between urbanization and the qualitative and quantitative characteristics of forest crimes, which are a major obstacle for sustainable forestry. Although forests cover about 27 % of Turkey’s territory, the forests are losing viability; the status of wood raw material per unit area and the total area of the country in the ratio of productive forests are becoming critical in Turkey. Turkey’s rugged terrain and factors such as human interventions, fires, deforestation for agriculture, illegal cuttings, or improper grazing reduce existing forests or cause deterioration of their structure. In the past, deforestation, as a result of human interventions in Turkey, was done by forest villagers who live in rural areas. The forest crimes depend on various socio-economic reasons and have many adverse effects on the sustainability of forest and forest existence. In developed countries, illegal interventions such as opening, grazing, cutting, occupation, use, settlement, or hunting crimes have been largely eliminated because of the absence of cadastral problems, the existence of more responsive people to protect the environment and forests and a rural population, which has a higher standard of living. In the last 20 years, there has been both a dramatic decrease in the population living in rural areas and a
Bayesian Classification of Image Structures
DEFF Research Database (Denmark)
Goswami, Dibyendu; Kalkan, Sinan; Krüger, Norbert
2009-01-01
In this paper, we describe work on Bayesian classi ers for distinguishing between homogeneous structures, textures, edges and junctions. We build semi-local classiers from hand-labeled images to distinguish between these four different kinds of structures based on the concept of intrinsic dimensi...
Bayesian Agglomerative Clustering with Coalescents
Teh, Yee Whye; Daumé III, Hal; Roy, Daniel
2009-01-01
We introduce a new Bayesian model for hierarchical clustering based on a prior over trees called Kingman's coalescent. We develop novel greedy and sequential Monte Carlo inferences which operate in a bottom-up agglomerative fashion. We show experimentally the superiority of our algorithms over others, and demonstrate our approach in document clustering and phylolinguistics.
Bayesian NL interpretation and learning
H. Zeevat
2011-01-01
Everyday natural language communication is normally successful, even though contemporary computational linguistics has shown that NL is characterised by very high degree of ambiguity and the results of stochastic methods are not good enough to explain the high success rate. Bayesian natural language
Differentiated Bayesian Conjoint Choice Designs
Z. Sándor (Zsolt); M. Wedel (Michel)
2003-01-01
textabstractPrevious conjoint choice design construction procedures have produced a single design that is administered to all subjects. This paper proposes to construct a limited set of different designs. The designs are constructed in a Bayesian fashion, taking into account prior uncertainty about
Bayesian inference for Hawkes processes
DEFF Research Database (Denmark)
Rasmussen, Jakob Gulddahl
The Hawkes process is a practically and theoretically important class of point processes, but parameter-estimation for such a process can pose various problems. In this paper we explore and compare two approaches to Bayesian inference. The first approach is based on the so-called conditional...
Bayesian stable isotope mixing models
In this paper we review recent advances in Stable Isotope Mixing Models (SIMMs) and place them into an over-arching Bayesian statistical framework which allows for several useful extensions. SIMMs are used to quantify the proportional contributions of various sources to a mixtur...
Bayesian inference for Hawkes processes
DEFF Research Database (Denmark)
Rasmussen, Jakob Gulddahl
2013-01-01
The Hawkes process is a practically and theoretically important class of point processes, but parameter-estimation for such a process can pose various problems. In this paper we explore and compare two approaches to Bayesian inference. The first approach is based on the so-called conditional...
3-D contextual Bayesian classifiers
DEFF Research Database (Denmark)
Larsen, Rasmus
In this paper we will consider extensions of a series of Bayesian 2-D contextual classification pocedures proposed by Owen (1984) Hjort & Mohn (1984) and Welch & Salter (1971) and Haslett (1985) to 3 spatial dimensions. It is evident that compared to classical pixelwise classification further...
Bayesian image restoration, using configurations
DEFF Research Database (Denmark)
Thorarinsdottir, Thordis
configurations are expressed in terms of the mean normal measure of the random set. These probabilities are used as prior probabilities in a Bayesian image restoration approach. Estimation of the remaining parameters in the model is outlined for salt and pepper noise. The inference in the model is discussed...
Bayesian image restoration, using configurations
DEFF Research Database (Denmark)
Thorarinsdottir, Thordis Linda
2006-01-01
configurations are expressed in terms of the mean normal measure of the random set. These probabilities are used as prior probabilities in a Bayesian image restoration approach. Estimation of the remaining parameters in the model is outlined for the salt and pepper noise. The inference in the model is discussed...
Bayesian Analysis of Experimental Data
Directory of Open Access Journals (Sweden)
Lalmohan Bhar
2013-10-01
Full Text Available Analysis of experimental data from Bayesian point of view has been considered. Appropriate methodology has been developed for application into designed experiments. Normal-Gamma distribution has been considered for prior distribution. Developed methodology has been applied to real experimental data taken from long term fertilizer experiments.
Topics in Bayesian statistics and maximum entropy
International Nuclear Information System (INIS)
Notions of Bayesian decision theory and maximum entropy methods are reviewed with particular emphasis on probabilistic inference and Bayesian modeling. The axiomatic approach is considered as the best justification of Bayesian analysis and maximum entropy principle applied in natural sciences. Particular emphasis is put on solving the inverse problem in digital image restoration and Bayesian modeling of neural networks. Further topics addressed briefly include language modeling, neutron scattering, multiuser detection and channel equalization in digital communications, genetic information, and Bayesian court decision-making. (author)
Ancient DNA in Greece. Problems and prospects
International Nuclear Information System (INIS)
The promise associated with early 'ancient DNA' results has not been translated into routine techniques of value to archaeologists. The reasons for this are partly technical - ancient DNA analysis is an extremely difficult technique - and partly practical - ancient DNA analysis is often an 'after thought' to an archaeological project. In this paper ancient human DNA analysis is briefly reviewed paying particular attention to specimens originating from Greek archaeological contexts. Problems commonly encountered during ancient DNA research are summarised and recommendations for future strategies in the application of ancient DNA in archaeology are proposed. (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.
Mapping The Ancient Maya Landscape From Space
Sever, Tom; Arnold, James E. (Technical Monitor)
2002-01-01
The Peten region of northern Guatemala is one of the last places on earth where major archeological sites remain to be discovered. It was in this region that the Maya civilization began, flourished, and abruptly disappeared. Remote sensing technology is helping to locate and map ancient Maya sites that are threatened today by accelerating deforestation and looting. Thematic Mapper and IKONOS satellite and airborne Star3-I radar data, combined with Global Positioning System (GPS) technology, are successfully detecting ancient Maya features such as cities, roadways, canals, and water reservoirs. Satellite imagery is also being used to map the bajos, which are seasonally flooded swamps that cover over 40% of the land surface. The use of bajos for farming has been a source of debate within the professional community for many years. But the recent detection and verification of cultural features within the bajo system by our research team are providing conclusive evidence that the ancient Maya had adapted well to wetland environments from the earliest times and utilized them until the time of the Maya collapse. The use of the bajos for farming is also an important resource for the future of the current inhabitants who are experiencing rapid population growth. Remote sensing imagery is also demonstrating that in the Preclassic period (600 BC- AD 250), the Maya had already achieved a high organizational level as evidenced by the construction of massive temples and an elaborate inter-connecting roadway system. Although they experienced several setbacks such as droughts and hurricanes, the Maya nevertheless managed the delicate forest ecosystem successfully for several centuries. However, around AD 800, something happened to the Maya to cause their rapid decline and eventual disappearance from the region. The evidence indicates that at this time there was increased climatic dryness, extensive deforestation, overpopulation, and widespread warfare. This raises a question that
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...
Clustering and Bayesian network for image of faces classification
Jayech, Khlifia
2012-01-01
In a content based image classification system, target images are sorted by feature similarities with respect to the query (CBIR). In this paper, we propose to use new approach combining distance tangent, k-means algorithm and Bayesian network for image classification. First, we use the technique of tangent distance to calculate several tangent spaces representing the same image. The objective is to reduce the error in the classification phase. Second, we cut the image in a whole of blocks. For each block, we compute a vector of descriptors. Then, we use K-means to cluster the low-level features including color and texture information to build a vector of labels for each image. Finally, we apply five variants of Bayesian networks classifiers (Na\\"ive Bayes, Global Tree Augmented Na\\"ive Bayes (GTAN), Global Forest Augmented Na\\"ive Bayes (GFAN), Tree Augmented Na\\"ive Bayes for each class (TAN), and Forest Augmented Na\\"ive Bayes for each class (FAN) to classify the image of faces using the vector of labels. ...
Night blindness and ancient remedy
Directory of Open Access Journals (Sweden)
H.A. Hajar Al Binali
2014-01-01
Full Text Available The aim of this article is to briefly review the history of night blindness and its treatment from ancient times until the present. The old Egyptians, the Babylonians, the Greeks and the Arabs used animal liver for treatment and successfully cured the disease. The author had the opportunity to observe the application of the old remedy to a patient. Now we know what the ancients did not know, that night blindness is caused by Vitamin A deficiency and the animal liver is the store house for Vitamin A.
Directory of Open Access Journals (Sweden)
Louise Cilliers
2008-09-01
Full Text Available In spite of an array of effective antibiotics, tuberculosis is still very common in developing countries where overcrowding, malnutrition and poor hygienic conditions prevail. Over the past 30 years associated HIV infection has worsened the situation by increasing the infection rate and mortality of tuberculosis. Of those diseases caused by a single organism only HIV causes more deaths internationally than tuberculosis. The tubercle bacillus probably first infected man in Neolithic times, and then via infected cattle, but the causative Mycobacteriacea have been in existence for 300 million years. Droplet infection is the most common way of acquiring tuberculosis, although ingestion (e.g. of infected cows’ milk may occur. Tuberculosis probably originated in Africa. The earliest path gnomonic evidence of human tuberculosis in man was found in osteo-archaeological findings of bone tuberculosis (Pott’s disease of the spine in the skeleton of anEgyptian priest from the 21st Dynasty (approximately 1 000 BC. Suggestive but not conclusiveevidence of tuberculotic lesions had been found in even earlier skeletons from Egypt and Europe. Medical hieroglyphics from ancient Egypt are silent on the disease, which could be tuberculosis,as do early Indian and Chinese writings. The Old Testament refers to the disease schachapeth, translated as phthisis in the Greek Septuagint. Although the Bible is not specific about this condition, tuberculosis is still called schachapeth in modern Hebrew. In pre-Hippocratic Greece Homer did not mention phthisis, a word meaning non-specific wasting of the body. However. Alexander of Tralles (6th century BC seemed to narrow the concept down to a specific disease, and in the Hippocratic Corpus (5th-4th centuries BC phthisis can be recognised as tuberculosis. It was predominantly a respiratory disease commonly seen and considered to be caused by an imbalance of bodily humours. It was commonest in autumn, winter and spring
Hierarchical Bayesian spatial models for multispecies conservation planning and monitoring.
Carroll, Carlos; Johnson, Devin S; Dunk, Jeffrey R; Zielinski, William J
2010-12-01
Biologists who develop and apply habitat models are often familiar with the statistical challenges posed by their data's spatial structure but are unsure of whether the use of complex spatial models will increase the utility of model results in planning. We compared the relative performance of nonspatial and hierarchical Bayesian spatial models for three vertebrate and invertebrate taxa of conservation concern (Church's sideband snails [Monadenia churchi], red tree voles [Arborimus longicaudus], and Pacific fishers [Martes pennanti pacifica]) that provide examples of a range of distributional extents and dispersal abilities. We used presence-absence data derived from regional monitoring programs to develop models with both landscape and site-level environmental covariates. We used Markov chain Monte Carlo algorithms and a conditional autoregressive or intrinsic conditional autoregressive model framework to fit spatial models. The fit of Bayesian spatial models was between 35 and 55% better than the fit of nonspatial analogue models. Bayesian spatial models outperformed analogous models developed with maximum entropy (Maxent) methods. Although the best spatial and nonspatial models included similar environmental variables, spatial models provided estimates of residual spatial effects that suggested how ecological processes might structure distribution patterns. Spatial models built from presence-absence data improved fit most for localized endemic species with ranges constrained by poorly known biogeographic factors and for widely distributed species suspected to be strongly affected by unmeasured environmental variables or population processes. By treating spatial effects as a variable of interest rather than a nuisance, hierarchical Bayesian spatial models, especially when they are based on a common broad-scale spatial lattice (here the national Forest Inventory and Analysis grid of 24 km(2) hexagons), can increase the relevance of habitat models to multispecies
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...
Understanding Malaria: Fighting an Ancient Scourge
Understanding Malaria Fighting an Ancient Scourge U.S. DEPARTMENT OF HEALTH AND HUMAN SERVICES National Institutes of Health National Institute of Allergy and Infectious Diseases Understanding Malaria Fighting an Ancient Scourge U.S. DEPARTMENT OF HEALTH ...
Phylogenetic estimation of timescales using ancient DNA
DEFF Research Database (Denmark)
Molak, Martyna; Lorenzen, Eline; Shapiro, Beth;
2013-01-01
In recent years, ancient DNA has increasingly been used for estimating molecular timescales, particularly in studies of substitution rates and demographic histories. Molecular clocks can be calibrated using temporal information from ancient DNA sequences. This information comes from the ages...
Bayesian versus 'plain-vanilla Bayesian' multitarget statistics
Mahler, Ronald P. S.
2004-08-01
Finite-set statistics (FISST) is a direct generalization of single-sensor, single-target Bayes statistics to the multisensor-multitarget realm, based on random set theory. Various aspects of FISST are being investigated by several research teams around the world. In recent years, however, a few partisans have claimed that a "plain-vanilla Bayesian approach" suffices as down-to-earth, "straightforward," and general "first principles" for multitarget problems. Therefore, FISST is mere mathematical "obfuscation." In this and a companion paper I demonstrate the speciousness of these claims. In this paper I summarize general Bayes statistics, what is required to use it in multisensor-multitarget problems, and why FISST is necessary to make it practical. Then I demonstrate that the "plain-vanilla Bayesian approach" is so heedlessly formulated that it is erroneous, not even Bayesian denigrates FISST concepts while unwittingly assuming them, and has resulted in a succession of algorithms afflicted by inherent -- but less than candidly acknowledged -- computational "logjams."
The eye and its diseases in Ancient Egypt
DEFF Research Database (Denmark)
Andersen, S. Ry
1997-01-01
Ophthalmology, History of ophthalmology, eyes in the Ancient Egypt, eye disease in Ancient Egypt, porotic hyperostosis, mummification......Ophthalmology, History of ophthalmology, eyes in the Ancient Egypt, eye disease in Ancient Egypt, porotic hyperostosis, mummification...
Forest Histories & Forest Futures
Whitlock, Cathy
2009-01-01
The climate changes projected for the future will have significant consequences for forest ecosystems and our ability to manage them. It is reasonable to ask: Are there historical precedents that help us understand what might happen in the future or are historical perspectives becoming irrelevant? What synergisms and feedbacks might be expected between rapidly changing climate and land–use in different settings, especially at the wildland–urban interface? What lessons from the past might help...
Institute of Scientific and Technical Information of China (English)
GE JIANXIONG
2010-01-01
@@ The famous painting,Along the River During Qingming Festival,impresses visitors at the China Pavilion not iust because of the animated figures in the electronic version of the painting but because it shows a prosperous view of Kaifeng,capital of the Northern Song Dynasty (960-1127).It also showcases the wisdom of city planning in ancient China.
Hobson, Allan
2013-12-01
Revision of Freud's theory requires a new way of seeking dream meaning. With the idea of elaborative encoding, Sue Llewellyn has provided a method of dream interpretation that takes into account both modern sleep science and the ancient art of memory. Her synthesis is elegant and compelling. But is her hypothesis testable? PMID:24304762
Zuskin, Eugenija; Lipozencić, Jasna; Pucarin-Cvetković, Jasna; Mustajbegović, Jadranka; Schachter, Neil; Mucić-Pucić, Branka; Neralić-Meniga, Inja
2008-01-01
Different aspects of medicine and/or healing in several societies are presented. In the ancient times as well as today medicine has been closely related to magic, science and religion. Various ancient societies and cultures had developed different views of medicine. It was believed that a human being has two bodies: a visible body that belongs to the earth and an invisible body of heaven. In the earliest prehistoric days, a different kind of medicine was practiced in countries such as Egypt, Greece, Rome, Mesopotamia, India, Tibet, China, and others. In those countries, "medicine people" practiced medicine from the magic to modern physical practices. Medicine was magical and mythological, and diseases were attributed mostly to the supernatural forces. The foundation of modern medicine can be traced back to ancient Greeks. Tibetan culture, for instance, even today, combines spiritual and practical medicine. Chinese medicine developed as a concept of yin and yang, acupuncture and acupressure, and it has even been used in the modern medicine. During medieval Europe, major universities and medical schools were established. In the ancient time, before hospitals had developed, patients were treated mostly in temples. PMID:18812066
Watzman, Haim
2006-01-01
Several artifacts found at the Gesher Benot Ya'aqov, or Daughters of Jacob Bridge, archaeological site in Israel provide a picture of ancient human ancestors that is different from the once accepted by most scholars. The discoveries by Israeli archaeologist Naama Goren-Inbar suggest that humans developed language and other key abilities far…
Adult Reading of Ancient Languages.
Casler, Frederick H.
Traditionally, students of ancient languages have been taught to translate rather than read. The four most popular current approaches to language instruction--the grammar-translation method, the direct-reading or inductive approach, the audiolingual method, and the structural approach--all have inherent deficiencies that are magnified when applied…
Bayesian inference on proportional elections.
Brunello, Gabriel Hideki Vatanabe; Nakano, Eduardo Yoshio
2015-01-01
Polls for majoritarian voting systems usually show estimates of the percentage of votes for each candidate. However, proportional vote systems do not necessarily guarantee the candidate with the most percentage of votes will be elected. Thus, traditional methods used in majoritarian elections cannot be applied on proportional elections. In this context, the purpose of this paper was to perform a Bayesian inference on proportional elections considering the Brazilian system of seats distribution. More specifically, a methodology to answer the probability that a given party will have representation on the chamber of deputies was developed. Inferences were made on a Bayesian scenario using the Monte Carlo simulation technique, and the developed methodology was applied on data from the Brazilian elections for Members of the Legislative Assembly and Federal Chamber of Deputies in 2010. A performance rate was also presented to evaluate the efficiency of the methodology. Calculations and simulations were carried out using the free R statistical software. PMID:25786259
Bayesian approach to rough set
Marwala, Tshilidzi
2007-01-01
This paper proposes an approach to training rough set models using Bayesian framework trained using Markov Chain Monte Carlo (MCMC) method. The prior probabilities are constructed from the prior knowledge that good rough set models have fewer rules. Markov Chain Monte Carlo sampling is conducted through sampling in the rough set granule space and Metropolis algorithm is used as an acceptance criteria. The proposed method is tested to estimate the risk of HIV given demographic data. The results obtained shows that the proposed approach is able to achieve an average accuracy of 58% with the accuracy varying up to 66%. In addition the Bayesian rough set give the probabilities of the estimated HIV status as well as the linguistic rules describing how the demographic parameters drive the risk of HIV.
Bayesian priors for transiting planets
Kipping, David M
2016-01-01
As astronomers push towards discovering ever-smaller transiting planets, it is increasingly common to deal with low signal-to-noise ratio (SNR) events, where the choice of priors plays an influential role in Bayesian inference. In the analysis of exoplanet data, the selection of priors is often treated as a nuisance, with observers typically defaulting to uninformative distributions. Such treatments miss a key strength of the Bayesian framework, especially in the low SNR regime, where even weak a priori information is valuable. When estimating the parameters of a low-SNR transit, two key pieces of information are known: (i) the planet has the correct geometric alignment to transit and (ii) the transit event exhibits sufficient signal-to-noise to have been detected. These represent two forms of observational bias. Accordingly, when fitting transits, the model parameter priors should not follow the intrinsic distributions of said terms, but rather those of both the intrinsic distributions and the observational ...
Bayesian Source Separation and Localization
Knuth, K H
1998-01-01
The problem of mixed signals occurs in many different contexts; one of the most familiar being acoustics. The forward problem in acoustics consists of finding the sound pressure levels at various detectors resulting from sound signals emanating from the active acoustic sources. The inverse problem consists of using the sound recorded by the detectors to separate the signals and recover the original source waveforms. In general, the inverse problem is unsolvable without additional information. This general problem is called source separation, and several techniques have been developed that utilize maximum entropy, minimum mutual information, and maximum likelihood. In previous work, it has been demonstrated that these techniques can be recast in a Bayesian framework. This paper demonstrates the power of the Bayesian approach, which provides a natural means for incorporating prior information into a source model. An algorithm is developed that utilizes information regarding both the statistics of the amplitudes...
Bayesian Inference for Radio Observations
Lochner, Michelle; Zwart, Jonathan T L; Smirnov, Oleg; Bassett, Bruce A; Oozeer, Nadeem; Kunz, Martin
2015-01-01
(Abridged) New telescopes like the Square Kilometre Array (SKA) will push into a new sensitivity regime and expose systematics, such as direction-dependent effects, that could previously be ignored. Current methods for handling such systematics rely on alternating best estimates of instrumental calibration and models of the underlying sky, which can lead to inaccurate uncertainty estimates and biased results because such methods ignore any correlations between parameters. These deconvolution algorithms produce a single image that is assumed to be a true representation of the sky, when in fact it is just one realisation of an infinite ensemble of images compatible with the noise in the data. In contrast, here we report a Bayesian formalism that simultaneously infers both systematics and science. Our technique, Bayesian Inference for Radio Observations (BIRO), determines all parameters directly from the raw data, bypassing image-making entirely, by sampling from the joint posterior probability distribution. Thi...
Directory of Open Access Journals (Sweden)
Dongsheng Chen
2016-01-01
Full Text Available Accurate biomass estimations are important for assessing and monitoring forest carbon storage. Bayesian theory has been widely applied to tree biomass models. Recently, a hierarchical Bayesian approach has received increasing attention for improving biomass models. In this study, tree biomass data were obtained by sampling 310 trees from 209 permanent sample plots from larch plantations in six regions across China. Non-hierarchical and hierarchical Bayesian approaches were used to model allometric biomass equations. We found that the total, root, stem wood, stem bark, branch and foliage biomass model relationships were statistically significant (p-values < 0.001 for both the non-hierarchical and hierarchical Bayesian approaches, but the hierarchical Bayesian approach increased the goodness-of-fit statistics over the non-hierarchical Bayesian approach. The R2 values of the hierarchical approach were higher than those of the non-hierarchical approach by 0.008, 0.018, 0.020, 0.003, 0.088 and 0.116 for the total tree, root, stem wood, stem bark, branch and foliage models, respectively. The hierarchical Bayesian approach significantly improved the accuracy of the biomass model (except for the stem bark and can reflect regional differences by using random parameters to improve the regional scale model accuracy.
DEFF Research Database (Denmark)
Balooni, Kulbhushan; Lund, Jens Friis
2014-01-01
One of the proposed strategies for implementation of reducing emissions from deforestation and forest degradation plus (REDD+) is to incentivize conservation of forests managed by communities under decentralized forest management. Yet, we argue that this is a challenging road to REDD+ because...... of three general characteristics of forests under existing decentralized management regimes. First, these forests already accumulate biomass and, in some cases, generate leakage, which threatens to undercut REDD+ additionality. Second, these forests are many and small, which will drive up REDD......+ transactions costs. Third, beyond the “conservation islands” represented by forests under decentralized management, processes of deforestation and forest degradation continue. Given these challenges, we argue that REDD+ efforts through decentralized forestry should be redirected from incentivizing further...
A Bayesian Nonparametric IRT Model
Karabatsos, George
2015-01-01
This paper introduces a flexible Bayesian nonparametric Item Response Theory (IRT) model, which applies to dichotomous or polytomous item responses, and which can apply to either unidimensional or multidimensional scaling. This is an infinite-mixture IRT model, with person ability and item difficulty parameters, and with a random intercept parameter that is assigned a mixing distribution, with mixing weights a probit function of other person and item parameters. As a result of its flexibility...
Elements of Bayesian experimental design
Energy Technology Data Exchange (ETDEWEB)
Sivia, D.S. [Rutherford Appleton Lab., Oxon (United Kingdom)
1997-09-01
We consider some elements of the Bayesian approach that are important for optimal experimental design. While the underlying principles used are very general, and are explained in detail in a recent tutorial text, they are applied here to the specific case of characterising the inferential value of different resolution peakshapes. This particular issue was considered earlier by Silver, Sivia and Pynn (1989, 1990a, 1990b), and the following presentation confirms and extends the conclusions of their analysis.
Bayesian kinematic earthquake source models
Minson, S. E.; Simons, M.; Beck, J. L.; Genrich, J. F.; Galetzka, J. E.; Chowdhury, F.; Owen, S. E.; Webb, F.; Comte, D.; Glass, B.; Leiva, C.; Ortega, F. H.
2009-12-01
Most coseismic, postseismic, and interseismic slip models are based on highly regularized optimizations which yield one solution which satisfies the data given a particular set of regularizing constraints. This regularization hampers our ability to answer basic questions such as whether seismic and aseismic slip overlap or instead rupture separate portions of the fault zone. We present a Bayesian methodology for generating kinematic earthquake source models with a focus on large subduction zone earthquakes. Unlike classical optimization approaches, Bayesian techniques sample the ensemble of all acceptable models presented as an a posteriori probability density function (PDF), and thus we can explore the entire solution space to determine, for example, which model parameters are well determined and which are not, or what is the likelihood that two slip distributions overlap in space. Bayesian sampling also has the advantage that all a priori knowledge of the source process can be used to mold the a posteriori ensemble of models. Although very powerful, Bayesian methods have up to now been of limited use in geophysical modeling because they are only computationally feasible for problems with a small number of free parameters due to what is called the "curse of dimensionality." However, our methodology can successfully sample solution spaces of many hundreds of parameters, which is sufficient to produce finite fault kinematic earthquake models. Our algorithm is a modification of the tempered Markov chain Monte Carlo (tempered MCMC or TMCMC) method. In our algorithm, we sample a "tempered" a posteriori PDF using many MCMC simulations running in parallel and evolutionary computation in which models which fit the data poorly are preferentially eliminated in favor of models which better predict the data. We present results for both synthetic test problems as well as for the 2007 Mw 7.8 Tocopilla, Chile earthquake, the latter of which is constrained by InSAR, local high
Bayesian Stable Isotope Mixing Models
Parnell, Andrew C.; Phillips, Donald L.; Bearhop, Stuart; Semmens, Brice X.; Ward, Eric J.; Moore, Jonathan W.; Andrew L Jackson; Inger, Richard
2012-01-01
In this paper we review recent advances in Stable Isotope Mixing Models (SIMMs) and place them into an over-arching Bayesian statistical framework which allows for several useful extensions. SIMMs are used to quantify the proportional contributions of various sources to a mixture. The most widely used application is quantifying the diet of organisms based on the food sources they have been observed to consume. At the centre of the multivariate statistical model we propose is a compositional m...
Bayesian Network--Response Regression
WANG, LU; Durante, Daniele; Dunson, David B.
2016-01-01
There is an increasing interest in learning how human brain networks vary with continuous traits (e.g., personality, cognitive abilities, neurological disorders), but flexible procedures to accomplish this goal are limited. We develop a Bayesian semiparametric model, which combines low-rank factorizations and Gaussian process priors to allow flexible shifts of the conditional expectation for a network-valued random variable across the feature space, while including subject-specific random eff...
Bayesian segmentation of hyperspectral images
Mohammadpour, Adel; Mohammad-Djafari, Ali
2007-01-01
In this paper we consider the problem of joint segmentation of hyperspectral images in the Bayesian framework. The proposed approach is based on a Hidden Markov Modeling (HMM) of the images with common segmentation, or equivalently with common hidden classification label variables which is modeled by a Potts Markov Random Field. We introduce an appropriate Markov Chain Monte Carlo (MCMC) algorithm to implement the method and show some simulation results.
Bayesian segmentation of hyperspectral images
Mohammadpour, Adel; Féron, Olivier; Mohammad-Djafari, Ali
2004-11-01
In this paper we consider the problem of joint segmentation of hyperspectral images in the Bayesian framework. The proposed approach is based on a Hidden Markov Modeling (HMM) of the images with common segmentation, or equivalently with common hidden classification label variables which is modeled by a Potts Markov Random Field. We introduce an appropriate Markov Chain Monte Carlo (MCMC) algorithm to implement the method and show some simulation results.
Bayesian analysis of contingency tables
Gómez Villegas, Miguel A.; González Pérez, Beatriz
2005-01-01
The display of the data by means of contingency tables is used in different approaches to statistical inference, for example, to broach the test of homogeneity of independent multinomial distributions. We develop a Bayesian procedure to test simple null hypotheses versus bilateral alternatives in contingency tables. Given independent samples of two binomial distributions and taking a mixed prior distribution, we calculate the posterior probability that the proportion of successes in the first...
Bayesian estimation of turbulent motion
Héas, P.; Herzet, C.; Mémin, E.; Heitz, D.; P. D. Mininni
2013-01-01
International audience Based on physical laws describing the multi-scale structure of turbulent flows, this article proposes a regularizer for fluid motion estimation from an image sequence. Regularization is achieved by imposing some scale invariance property between histograms of motion increments computed at different scales. By reformulating this problem from a Bayesian perspective, an algorithm is proposed to jointly estimate motion, regularization hyper-parameters, and to select the ...
Bayesian Kernel Mixtures for Counts
Canale, Antonio; David B Dunson
2011-01-01
Although Bayesian nonparametric mixture models for continuous data are well developed, there is a limited literature on related approaches for count data. A common strategy is to use a mixture of Poissons, which unfortunately is quite restrictive in not accounting for distributions having variance less than the mean. Other approaches include mixing multinomials, which requires finite support, and using a Dirichlet process prior with a Poisson base measure, which does not allow smooth deviatio...
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
Bayesian second law of thermodynamics.
Bartolotta, Anthony; Carroll, Sean M; Leichenauer, Stefan; Pollack, Jason
2016-08-01
We derive a generalization of the second law of thermodynamics that uses Bayesian updates to explicitly incorporate the effects of a measurement of a system at some point in its evolution. By allowing an experimenter's knowledge to be updated by the measurement process, this formulation resolves a tension between the fact that the entropy of a statistical system can sometimes fluctuate downward and the information-theoretic idea that knowledge of a stochastically evolving system degrades over time. The Bayesian second law can be written as ΔH(ρ_{m},ρ)+〈Q〉_{F|m}≥0, where ΔH(ρ_{m},ρ) is the change in the cross entropy between the original phase-space probability distribution ρ and the measurement-updated distribution ρ_{m} and 〈Q〉_{F|m} is the expectation value of a generalized heat flow out of the system. We also derive refined versions of the second law that bound the entropy increase from below by a non-negative number, as well as Bayesian versions of integral fluctuation theorems. We demonstrate the formalism using simple analytical and numerical examples. PMID:27627241
Bayesian second law of thermodynamics
Bartolotta, Anthony; Carroll, Sean M.; Leichenauer, Stefan; Pollack, Jason
2016-08-01
We derive a generalization of the second law of thermodynamics that uses Bayesian updates to explicitly incorporate the effects of a measurement of a system at some point in its evolution. By allowing an experimenter's knowledge to be updated by the measurement process, this formulation resolves a tension between the fact that the entropy of a statistical system can sometimes fluctuate downward and the information-theoretic idea that knowledge of a stochastically evolving system degrades over time. The Bayesian second law can be written as Δ H (ρm,ρ ) + F |m≥0 , where Δ H (ρm,ρ ) is the change in the cross entropy between the original phase-space probability distribution ρ and the measurement-updated distribution ρm and F |m is the expectation value of a generalized heat flow out of the system. We also derive refined versions of the second law that bound the entropy increase from below by a non-negative number, as well as Bayesian versions of integral fluctuation theorems. We demonstrate the formalism using simple analytical and numerical examples.
Energy Technology Data Exchange (ETDEWEB)
None
2016-06-01
Forest biomass is an abundant biomass feedstock that complements the conventional forest use of wood for paper and wood materials. It may be utilized for bioenergy production, such as heat and electricity, as well as for biofuels and a variety of bioproducts, such as industrial chemicals, textiles, and other renewable materials. The resources within the 2016 Billion-Ton Report include primary forest resources, which are taken directly from timberland-only forests, removed from the land, and taken to the roadside.
Chen, Han Y H; Luo, Yong
2015-10-01
Biomass change of the world's forests is critical to the global carbon cycle. Despite storing nearly half of global forest carbon, the boreal biome of diverse forest types and ages is a poorly understood component of the carbon cycle. Using data from 871 permanent plots in the western boreal forest of Canada, we examined net annual aboveground biomass change (ΔAGB) of four major forest types between 1958 and 2011. We found that ΔAGB was higher for deciduous broadleaf (DEC) (1.44 Mg ha(-1) year(-1) , 95% Bayesian confidence interval (CI), 1.22-1.68) and early-successional coniferous forests (ESC) (1.42, CI, 1.30-1.56) than mixed forests (MIX) (0.80, CI, 0.50-1.11) and late-successional coniferous (LSC) forests (0.62, CI, 0.39-0.88). ΔAGB declined with forest age as well as calendar year. After accounting for the effects of forest age, ΔAGB declined by 0.035, 0.021, 0.032 and 0.069 Mg ha(-1) year(-1) per calendar year in DEC, ESC, MIX and LSC forests, respectively. The ΔAGB declines resulted from increased tree mortality and reduced growth in all forest types except DEC, in which a large biomass loss from mortality was accompanied with a small increase in growth. With every degree of annual temperature increase, ΔAGB decreased by 1.00, 0.20, 0.55 and 1.07 Mg ha(-1) year(-1) in DEC, ESC, MIX and LSC forests, respectively. With every cm decrease of annual climatic moisture availability, ΔAGB decreased 0.030, 0.045 and 0.17 Mg ha(-1) year(-1) in ESC, MIX and LSC forests, but changed little in DEC forests. Our results suggest that persistent warming and decreasing water availability have profound negative effects on forest biomass in the boreal forests of western Canada. Furthermore, our results indicate that forest responses to climate change are strongly dependent on forest composition with late-successional coniferous forests being most vulnerable to climate changes in terms of aboveground biomass.
12th Brazilian Meeting on Bayesian Statistics
Louzada, Francisco; Rifo, Laura; Stern, Julio; Lauretto, Marcelo
2015-01-01
Through refereed papers, this volume focuses on the foundations of the Bayesian paradigm; their comparison to objectivistic or frequentist Statistics counterparts; and the appropriate application of Bayesian foundations. This research in Bayesian Statistics is applicable to data analysis in biostatistics, clinical trials, law, engineering, and the social sciences. EBEB, the Brazilian Meeting on Bayesian Statistics, is held every two years by the ISBrA, the International Society for Bayesian Analysis, one of the most active chapters of the ISBA. The 12th meeting took place March 10-14, 2014 in Atibaia. Interest in foundations of inductive Statistics has grown recently in accordance with the increasing availability of Bayesian methodological alternatives. Scientists need to deal with the ever more difficult choice of the optimal method to apply to their problem. This volume shows how Bayes can be the answer. The examination and discussion on the foundations work towards the goal of proper application of Bayesia...
Compiling Relational Bayesian Networks for Exact Inference
DEFF Research Database (Denmark)
Jaeger, Manfred; Chavira, Mark; Darwiche, Adnan
2004-01-01
We describe a system for exact inference with relational Bayesian networks as defined in the publicly available \\primula\\ tool. The system is based on compiling propositional instances of relational Bayesian networks into arithmetic circuits and then performing online inference by evaluating...... and differentiating these circuits in time linear in their size. We report on experimental results showing the successful compilation, and efficient inference, on relational Bayesian networks whose {\\primula}--generated propositional instances have thousands of variables, and whose jointrees have clusters...
Bayesian Posterior Distributions Without Markov Chains
Cole, Stephen R.; Chu, Haitao; Greenland, Sander; Hamra, Ghassan; Richardson, David B.
2012-01-01
Bayesian posterior parameter distributions are often simulated using Markov chain Monte Carlo (MCMC) methods. However, MCMC methods are not always necessary and do not help the uninitiated understand Bayesian inference. As a bridge to understanding Bayesian inference, the authors illustrate a transparent rejection sampling method. In example 1, they illustrate rejection sampling using 36 cases and 198 controls from a case-control study (1976–1983) assessing the relation between residential ex...
Variational bayesian method of estimating variance components.
Arakawa, Aisaku; Taniguchi, Masaaki; Hayashi, Takeshi; Mikawa, Satoshi
2016-07-01
We developed a Bayesian analysis approach by using a variational inference method, a so-called variational Bayesian method, to determine the posterior distributions of variance components. This variational Bayesian method and an alternative Bayesian method using Gibbs sampling were compared in estimating genetic and residual variance components from both simulated data and publically available real pig data. In the simulated data set, we observed strong bias toward overestimation of genetic variance for the variational Bayesian method in the case of low heritability and low population size, and less bias was detected with larger population sizes in both methods examined. The differences in the estimates of variance components between the variational Bayesian and the Gibbs sampling were not found in the real pig data. However, the posterior distributions of the variance components obtained with the variational Bayesian method had shorter tails than those obtained with the Gibbs sampling. Consequently, the posterior standard deviations of the genetic and residual variances of the variational Bayesian method were lower than those of the method using Gibbs sampling. The computing time required was much shorter with the variational Bayesian method than with the method using Gibbs sampling.
SYNTHESIZED EXPECTED BAYESIAN METHOD OF PARAMETRIC ESTIMATE
Institute of Scientific and Technical Information of China (English)
Ming HAN; Yuanyao DING
2004-01-01
This paper develops a new method of parametric estimate, which is named as "synthesized expected Bayesian method". When samples of products are tested and no failure events occur, thedefinition of expected Bayesian estimate is introduced and the estimates of failure probability and failure rate are provided. After some failure information is introduced by making an extra-test, a synthesized expected Bayesian method is defined and used to estimate failure probability, failure rateand some other parameters in exponential distribution and Weibull distribution of populations. Finally,calculations are performed according to practical problems, which show that the synthesized expected Bayesian method is feasible and easy to operate.
Bruel, Per V.
2002-11-01
Models were made of vases described by Vitruvius in Rome in about the year 70 A.D. and of sound vases (lydpotter) placed in Danish churches from 1100-1300 A.D. Measurements of vase's resonant frequencies and damping (reradiation) verified that the model vases obeyed expected physical rules. It was concluded that the excellent acoustical quality of many ancient Greek and Roman theaters cannot be ascribed to the vases placed under their seats. This study also found that sound vases placed in Nordic churches could not have shortened the reverberation time because there are far too few of them. Moreover, they could not have covered a broad frequency range. It remains a mystery why vases were installed under the seats of ancient Greek theaters and why, 1000 years later, Danes placed vases in their churches.
Mitogenomic analyses from ancient DNA
DEFF Research Database (Denmark)
Paijmans, Johanna L.A.; Gilbert, M Thomas P; Hofreiter, Michael
2013-01-01
analyses (whether using modern or ancient DNA) were largely restricted to the analysis of short fragments of the mitochondrial genome. However, due to many technological advances during the past decade, a growing number of studies have explored the power of complete mitochondrial genome sequences...... (mitogenomes). Such studies were initially limited to analyses of extant organisms, but developments in both DNA sequencing technologies and general methodological aspects related to working with degraded DNA have resulted in complete mitogenomes becoming increasingly popular for ancient DNA studies as well....... To date, at least 124 partially or fully assembled mitogenomes from more than 20 species have been obtained, and, given the rapid progress in sequencing technology, this number is likely to dramatically increase in the future. The increased information content offered by analysing full mitogenomes has...
Molecular analysis of ancient caries.
Simón, Marc; Montiel, Rafael; Smerling, Andrea; Solórzano, Eduvigis; Díaz, Nancy; Álvarez-Sandoval, Brenda A; Jiménez-Marín, Andrea R; Malgosa, Assumpció
2014-09-01
An 84 base pair sequence of the Streptococcus mutans virulence factor, known as dextranase, has been obtained from 10 individuals from the Bronze Age to the Modern Era in Europe and from before and after the colonization in America. Modern samples show four polymorphic sites that have not been found in the ancient samples studied so far. The nucleotide and haplotype diversity of this region have increased over time, which could be reflecting the footprint of a population expansion. While this segment has apparently evolved according to neutral evolution, we have been able to detect one site that is under positive selection pressure both in present and past populations. This study is a first step to study the evolution of this microorganism, analysed using direct evidence obtained from ancient remains.
ANCIENT BREAD STAMPS FROM JORDAN
Kakish, Randa
2014-01-01
Marking bread was an old practice performed in different parts of the old world. It was done for religious, magical, economic and identification purposes. Bread stamps differ from other groups of stamps. Accordingly, the aim of this article is to identify such stamps, displayed or stored, in a number of Jordanian Archaeological Museums. A col-lection of twelve ancient bread stamps were identified and studied. Two of the stamps were of unknown provenance while the others came from al-Shuneh, D...
Ancient Technology in Contemporary Surgery
Buck, Bruce A.
1982-01-01
Archaeologists have shown that ancient man developed the ability to produce cutting blades of an extreme degree of sharpness from volcanic glass. The finest of these prismatic blades were produced in Mesoamerica about 2,500 years ago. The technique of production of these blades was rediscovered 12 years ago by Dr. Don Crabtree, who suggested possible uses for the blades in modern surgery. Blades produced by Dr. Crabtree have been used in experimental microsurgery with excellent results. Anima...
Splendid Arts Fram Ancient Capitals
Institute of Scientific and Technical Information of China (English)
1998-01-01
IT was in the golden autumn in Beijing, when the sky was high and the air clear, that I hurried to Zhongshan Park to witness the display of the songs and dances of the seven Chinese ancient capitals. The flower beds arranged for the celebration of National Day were still there and the colorful blooms looked especially bright in the sunshine. The seven cities which have served as capitals in Chinese history are Beijing,
Psychiatric Thoughts in Ancient India
Directory of Open Access Journals (Sweden)
Ravi Abhyankar
2015-01-01
Full Text Available A review of the literature regarding psychiatric thoughts in ancient India is attempted. Besides interesting reading, many of the concepts are still relevant and can be used in day-to-day practice especially towards healthy and happy living. Certain concepts are surprisingly contemporary and valid today. They can be used in psychotherapy and counselling and for promoting mental health. However, the description and classification of mental illness is not in tune with modern psychiatry.
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 phylogeography finds its roots.
Directory of Open Access Journals (Sweden)
Philippe Lemey
2009-09-01
Full Text Available As a key factor in endemic and epidemic dynamics, the geographical distribution of viruses has been frequently interpreted in the light of their genetic histories. Unfortunately, inference of historical dispersal or migration patterns of viruses has mainly been restricted to model-free heuristic approaches that provide little insight into the temporal setting of the spatial dynamics. The introduction of probabilistic models of evolution, however, offers unique opportunities to engage in this statistical endeavor. Here we introduce a Bayesian framework for inference, visualization and hypothesis testing of phylogeographic history. By implementing character mapping in a Bayesian software that samples time-scaled phylogenies, we enable the reconstruction of timed viral dispersal patterns while accommodating phylogenetic uncertainty. Standard Markov model inference is extended with a stochastic search variable selection procedure that identifies the parsimonious descriptions of the diffusion process. In addition, we propose priors that can incorporate geographical sampling distributions or characterize alternative hypotheses about the spatial dynamics. To visualize the spatial and temporal information, we summarize inferences using virtual globe software. We describe how Bayesian phylogeography compares with previous parsimony analysis in the investigation of the influenza A H5N1 origin and H5N1 epidemiological linkage among sampling localities. Analysis of rabies in West African dog populations reveals how virus diffusion may enable endemic maintenance through continuous epidemic cycles. From these analyses, we conclude that our phylogeographic framework will make an important asset in molecular epidemiology that can be easily generalized to infer biogeogeography from genetic data for many organisms.
Numeracy, frequency, and Bayesian reasoning
Directory of Open Access Journals (Sweden)
Gretchen B. Chapman
2009-02-01
Full Text Available Previous research has demonstrated that Bayesian reasoning performance is improved if uncertainty information is presented as natural frequencies rather than single-event probabilities. A questionnaire study of 342 college students replicated this effect but also found that the performance-boosting benefits of the natural frequency presentation occurred primarily for participants who scored high in numeracy. This finding suggests that even comprehension and manipulation of natural frequencies requires a certain threshold of numeracy abilities, and that the beneficial effects of natural frequency presentation may not be as general as previously believed.
Bayesian Query-Focused Summarization
Daumé, Hal
2009-01-01
We present BayeSum (for ``Bayesian summarization''), a model for sentence extraction in query-focused summarization. BayeSum leverages the common case in which multiple documents are relevant to a single query. Using these documents as reinforcement for query terms, BayeSum is not afflicted by the paucity of information in short queries. We show that approximate inference in BayeSum is possible on large data sets and results in a state-of-the-art summarization system. Furthermore, we show how BayeSum can be understood as a justified query expansion technique in the language modeling for IR framework.
Bayesian Sampling using Condition Indicators
DEFF Research Database (Denmark)
Faber, Michael H.; Sørensen, John Dalsgaard
2002-01-01
The problem of control quality of components is considered for the special case where the acceptable failure rate is low, the test costs are high and where it may be difficult or impossible to test the condition of interest directly. Based on the classical control theory and the concept...... of condition indicators introduced by Benjamin and Cornell (1970) a Bayesian approach to quality control is formulated. The formulation is then extended to the case where the quality control is based on sampling of indirect information about the condition of the components, i.e. condition indicators...
Analysis of Ancient DNA in Microbial Ecology.
Gorgé, Olivier; Bennett, E Andrew; Massilani, Diyendo; Daligault, Julien; Pruvost, Melanie; Geigl, Eva-Maria; Grange, Thierry
2016-01-01
The development of next-generation sequencing has led to a breakthrough in the analysis of ancient genomes, and the subsequent genomic analyses of the skeletal remains of ancient humans have revolutionized the knowledge of the evolution of our species, including the discovery of a new hominin, and demonstrated admixtures with more distantly related archaic populations such as Neandertals and Denisovans. Moreover, it has also yielded novel insights into the evolution of ancient pathogens. The analysis of ancient microbial genomes allows the study of their recent evolution, presently over the last several millennia. These spectacular results have been attained despite the degradation of DNA after the death of the host, which results in very short DNA molecules that become increasingly damaged, only low quantities of which remain. The low quantity of ancient DNA molecules renders their analysis difficult and prone to contamination with modern DNA molecules, in particular via contamination from the reagents used in DNA purification and downstream analysis steps. Finally, the rare ancient molecules are diluted in environmental DNA originating from the soil microorganisms that colonize bones and teeth. Thus, ancient skeletal remains can share DNA profiles with environmental samples and identifying ancient microbial genomes among the more recent, presently poorly characterized, environmental microbiome is particularly challenging. Here, we describe the methods developed and/or in use in our laboratory to produce reliable and reproducible paleogenomic results from ancient skeletal remains that can be used to identify the presence of ancient microbiota. PMID:26791510
Planning Forest Opening with Forest Roads
Krč, Janez; Beguš, Jurij
2013-01-01
The article presents the model for determining inaccessible forest areas by density of forest roads. The model is based on the GIS analysis of the distances between the existing network of public and forest roads and inaccessible forest areas, sizes of excluded forest areas, and forest site potentials. In order to increase forest road density, the following must be done: (1) construct connecting roads to the inaccessible forest areas and (2) construct new forest roads with different density i...
Yarmohammadi, Hassan; Zargaran, Arman; Vatanpour, Azadeh; Abedini, Ehsan; Adhami, Siamak
2013-01-01
Since the dawn of medicine, medical rights and ethics have always been one of mankind's concerns. In any civilisation, attention paid to medical laws and ethics depends on the progress of human values and the advancement of medical science. The history of various civilisations teaches that each had its own views on medical ethics, but most had something in common. Ancient civilisations such as Greece, Rome, or Assyria did not consider the foetus to be alive and therefore to have human rights. In contrast, ancient Persians valued the foetus as a living person equal to others. Accordingly, they brought laws against abortion, even in cases of sexual abuse. Furthermore, abortion was considered to be a murder and punishments were meted out to the mother, father, and the person performing it. PMID:24304111
Using Bayesian Networks to Improve Knowledge Assessment
Millan, Eva; Descalco, Luis; Castillo, Gladys; Oliveira, Paula; Diogo, Sandra
2013-01-01
In this paper, we describe the integration and evaluation of an existing generic Bayesian student model (GBSM) into an existing computerized testing system within the Mathematics Education Project (PmatE--Projecto Matematica Ensino) of the University of Aveiro. This generic Bayesian student model had been previously evaluated with simulated…
Bayesian analysis of exoplanet and binary orbits
Schulze-Hartung, Tim; Launhardt, Ralf; Henning, Thomas
2012-01-01
We introduce BASE (Bayesian astrometric and spectroscopic exoplanet detection and characterisation tool), a novel program for the combined or separate Bayesian analysis of astrometric and radial-velocity measurements of potential exoplanet hosts and binary stars. The capabilities of BASE are demonstrated using all publicly available data of the binary Mizar A.
Bayesian credible interval construction for Poisson statistics
Institute of Scientific and Technical Information of China (English)
ZHU Yong-Sheng
2008-01-01
The construction of the Bayesian credible (confidence) interval for a Poisson observable including both the signal and background with and without systematic uncertainties is presented.Introducing the conditional probability satisfying the requirement of the background not larger than the observed events to construct the Bayesian credible interval is also discussed.A Fortran routine,BPOCI,has been developed to implement the calculation.
Modeling Diagnostic Assessments with Bayesian Networks
Almond, Russell G.; DiBello, Louis V.; Moulder, Brad; Zapata-Rivera, Juan-Diego
2007-01-01
This paper defines Bayesian network models and examines their applications to IRT-based cognitive diagnostic modeling. These models are especially suited to building inference engines designed to be synchronous with the finer grained student models that arise in skills diagnostic assessment. Aspects of the theory and use of Bayesian network models…
Advances in Bayesian Modeling in Educational Research
Levy, Roy
2016-01-01
In this article, I provide a conceptually oriented overview of Bayesian approaches to statistical inference and contrast them with frequentist approaches that currently dominate conventional practice in educational research. The features and advantages of Bayesian approaches are illustrated with examples spanning several statistical modeling…
Learning dynamic Bayesian networks with mixed variables
DEFF Research Database (Denmark)
Bøttcher, Susanne Gammelgaard
This paper considers dynamic Bayesian networks for discrete and continuous variables. We only treat the case, where the distribution of the variables is conditional Gaussian. We show how to learn the parameters and structure of a dynamic Bayesian network and also how the Markov order can be learned...
The Bayesian Revolution Approaches Psychological Development
Shultz, Thomas R.
2007-01-01
This commentary reviews five articles that apply Bayesian ideas to psychological development, some with psychology experiments, some with computational modeling, and some with both experiments and modeling. The reviewed work extends the current Bayesian revolution into tasks often studied in children, such as causal learning and word learning, and…
Bayesian Network for multiple hypthesis tracking
W.P. Zajdel; B.J.A. Kröse
2002-01-01
For a flexible camera-to-camera tracking of multiple objects we model the objects behavior with a Bayesian network and combine it with the multiple hypohesis framework that associates observations with objects. Bayesian networks offer a possibility to factor complex, joint distributions into a produ
Water and sustainable land use at the ancient tropical city of Tikal, Guatemala.
Scarborough, Vernon L; Dunning, Nicholas P; Tankersley, Kenneth B; Carr, Christopher; Weaver, Eric; Grazioso, Liwy; Lane, Brian; Jones, John G; Buttles, Palma; Valdez, Fred; Lentz, David L
2012-07-31
The access to water and the engineered landscapes accommodating its collection and allocation are pivotal issues for assessing sustainability. Recent mapping, sediment coring, and formal excavation at Tikal, Guatemala, have markedly expanded our understanding of ancient Maya water and land use. Among the landscape and engineering feats identified are the largest ancient dam identified in the Maya area of Central America; the posited manner by which reservoir waters were released; construction of a cofferdam for dredging the largest reservoir at Tikal; the presence of ancient springs linked to the initial colonization of Tikal; the use of sand filtration to cleanse water entering reservoirs; a switching station that facilitated seasonal filling and release; and the deepest rock-cut canal segment in the Maya Lowlands. These engineering achievements were integrated into a system that sustained the urban complex through deep time, and they have implications for sustainable construction and use of water management systems in tropical forest settings worldwide. PMID:22802627
2nd Bayesian Young Statisticians Meeting
Bitto, Angela; Kastner, Gregor; Posekany, Alexandra
2015-01-01
The Second Bayesian Young Statisticians Meeting (BAYSM 2014) and the research presented here facilitate connections among researchers using Bayesian Statistics by providing a forum for the development and exchange of ideas. WU Vienna University of Business and Economics hosted BAYSM 2014 from September 18th to 19th. The guidance of renowned plenary lecturers and senior discussants is a critical part of the meeting and this volume, which follows publication of contributions from BAYSM 2013. The meeting's scientific program reflected the variety of fields in which Bayesian methods are currently employed or could be introduced in the future. Three brilliant keynote lectures by Chris Holmes (University of Oxford), Christian Robert (Université Paris-Dauphine), and Mike West (Duke University), were complemented by 24 plenary talks covering the major topics Dynamic Models, Applications, Bayesian Nonparametrics, Biostatistics, Bayesian Methods in Economics, and Models and Methods, as well as a lively poster session ...
BAYESIAN BICLUSTERING FOR PATIENT STRATIFICATION.
Khakabimamaghani, Sahand; Ester, Martin
2016-01-01
The move from Empirical Medicine towards Personalized Medicine has attracted attention to Stratified Medicine (SM). Some methods are provided in the literature for patient stratification, which is the central task of SM, however, there are still significant open issues. First, it is still unclear if integrating different datatypes will help in detecting disease subtypes more accurately, and, if not, which datatype(s) are most useful for this task. Second, it is not clear how we can compare different methods of patient stratification. Third, as most of the proposed stratification methods are deterministic, there is a need for investigating the potential benefits of applying probabilistic methods. To address these issues, we introduce a novel integrative Bayesian biclustering method, called B2PS, for patient stratification and propose methods for evaluating the results. Our experimental results demonstrate the superiority of B2PS over a popular state-of-the-art method and the benefits of Bayesian approaches. Our results agree with the intuition that transcriptomic data forms a better basis for patient stratification than genomic data.
BAYESIAN BICLUSTERING FOR PATIENT STRATIFICATION.
Khakabimamaghani, Sahand; Ester, Martin
2016-01-01
The move from Empirical Medicine towards Personalized Medicine has attracted attention to Stratified Medicine (SM). Some methods are provided in the literature for patient stratification, which is the central task of SM, however, there are still significant open issues. First, it is still unclear if integrating different datatypes will help in detecting disease subtypes more accurately, and, if not, which datatype(s) are most useful for this task. Second, it is not clear how we can compare different methods of patient stratification. Third, as most of the proposed stratification methods are deterministic, there is a need for investigating the potential benefits of applying probabilistic methods. To address these issues, we introduce a novel integrative Bayesian biclustering method, called B2PS, for patient stratification and propose methods for evaluating the results. Our experimental results demonstrate the superiority of B2PS over a popular state-of-the-art method and the benefits of Bayesian approaches. Our results agree with the intuition that transcriptomic data forms a better basis for patient stratification than genomic data. PMID:26776199
Institute of Scientific and Technical Information of China (English)
SHENXian-sheng; LIShu-mei; YANGJie-pin; SUNHao
2004-01-01
A large number of plant remains were discovered in the ancient-woods layer of Zhujiajian Island, Zhejiang Province.There were some thick trunks, complete laminas, fruit, seeds and so on. According to radiocarbon tests conducted for plant remains, the ancient-woods layer has been dated back to about 8750 - 6200 years, and the vegetation was a subtropical evergreen and deciduous broad-leaved mixed forests on the island in the past. In the middle of the ancient-woods layer, two grains of wild rice were explored accidentally, which are Oryza rufipogon, along with the fruit and seeds of some water plants, such as Ceratophyllum dcmcrsum, C.oryzetoum, Euryale fetox, Trapa incisa var. quadricaudata , Scirpus yagara and so on. There might be marshy soil and a pond in ancient forest vegetation from where the grains of wild rice and hydrophytic fruit were found. It is of tremendous importance to study the origin of wild rice in China.
Institute of Scientific and Technical Information of China (English)
SHEN Xian-sheng; LI Shu-mei; YANG Jie-pin; SUN Hao
2004-01-01
A large number of plant remains were discovered in the ancient-woods layer of Zhujiajian Island, Zhejiang Province.There were some thick trunks, complete laminas, fruit, seeds and so on. According to radiocarbon tests conducted for plant remains, the ancient-woods layer has been dated back to about 8750 - 6200 years, and the vegetation was a subtropical evergreen and deciduous broad-leaved mixed forests on the island in the past. In the middle of the ancient-woods layer, two grains of wild rice were explored accidentally, which are Oryza rufipogon, along with the fruit and seeds of some water plants, such as Ceratophyllum demersum, C. oryzetorum, Euryale ferox, Trapa incisa var. quadricaudata , Scirpus yagara and so on. There might be marshy soil and a pond in ancient forest vegetation from where the grains of wild rice and hydrophytic fruit were found. It is of tremendous importance to study the origin of wild rice in China.
The Ancient Greece's roots of Olimpism
Directory of Open Access Journals (Sweden)
Bubka Sergej Nazarovich
2011-10-01
Full Text Available The paper focused on the phenomena of sport in Ancient Greece along with history, traditions, religion, education, culture and art. Economic and political conditions are analysed which promote or hamper development of Olympic Games in Ancient Greece. Exceptional stability of Ancient Olympic games during more than eleven centuries are noted as well as their influence on the life of Greek polices of those days. Hellenistic period needs of individual consideration.
The History and Practice of Ancient Astronomy
Evans, James
1998-01-01
The History and Practice of Ancient Astronomy combines new scholarship with hands-on science to bring readers into direct contact with the work of ancient astronomers. While tracing ideas from ancient Babylon to sixteenth-century Europe, the book places its greatest emphasis on the Greek period, when astronomers developed the geometric and philosophical ideas that have determined the subsequent character of Western astronomy. The author approaches this history through the concrete details of ancient astronomical practice. Carefully organized and generously illustrated, the book can teach reade
From Here I Walked into Ancient China
Institute of Scientific and Technical Information of China (English)
Yan Manman
2011-01-01
@@ When I was a little girl, I had heard about the eighth world wonder - terra cotta warriors in Qin Emperor Mausoleum.I have been wishing to visit there to see those magnificent scene which were created thousands of years ago.While with my age added, I gradually learned the terra cotta warriors were lust only one of many ancient marks of Xi'an, which once was capital of 13 dynasties in ancient China.Xi'an actually is a carrier of ancient China culture, where I walked from the modern world to the ancient China.
Re-inventing ancient human DNA
Knapp, Michael; Lalueza-Fox, Carles; Hofreiter, M.
2015-01-01
For a long time, the analysis of ancient human DNA represented one of the most controversial disciplines in an already controversial field of research. Scepticism in this field was only matched by the long-lasting controversy over the authenticity of ancient pathogen DNA. This ambiguous view on ancient human DNA had a dichotomous root. On the one hand, the interest in ancient human DNA is great because such studies touch on the history and evolution of our own species. On the other hand, beca...
Ancient Ethics and Contemporary Ethics
Directory of Open Access Journals (Sweden)
Alfonso Gómez Lobo
1998-12-01
Full Text Available The aim of this paper is to examine a few doctrines in the history of ancient ethics which can still be considered valuable and even perhaps valid today. Moral motivation for the Stoics and for Socratesis based on self-interest with the further assumption that the moral virtues are the true goods. But the Stoic and Socratic justification strategies are different. Attention is then called to the Protagorean brand ofrelativism underlying contemporary libertarian claims. The paper end swith the suggestion that only a theory of objective human goods can resolve the problem of moral motivation and of the indeterminacy of the harm principie in modern liberalism.
Chinese Ancient Football with Romanticism
Institute of Scientific and Technical Information of China (English)
江凌; 李晓勤
2004-01-01
Like other traditional Chinese sports, the ancient Chinese football, which used to be called “cuju”, has some differences from several sports in western countries concerning cultural and hamanist purport as well as metal aspiration, although it was similar with modern football to some extent, such as a leather-made ball with a bladder, rectangle sports ground, referee, goal and certain competitiveness. The author tries to talk about such difference in cultural and humanist purport as well as mental aspiration by making a comparison between “cuju” and modern football.
Ancient Indian Leaps into Mathematics
Yadav, B S
2011-01-01
This book presents contributions of mathematicians covering topics from ancient India, placing them in the broader context of the history of mathematics. Although the translations of some Sanskrit mathematical texts are available in the literature, Indian contributions are rarely presented in major Western historical works. Yet some of the well-known and universally-accepted discoveries from India, including the concept of zero and the decimal representation of numbers, have made lasting contributions to the foundation of modern mathematics. Through a systematic approach, this book examines th
A Bayesian Reflection on Surfaces
Directory of Open Access Journals (Sweden)
David R. Wolf
1999-10-01
Full Text Available Abstract: The topic of this paper is a novel Bayesian continuous-basis field representation and inference framework. Within this paper several problems are solved: The maximally informative inference of continuous-basis fields, that is where the basis for the field is itself a continuous object and not representable in a finite manner; the tradeoff between accuracy of representation in terms of information learned, and memory or storage capacity in bits; the approximation of probability distributions so that a maximal amount of information about the object being inferred is preserved; an information theoretic justification for multigrid methodology. The maximally informative field inference framework is described in full generality and denoted the Generalized Kalman Filter. The Generalized Kalman Filter allows the update of field knowledge from previous knowledge at any scale, and new data, to new knowledge at any other scale. An application example instance, the inference of continuous surfaces from measurements (for example, camera image data, is presented.
Quantum Bayesianism at the Perimeter
Fuchs, Christopher A
2010-01-01
The author summarizes the Quantum Bayesian viewpoint of quantum mechanics, developed originally by C. M. Caves, R. Schack, and himself. It is a view crucially dependent upon the tools of quantum information theory. Work at the Perimeter Institute for Theoretical Physics continues the development and is focused on the hard technical problem of a finding a good representation of quantum mechanics purely in terms of probabilities, without amplitudes or Hilbert-space operators. The best candidate representation involves a mysterious entity called a symmetric informationally complete quantum measurement. Contemplation of it gives a way of thinking of the Born Rule as an addition to the rules of probability theory, applicable when one gambles on the consequences of interactions with physical systems. The article ends by outlining some directions for future work.
Hedging Strategies for Bayesian Optimization
Brochu, Eric; de Freitas, Nando
2010-01-01
Bayesian optimization with Gaussian processes has become an increasingly popular tool in the machine learning community. It is efficient and can be used when very little is known about the objective function, making it popular in expensive black-box optimization scenarios. It is able to do this by sampling the objective using an acquisition function which incorporates the model's estimate of the objective and the uncertainty at any given point. However, there are several different parameterized acquisition functions in the literature, and it is often unclear which one to use. Instead of using a single acquisition function, we adopt a portfolio of acquisition functions governed by an online multi-armed bandit strategy. We describe the method, which we call GP-Hedge, and show that this method almost always outperforms the best individual acquisition function.
Bayesian Networks and Influence Diagrams
DEFF Research Database (Denmark)
Kjærulff, Uffe Bro; Madsen, Anders Læsø
, and exercises are included for the reader to check his/her level of understanding. The techniques and methods presented for knowledge elicitation, model construction and verification, modeling techniques and tricks, learning models from data, and analyses of models have all been developed and refined......, troubleshooting, and data mining under uncertainty. Bayesian Networks and Influence Diagrams: A Guide to Construction and Analysis provides a comprehensive guide for practitioners who wish to understand, construct, and analyze intelligent systems for decision support based on probabilistic networks. Intended...... primarily for practitioners, this book does not require sophisticated mathematical skills or deep understanding of the underlying theory and methods nor does it discuss alternative technologies for reasoning under uncertainty. The theory and methods presented are illustrated through more than 140 examples...
Bayesian Networks and Influence Diagrams
DEFF Research Database (Denmark)
Kjærulff, Uffe Bro; Madsen, Anders Læsø
under uncertainty. The theory and methods presented are illustrated through more than 140 examples, and exercises are included for the reader to check his or her level of understanding. The techniques and methods presented on model construction and verification, modeling techniques and tricks, learning......Bayesian Networks and Influence Diagrams: A Guide to Construction and Analysis, Second Edition, provides a comprehensive guide for practitioners who wish to understand, construct, and analyze intelligent systems for decision support based on probabilistic networks. This new edition contains six new...... sections, in addition to fully-updated examples, tables, figures, and a revised appendix. Intended primarily for practitioners, this book does not require sophisticated mathematical skills or deep understanding of the underlying theory and methods nor does it discuss alternative technologies for reasoning...
State Information in Bayesian Games
Cuff, Paul
2009-01-01
Two-player zero-sum repeated games are well understood. Computing the value of such a game is straightforward. Additionally, if the payoffs are dependent on a random state of the game known to one, both, or neither of the players, the resulting value of the game has been analyzed under the framework of Bayesian games. This investigation considers the optimal performance in a game when a helper is transmitting state information to one of the players. Encoding information for an adversarial setting (game) requires a different result than rate-distortion theory provides. Game theory has accentuated the importance of randomization (mixed strategy), which does not find a significant role in most communication modems and source coding codecs. Higher rates of communication, used in the right way, allow the message to include the necessary random component useful in games.
Multiview Bayesian Correlated Component Analysis
DEFF Research Database (Denmark)
Kamronn, Simon Due; Poulsen, Andreas Trier; Hansen, Lars Kai
2015-01-01
Correlated component analysis as proposed by Dmochowski, Sajda, Dias, and Parra (2012) is a tool for investigating brain process similarity in the responses to multiple views of a given stimulus. Correlated components are identified under the assumption that the involved spatial networks...... are identical. Here we propose a hierarchical probabilistic model that can infer the level of universality in such multiview data, from completely unrelated representations, corresponding to canonical correlation analysis, to identical representations as in correlated component analysis. This new model, which...... we denote Bayesian correlated component analysis, evaluates favorably against three relevant algorithms in simulated data. A well-established benchmark EEG data set is used to further validate the new model and infer the variability of spatial representations across multiple subjects....
Elvira, Clément; Dobigeon, Nicolas
2015-01-01
Sparse representations have proven their efficiency in solving a wide class of inverse problems encountered in signal and image processing. Conversely, enforcing the information to be spread uniformly over representation coefficients exhibits relevant properties in various applications such as digital communications. Anti-sparse regularization can be naturally expressed through an $\\ell_{\\infty}$-norm penalty. This paper derives a probabilistic formulation of such representations. A new probability distribution, referred to as the democratic prior, is first introduced. Its main properties as well as three random variate generators for this distribution are derived. Then this probability distribution is used as a prior to promote anti-sparsity in a Gaussian linear inverse problem, yielding a fully Bayesian formulation of anti-sparse coding. Two Markov chain Monte Carlo (MCMC) algorithms are proposed to generate samples according to the posterior distribution. The first one is a standard Gibbs sampler. The seco...
Nonparametric Bayesian inference in biostatistics
Müller, Peter
2015-01-01
As chapters in this book demonstrate, BNP has important uses in clinical sciences and inference for issues like unknown partitions in genomics. Nonparametric Bayesian approaches (BNP) play an ever expanding role in biostatistical inference from use in proteomics to clinical trials. Many research problems involve an abundance of data and require flexible and complex probability models beyond the traditional parametric approaches. As this book's expert contributors show, BNP approaches can be the answer. Survival Analysis, in particular survival regression, has traditionally used BNP, but BNP's potential is now very broad. This applies to important tasks like arrangement of patients into clinically meaningful subpopulations and segmenting the genome into functionally distinct regions. This book is designed to both review and introduce application areas for BNP. While existing books provide theoretical foundations, this book connects theory to practice through engaging examples and research questions. Chapters c...
Bayesian Kernel Mixtures for Counts.
Canale, Antonio; Dunson, David B
2011-12-01
Although Bayesian nonparametric mixture models for continuous data are well developed, there is a limited literature on related approaches for count data. A common strategy is to use a mixture of Poissons, which unfortunately is quite restrictive in not accounting for distributions having variance less than the mean. Other approaches include mixing multinomials, which requires finite support, and using a Dirichlet process prior with a Poisson base measure, which does not allow smooth deviations from the Poisson. As a broad class of alternative models, we propose to use nonparametric mixtures of rounded continuous kernels. An efficient Gibbs sampler is developed for posterior computation, and a simulation study is performed to assess performance. Focusing on the rounded Gaussian case, we generalize the modeling framework to account for multivariate count data, joint modeling with continuous and categorical variables, and other complications. The methods are illustrated through applications to a developmental toxicity study and marketing data. This article has supplementary material online. PMID:22523437
Bayesian networks in educational assessment
Almond, Russell G; Steinberg, Linda S; Yan, Duanli; Williamson, David M
2015-01-01
Bayesian inference networks, a synthesis of statistics and expert systems, have advanced reasoning under uncertainty in medicine, business, and social sciences. This innovative volume is the first comprehensive treatment exploring how they can be applied to design and analyze innovative educational assessments. Part I develops Bayes nets’ foundations in assessment, statistics, and graph theory, and works through the real-time updating algorithm. Part II addresses parametric forms for use with assessment, model-checking techniques, and estimation with the EM algorithm and Markov chain Monte Carlo (MCMC). A unique feature is the volume’s grounding in Evidence-Centered Design (ECD) framework for assessment design. This “design forward” approach enables designers to take full advantage of Bayes nets’ modularity and ability to model complex evidentiary relationships that arise from performance in interactive, technology-rich assessments such as simulations. Part III describes ECD, situates Bayes nets as ...
[Ancient history of Indian pharmacy].
Okuda, Jun; Natsume, Yohko
2010-01-01
The study of the ancient history of Indian medicine has recently been revived due to the publication of polyglot translations. However, little is known of ancient Indian pharmacy. Archaeological evidence suggests the Indus people lived a settled life approximately in 2500 B.C. Their cities were enjoying the cleanest and most hygienic daily life with elaborate civic sanitation systems. The whole conception shows a remarkable concern for health. Then, the early Aryans invaded India about 1500 B.C. and the Vedic age started. The Rgveda texts contain the hymns for Soma and those for herbs. The term Ayurveda (i.e., science of life) is found in some old versions of both Ramāyana and Mahābhārata and in the Atharvaveda. Suśruta had the credit of making a breakthrough in the field of surgery. The Ayurveda, a work on internal medicine, gives the following transmission of sages: Brahmā-->Daksa-->Prajāpati-->Aśivinau-->Indra-->Caraka. On the other hand, the Suśruta-samhitā, which deals mainly with surgical medicine, explains it as follows; Indra-->Dhanvantari-->Suśruta Both Caraka and Suśruta were medical doctors as well as pharmacists, so they studied more than 1000 herbs thoroughly. The Ayurveda had been used by his devotees for medical purposes. It eventually spread over Asia with the advanced evolution of Buddhism.
[Ancient history of Indian pharmacy].
Okuda, Jun; Natsume, Yohko
2010-01-01
The study of the ancient history of Indian medicine has recently been revived due to the publication of polyglot translations. However, little is known of ancient Indian pharmacy. Archaeological evidence suggests the Indus people lived a settled life approximately in 2500 B.C. Their cities were enjoying the cleanest and most hygienic daily life with elaborate civic sanitation systems. The whole conception shows a remarkable concern for health. Then, the early Aryans invaded India about 1500 B.C. and the Vedic age started. The Rgveda texts contain the hymns for Soma and those for herbs. The term Ayurveda (i.e., science of life) is found in some old versions of both Ramāyana and Mahābhārata and in the Atharvaveda. Suśruta had the credit of making a breakthrough in the field of surgery. The Ayurveda, a work on internal medicine, gives the following transmission of sages: Brahmā-->Daksa-->Prajāpati-->Aśivinau-->Indra-->Caraka. On the other hand, the Suśruta-samhitā, which deals mainly with surgical medicine, explains it as follows; Indra-->Dhanvantari-->Suśruta Both Caraka and Suśruta were medical doctors as well as pharmacists, so they studied more than 1000 herbs thoroughly. The Ayurveda had been used by his devotees for medical purposes. It eventually spread over Asia with the advanced evolution of Buddhism. PMID:21032887
Bayesian models a statistical primer for ecologists
Hobbs, N Thompson
2015-01-01
Bayesian modeling has become an indispensable tool for ecological research because it is uniquely suited to deal with complexity in a statistically coherent way. This textbook provides a comprehensive and accessible introduction to the latest Bayesian methods-in language ecologists can understand. Unlike other books on the subject, this one emphasizes the principles behind the computations, giving ecologists a big-picture understanding of how to implement this powerful statistical approach. Bayesian Models is an essential primer for non-statisticians. It begins with a definition of probabili
Compiling Relational Bayesian Networks for Exact Inference
DEFF Research Database (Denmark)
Jaeger, Manfred; Darwiche, Adnan; Chavira, Mark
2006-01-01
We describe in this paper a system for exact inference with relational Bayesian networks as defined in the publicly available PRIMULA tool. The system is based on compiling propositional instances of relational Bayesian networks into arithmetic circuits and then performing online inference...... by evaluating and differentiating these circuits in time linear in their size. We report on experimental results showing successful compilation and efficient inference on relational Bayesian networks, whose PRIMULA--generated propositional instances have thousands of variables, and whose jointrees have clusters...
Directory of Open Access Journals (Sweden)
V V Robin
Full Text Available BACKGROUND: Sky islands, formed by the highest reaches of mountain tracts physically isolated from one another, represent one of the biodiversity-rich regions of the world. Comparative studies of geographically isolated populations on such islands can provide valuable insights into the biogeography and evolution of species on these islands. The Western Ghats mountains of southern India form a sky island system, where the relationship between the island structure and the evolution of its species remains virtually unknown despite a few population genetic studies. METHODS AND PRINCIPAL FINDINGS: We investigated how ancient geographic gaps and glacial cycles have partitioned genetic variation in modern populations of a threatened endemic bird, the White-bellied Shortwing Brachypteryx major, across the montane Shola forests on these islands and also inferred its evolutionary history. We used bayesian and maximum likelihood-based phylogenetic and population-genetic analyses on data from three mitochondrial markers and one nuclear marker (totally 2594 bp obtained from 33 White-bellied Shortwing individuals across five islands. Genetic differentiation between populations of the species correlated with the locations of deep valleys in the Western Ghats but not with geographical distance between these populations. All populations revealed demographic histories consistent with population founding and expansion during the Last Glacial Maximum. Given the level of genetic differentiation north and south of the Palghat Gap, we suggest that these populations be considered two different taxonomic species. CONCLUSIONS AND SIGNIFICANCE: Our results show that the physiography and paleo-climate of this region historically resulted in multiple glacial refugia that may have subsequently driven the evolutionary history and current population structure of this bird. The first avian genetic study from this biodiversity hotspot, our results provide insights into processes
The Idea of Ancient Greek Philosophy
Institute of Scientific and Technical Information of China (English)
苏雪
2016-01-01
As the source of western philosophy, ancient Greek philosophy had a profound influence on western philosophy. Ancient philosophers were hard to reach a consensus on the existence of all the things in the world. They tried to grasp the profound understanding of the world, which is the clue of the history of philosophy.
Attitudes Toward Deviant Sex in Ancient Mesopotamia
Bullough, Vern L.
1971-01-01
The article concludes that the whole question of sexual life in ancient Mesopotamia is difficult to reconstruct and fraught with many uncertainties. Nevertheless, it seems certain that the ancient Mesopotamians had fewer prohibitions against sex than our own civilization, and regarded as acceptable many practices which later societies condemned.…
An ancient rangefinder for teaching surveying methods
Sparavigna, Amelia Carolina
2012-01-01
Rangefinders are instruments used for ballistics and for surveying in general. Here we propose a discussion of some of them, ranging from the ancient Rome to the modern methods. Using an ancient roman artefact as a model, we can pre-pare a rangefinder at no cost for teaching surveying methods to students of engineering and military schools
Women--Sex Objects in Ancient Egypt.
Mutimer, Brian T. P.
Although it has been said that the women in Ancient Egypt enjoyed a reasonable state of social and professional equality with men, this paper presents an alternate theory--that women were second-class citizens whose physical prowess was secondary to their role as sex objects. It appears that men and women in Ancient Egypt often participated in the…
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.
A Hierarchical Bayesian Model to Predict Self-Thinning Line for Chinese Fir in Southern China.
Directory of Open Access Journals (Sweden)
Xiongqing Zhang
Full Text Available Self-thinning is a dynamic equilibrium between forest growth and mortality at full site occupancy. Parameters of the self-thinning lines are often confounded by differences across various stand and site conditions. For overcoming the problem of hierarchical and repeated measures, we used hierarchical Bayesian method to estimate the self-thinning line. The results showed that the self-thinning line for Chinese fir (Cunninghamia lanceolata (Lamb.Hook. plantations was not sensitive to the initial planting density. The uncertainty of model predictions was mostly due to within-subject variability. The simulation precision of hierarchical Bayesian method was better than that of stochastic frontier function (SFF. Hierarchical Bayesian method provided a reasonable explanation of the impact of other variables (site quality, soil type, aspect, etc. on self-thinning line, which gave us the posterior distribution of parameters of self-thinning line. The research of self-thinning relationship could be benefit from the use of hierarchical Bayesian method.
Mechanisms in ancient Chinese books with illustrations
Hsiao, Kuo-Hung
2014-01-01
This book presents a unique approach for studying mechanisms and machines with drawings that were depicted unclearly in ancient Chinese books. The historical, cultural and technical backgrounds of the mechanisms are explained, and various mechanisms described and illustrated in ancient books are introduced. By utilizing the idea for the conceptual design of modern mechanisms, all feasible designs of ancient mechanisms with uncertain members and joints that meet the technical standards of the subjects’ time periods are synthesized systematically. Ancient Chinese crossbows (the original crossbow and repeating crossbows), textile mechanisms (silk-reeling mechanism, spinning mechanisms, and looms), and many other artisan's tool mechanisms are used as illustrated examples. Such an approach provides a logical method for the reconstruction designs of ancient mechanisms with uncertain structures. It also provides an innovative direction for researchers to further identify the original structures of mechanisms...
Structural recognition of ancient Chinese ideographic characters
Institute of Scientific and Technical Information of China (English)
Li Ning; Chen Dan
2014-01-01
Ancient Chinese characters, typically the ideographic characters on bones and bronze before Shang Dynasty (16th—11th century B.C.), are valuable culture legacy of history. However the recognition of Ancient Chinese characters has been the task of paleography experts for long. With the help of modern computer technique, everyone can expect to be able to recognize the characters and understand the ancient inscriptions. This research is aimed to help people recognize and understand those ancient Chinese characters by combining Chinese paleography theory and computer information processing technology. Based on the analysis of ancient character features, a method for structural character recognition is proposed. The important characteristics of strokes and basic components or radicals used in recognition are introduced in detail. A system was implemented based on above method to show the effectiveness of the method.
Bayesian Uncertainty Analyses Via Deterministic Model
Krzysztofowicz, R.
2001-05-01
Rational decision-making requires that the total uncertainty about a variate of interest (a predictand) be quantified in terms of a probability distribution, conditional on all available information and knowledge. Suppose the state-of-knowledge is embodied in a deterministic model, which is imperfect and outputs only an estimate of the predictand. Fundamentals are presented of three Bayesian approaches to producing a probability distribution of the predictand via any deterministic model. The Bayesian Processor of Output (BPO) quantifies the total uncertainty in terms of a posterior distribution, conditional on model output. The Bayesian Processor of Ensemble (BPE) quantifies the total uncertainty in terms of a posterior distribution, conditional on an ensemble of model output. The Bayesian Forecasting System (BFS) decomposes the total uncertainty into input uncertainty and model uncertainty, which are characterized independently and then integrated into a predictive distribution.
Learning Bayesian networks for discrete data
Liang, Faming
2009-02-01
Bayesian networks have received much attention in the recent literature. In this article, we propose an approach to learn Bayesian networks using the stochastic approximation Monte Carlo (SAMC) algorithm. Our approach has two nice features. Firstly, it possesses the self-adjusting mechanism and thus avoids essentially the local-trap problem suffered by conventional MCMC simulation-based approaches in learning Bayesian networks. Secondly, it falls into the class of dynamic importance sampling algorithms; the network features can be inferred by dynamically weighted averaging the samples generated in the learning process, and the resulting estimates can have much lower variation than the single model-based estimates. The numerical results indicate that our approach can mix much faster over the space of Bayesian networks than the conventional MCMC simulation-based approaches. © 2008 Elsevier B.V. All rights reserved.
A Bayesian approach to model uncertainty
International Nuclear Information System (INIS)
A Bayesian approach to model uncertainty is taken. For the case of a finite number of alternative models, the model uncertainty is equivalent to parameter uncertainty. A derivation based on Savage's partition problem is given
Bayesian Control for Concentrating Mixed Nuclear Waste
Welch, Robert L.; Smith, Clayton
2013-01-01
A control algorithm for batch processing of mixed waste is proposed based on conditional Gaussian Bayesian networks. The network is compiled during batch staging for real-time response to sensor input.
An Intuitive Dashboard for Bayesian Network Inference
International Nuclear Information System (INIS)
Current Bayesian network software packages provide good graphical interface for users who design and develop Bayesian networks for various applications. However, the intended end-users of these networks may not necessarily find such an interface appealing and at times it could be overwhelming, particularly when the number of nodes in the network is large. To circumvent this problem, this paper presents an intuitive dashboard, which provides an additional layer of abstraction, enabling the end-users to easily perform inferences over the Bayesian networks. Unlike most software packages, which display the nodes and arcs of the network, the developed tool organises the nodes based on the cause-and-effect relationship, making the user-interaction more intuitive and friendly. In addition to performing various types of inferences, the users can conveniently use the tool to verify the behaviour of the developed Bayesian network. The tool has been developed using QT and SMILE libraries in C++
An Intuitive Dashboard for Bayesian Network Inference
Reddy, Vikas; Charisse Farr, Anna; Wu, Paul; Mengersen, Kerrie; Yarlagadda, Prasad K. D. V.
2014-03-01
Current Bayesian network software packages provide good graphical interface for users who design and develop Bayesian networks for various applications. However, the intended end-users of these networks may not necessarily find such an interface appealing and at times it could be overwhelming, particularly when the number of nodes in the network is large. To circumvent this problem, this paper presents an intuitive dashboard, which provides an additional layer of abstraction, enabling the end-users to easily perform inferences over the Bayesian networks. Unlike most software packages, which display the nodes and arcs of the network, the developed tool organises the nodes based on the cause-and-effect relationship, making the user-interaction more intuitive and friendly. In addition to performing various types of inferences, the users can conveniently use the tool to verify the behaviour of the developed Bayesian network. The tool has been developed using QT and SMILE libraries in C++.
Nomograms for Visualization of Naive Bayesian Classifier
Možina, Martin; Demšar, Janez; Michael W Kattan; Zupan, Blaz
2004-01-01
Besides good predictive performance, the naive Bayesian classifier can also offer a valuable insight into the structure of the training data and effects of the attributes on the class probabilities. This structure may be effectively revealed through visualization of the classifier. We propose a new way to visualize the naive Bayesian model in the form of a nomogram. The advantages of the proposed method are simplicity of presentation, clear display of the effects of individual attribute value...
Subjective Bayesian Analysis: Principles and Practice
Goldstein, Michael
2006-01-01
We address the position of subjectivism within Bayesian statistics. We argue, first, that the subjectivist Bayes approach is the only feasible method for tackling many important practical problems. Second, we describe the essential role of the subjectivist approach in scientific analysis. Third, we consider possible modifications to the Bayesian approach from a subjectivist viewpoint. Finally, we address the issue of pragmatism in implementing the subjectivist approach.
Bayesian Analysis of Multivariate Probit Models
Siddhartha Chib; Edward Greenberg
1996-01-01
This paper provides a unified simulation-based Bayesian and non-Bayesian analysis of correlated binary data using the multivariate probit model. The posterior distribution is simulated by Markov chain Monte Carlo methods, and maximum likelihood estimates are obtained by a Markov chain Monte Carlo version of the E-M algorithm. Computation of Bayes factors from the simulation output is also considered. The methods are applied to a bivariate data set, to a 534-subject, four-year longitudinal dat...
Fitness inheritance in the Bayesian optimization algorithm
Pelikan, Martin; Sastry, Kumara
2004-01-01
This paper describes how fitness inheritance can be used to estimate fitness for a proportion of newly sampled candidate solutions in the Bayesian optimization algorithm (BOA). The goal of estimating fitness for some candidate solutions is to reduce the number of fitness evaluations for problems where fitness evaluation is expensive. Bayesian networks used in BOA to model promising solutions and generate the new ones are extended to allow not only for modeling and sampling candidate solutions...
Kernel Bayesian Inference with Posterior Regularization
Song, Yang; Jun ZHU; Ren, Yong
2016-01-01
We propose a vector-valued regression problem whose solution is equivalent to the reproducing kernel Hilbert space (RKHS) embedding of the Bayesian posterior distribution. This equivalence provides a new understanding of kernel Bayesian inference. Moreover, the optimization problem induces a new regularization for the posterior embedding estimator, which is faster and has comparable performance to the squared regularization in kernel Bayes' rule. This regularization coincides with a former th...
Bayesian Classification in Medicine: The Transferability Question *
Zagoria, Ronald J.; Reggia, James A.; Price, Thomas R.; Banko, Maryann
1981-01-01
Using probabilities derived from a geographically distant patient population, we applied Bayesian classification to categorize stroke patients by etiology. Performance was assessed both by error rate and with a new linear accuracy coefficient. This approach to patient classification was found to be surprisingly accurate when compared to classification by two neurologists and to classification by the Bayesian method using “low cost” local and subjective probabilities. We conclude that for some...
Bayesian target tracking based on particle filter
Institute of Scientific and Technical Information of China (English)
无
2005-01-01
For being able to deal with the nonlinear or non-Gaussian problems, particle filters have been studied by many researchers. Based on particle filter, the extended Kalman filter (EKF) proposal function is applied to Bayesian target tracking. Markov chain Monte Carlo (MCMC) method, the resampling step, etc novel techniques are also introduced into Bayesian target tracking. And the simulation results confirm the improved particle filter with these techniques outperforms the basic one.
Bayesian Variable Selection in Spatial Autoregressive Models
Jesus Crespo Cuaresma; Philipp Piribauer
2015-01-01
This paper compares the performance of Bayesian variable selection approaches for spatial autoregressive models. We present two alternative approaches which can be implemented using Gibbs sampling methods in a straightforward way and allow us to deal with the problem of model uncertainty in spatial autoregressive models in a flexible and computationally efficient way. In a simulation study we show that the variable selection approaches tend to outperform existing Bayesian model averaging tech...
Fuzzy Functional Dependencies and Bayesian Networks
Institute of Scientific and Technical Information of China (English)
LIU WeiYi(刘惟一); SONG Ning(宋宁)
2003-01-01
Bayesian networks have become a popular technique for representing and reasoning with probabilistic information. The fuzzy functional dependency is an important kind of data dependencies in relational databases with fuzzy values. The purpose of this paper is to set up a connection between these data dependencies and Bayesian networks. The connection is done through a set of methods that enable people to obtain the most information of independent conditions from fuzzy functional dependencies.
Bayesian Models of Brain and Behaviour
Penny, William
2012-01-01
This paper presents a review of Bayesian models of brain and behaviour. We first review the basic principles of Bayesian inference. This is followed by descriptions of sampling and variational methods for approximate inference, and forward and backward recursions in time for inference in dynamical models. The review of behavioural models covers work in visual processing, sensory integration, sensorimotor integration, and collective decision making. The review of brain models covers a range of...
Bayesian Modeling of a Human MMORPG Player
Synnaeve, Gabriel
2010-01-01
This paper describes an application of Bayesian programming to the control of an autonomous avatar in a multiplayer role-playing game (the example is based on World of Warcraft). We model a particular task, which consists of choosing what to do and to select which target in a situation where allies and foes are present. We explain the model in Bayesian programming and show how we could learn the conditional probabilities from data gathered during human-played sessions.
Bayesian Modeling of a Human MMORPG Player
Synnaeve, Gabriel; Bessière, Pierre
2011-03-01
This paper describes an application of Bayesian programming to the control of an autonomous avatar in a multiplayer role-playing game (the example is based on World of Warcraft). We model a particular task, which consists of choosing what to do and to select which target in a situation where allies and foes are present. We explain the model in Bayesian programming and show how we could learn the conditional probabilities from data gathered during human-played sessions.
Ancient Acupuncture Literature on Apoplexy
Institute of Scientific and Technical Information of China (English)
XU Yi-zeng; BI Zhen; Xiao Yuan-chun
2003-01-01
This paper reviews twenty-eight Chinese medicine books with complete prescriptions prior to the Qing Dynasty, and analyzes the characteristics of acupoint selection and needling manipulations from the perspective of apoplectic symptoms. It is concluded that,in ancient times, apoplexy is often treated on the basis of its symptoms and a great number of acupoints are employed; hemiplegia is mainly treated by the acupoints of the Large Intestine Meridian and Gallbladder Meridian,with two key acupoints; coma is mainly treated by first-aid acupoints and qi-supplementing acupoints, with seven key acupoints; wry mouth and convulsion are mainly treated by the local acupoints; as for needling manipulations, moxibustion with moxa cones is principally used, while needling is less used.
Detecting hybridization using ancient DNA.
Schaefer, Nathan K; Shapiro, Beth; Green, Richard E
2016-06-01
It is well established that related species hybridize and that this can have varied but significant effects on speciation and environmental adaptation. It should therefore come as no surprise that hybridization is not limited to species that are alive today. In the last several decades, advances in technologies for recovering and sequencing DNA from fossil remains have enabled the assembly of high-coverage genome sequences for a growing diversity of organisms, including many that are extinct. Thanks to the development of new statistical approaches for detecting and quantifying admixture from genomic data, genomes from extinct populations have proven useful both in revealing previously unknown hybridization events and informing the study of hybridization between living organisms. Here, we review some of the key recent statistical innovations for detecting ancient hybridization using genomewide sequence data and discuss how these innovations have revised our understanding of human evolutionary history.
[Being old in ancient Hellas].
van Hooff, A J
1983-08-01
There is room for a more balanced view of old age among the ancient Greeks than is furnished by De Beauvoir's la Vieillesse and other more or less one-sided publications. The old body was despised by the Greeks of classical times; especially walking with three legs (tripous) was stressed as a mark of old age. The Hippocratic writings show some interest in the infirmities of elderly people. Specific psychic and intellectual qualities were not attributed to senescence: old age brought out good and bad qualities of a person more sharply than before. The share of old people in the population cannot be established with any certainty, but there was always a group of men in their sixties who had specific tasks in society. Old age was not an autonomous theme in art, it was solely accidental. The position of the elderly was challenged occasionally in democratic Athens, but it was never undermined. Old people were never marginated in classical Greece.
Updating beliefs and combining evidence in adaptive forest management under climate change
DEFF Research Database (Denmark)
Yousefpour, Rasoul; Temperli, Christian; Bugmann, Harald;
2013-01-01
We study climate uncertainty and how managers' beliefs about climate change develop and influence their decisions. We develop an approach for updating knowledge and beliefs based on the observation of forest and climate variables and illustrate its application for the adaptive management of an even......-aged Norway spruce (Picea abies L. Karst) forest in the Black Forest, Germany. We simulated forest development under a range of climate change scenarios and forest management alternatives. Our analysis used Bayesian updating and Dempster's rule of combination to simulate how observations of climate and forest...... variables may influence a decision maker's beliefs about climate development and thereby management decisions. While forest managers may be inclined to rely on observed forest variables to infer climate change and impacts, we found that observation of climate state, e.g. temperature or precipitation...
FS National Forest Dataset (US Forest Service Proclaimed Forests)
US Forest Service, Department of Agriculture — A map service on the www depicting the boundaries encompassing the National Forest System (NFS) lands within the original proclaimed National Forests, along with...
Almathen, Faisal; Charruau, Pauline; Mohandesan, Elmira; Mwacharo, Joram M; Orozco-terWengel, Pablo; Pitt, Daniel; Abdussamad, Abdussamad M; Uerpmann, Margarethe; Uerpmann, Hans-Peter; De Cupere, Bea; Magee, Peter; Alnaqeeb, Majed A; Salim, Bashir; Raziq, Abdul; Dessie, Tadelle; Abdelhadi, Omer M; Banabazi, Mohammad H; Al-Eknah, Marzook; Walzer, Chris; Faye, Bernard; Hofreiter, Michael; Peters, Joris; Hanotte, Olivier; Burger, Pamela A
2016-06-14
Dromedaries have been fundamental to the development of human societies in arid landscapes and for long-distance trade across hostile hot terrains for 3,000 y. Today they continue to be an important livestock resource in marginal agro-ecological zones. However, the history of dromedary domestication and the influence of ancient trading networks on their genetic structure have remained elusive. We combined ancient DNA sequences of wild and early-domesticated dromedary samples from arid regions with nuclear microsatellite and mitochondrial genotype information from 1,083 extant animals collected across the species' range. We observe little phylogeographic signal in the modern population, indicative of extensive gene flow and virtually affecting all regions except East Africa, where dromedary populations have remained relatively isolated. In agreement with archaeological findings, we identify wild dromedaries from the southeast Arabian Peninsula among the founders of the domestic dromedary gene pool. Approximate Bayesian computations further support the "restocking from the wild" hypothesis, with an initial domestication followed by introgression from individuals from wild, now-extinct populations. Compared with other livestock, which show a long history of gene flow with their wild ancestors, we find a high initial diversity relative to the native distribution of the wild ancestor on the Arabian Peninsula and to the brief coexistence of early-domesticated and wild individuals. This study also demonstrates the potential to retrieve ancient DNA sequences from osseous remains excavated in hot and dry desert environments. PMID:27162355
Almathen, Faisal; Charruau, Pauline; Mohandesan, Elmira; Mwacharo, Joram M; Orozco-terWengel, Pablo; Pitt, Daniel; Abdussamad, Abdussamad M; Uerpmann, Margarethe; Uerpmann, Hans-Peter; De Cupere, Bea; Magee, Peter; Alnaqeeb, Majed A; Salim, Bashir; Raziq, Abdul; Dessie, Tadelle; Abdelhadi, Omer M; Banabazi, Mohammad H; Al-Eknah, Marzook; Walzer, Chris; Faye, Bernard; Hofreiter, Michael; Peters, Joris; Hanotte, Olivier; Burger, Pamela A
2016-06-14
Dromedaries have been fundamental to the development of human societies in arid landscapes and for long-distance trade across hostile hot terrains for 3,000 y. Today they continue to be an important livestock resource in marginal agro-ecological zones. However, the history of dromedary domestication and the influence of ancient trading networks on their genetic structure have remained elusive. We combined ancient DNA sequences of wild and early-domesticated dromedary samples from arid regions with nuclear microsatellite and mitochondrial genotype information from 1,083 extant animals collected across the species' range. We observe little phylogeographic signal in the modern population, indicative of extensive gene flow and virtually affecting all regions except East Africa, where dromedary populations have remained relatively isolated. In agreement with archaeological findings, we identify wild dromedaries from the southeast Arabian Peninsula among the founders of the domestic dromedary gene pool. Approximate Bayesian computations further support the "restocking from the wild" hypothesis, with an initial domestication followed by introgression from individuals from wild, now-extinct populations. Compared with other livestock, which show a long history of gene flow with their wild ancestors, we find a high initial diversity relative to the native distribution of the wild ancestor on the Arabian Peninsula and to the brief coexistence of early-domesticated and wild individuals. This study also demonstrates the potential to retrieve ancient DNA sequences from osseous remains excavated in hot and dry desert environments.
Thomson, Vicki A; Lebrasseur, Ophélie; Austin, Jeremy J; Hunt, Terry L; Burney, David A; Denham, Tim; Rawlence, Nicolas J; Wood, Jamie R; Gongora, Jaime; Girdland Flink, Linus; Linderholm, Anna; Dobney, Keith; Larson, Greger; Cooper, Alan
2014-04-01
The human colonization of Remote Oceania remains one of the great feats of exploration in history, proceeding east from Asia across the vast expanse of the Pacific Ocean. Human commensal and domesticated species were widely transported as part of this diaspora, possibly as far as South America. We sequenced mitochondrial control region DNA from 122 modern and 22 ancient chicken specimens from Polynesia and Island Southeast Asia and used these together with Bayesian modeling methods to examine the human dispersal of chickens across this area. We show that specific techniques are essential to remove contaminating modern DNA from experiments, which appear to have impacted previous studies of Pacific chickens. In contrast to previous reports, we find that all ancient specimens and a high proportion of the modern chickens possess a group of unique, closely related haplotypes found only in the Pacific. This group of haplotypes appears to represent the authentic founding mitochondrial DNA chicken lineages transported across the Pacific, and allows the early dispersal of chickens across Micronesia and Polynesia to be modeled. Importantly, chickens carrying this genetic signature persist on several Pacific islands at high frequencies, suggesting that the original Polynesian chicken lineages may still survive. No early South American chicken samples have been detected with the diagnostic Polynesian mtDNA haplotypes, arguing against reports that chickens provide evidence of Polynesian contact with pre-European South America. Two modern specimens from the Philippines carry haplotypes similar to the ancient Pacific samples, providing clues about a potential homeland for the Polynesian chicken. PMID:24639505
Putting Us on the Map: Remote Sensing Investigation of the Ancient Maya Landscape
Sever, Thomas L.; Saturno, William
2004-01-01
A common problem for archaeologists studying ancient settlement in the Maya Lowlands is overcoming the dense vegetation in order to obtain an accurate regional perspective of the presence of archaeological sites, their exact locations and their overall extents. Most often this is done by extensive ground surveys in which many individuals chop parallel paths through the vegetation in search of sites. Once a site is found an effort is made to mark its location on a regional map and to explore its perimeter. Obtaining locational information has been made dramatically easier in recent years with the advent of improved Global Positioning Systems (GPS), however the process of initial identification of sites and the determination of their borders is exceedingly labor intensive and has remained relatively unchanged since the beginning of settlement surveys in the region in the 1950 s. Currently, we are revolutionizing settlement survey in the Maya Lowlands by using remotely sensed data from IKONOS, Quickbird, and Eo 1, satellites as well as airborne AIRSAR radar data. The Ancient Maya built their cities, towns and even their smallest hamlets using excavated limestone and lime plasters. We propose that the decay of these structures provides a unique microenvironment for the growth of vegetation as the levels of moisture and nutrition within the ruins vary substantially from those in the surrounding forest. These microenvironmental differences on the ground are likewise represented by compositional differences in the forest canopy both in the species present and in leaf color (representing moisture/nutritional stress) visible through the analysis of high-resolution satellite data. In this way the detailed analysis of forest composition can reveal a detailed picture of the ancient settlements that lie beneath it. Preliminary examinations using this technique have been very successful and we are refining these techniques in order to efficiently comprehend the details of
Bayesian inference for OPC modeling
Burbine, Andrew; Sturtevant, John; Fryer, David; Smith, Bruce W.
2016-03-01
The use of optical proximity correction (OPC) demands increasingly accurate models of the photolithographic process. Model building and inference techniques in the data science community have seen great strides in the past two decades which make better use of available information. This paper aims to demonstrate the predictive power of Bayesian inference as a method for parameter selection in lithographic models by quantifying the uncertainty associated with model inputs and wafer data. Specifically, the method combines the model builder's prior information about each modelling assumption with the maximization of each observation's likelihood as a Student's t-distributed random variable. Through the use of a Markov chain Monte Carlo (MCMC) algorithm, a model's parameter space is explored to find the most credible parameter values. During parameter exploration, the parameters' posterior distributions are generated by applying Bayes' rule, using a likelihood function and the a priori knowledge supplied. The MCMC algorithm used, an affine invariant ensemble sampler (AIES), is implemented by initializing many walkers which semiindependently explore the space. The convergence of these walkers to global maxima of the likelihood volume determine the parameter values' highest density intervals (HDI) to reveal champion models. We show that this method of parameter selection provides insights into the data that traditional methods do not and outline continued experiments to vet the method.
Bayesian analysis of 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 volcanic eruptions
Ho, Chih-Hsiang
1990-10-01
The simple Poisson model generally gives a good fit to many volcanoes for volcanic eruption forecasting. Nonetheless, empirical evidence suggests that volcanic activity in successive equal time-periods tends to be more variable than a simple Poisson with constant eruptive rate. An alternative model is therefore examined in which eruptive rate(λ) for a given volcano or cluster(s) of volcanoes is described by a gamma distribution (prior) rather than treated as a constant value as in the assumptions of a simple Poisson model. Bayesian analysis is performed to link two distributions together to give the aggregate behavior of the volcanic activity. When the Poisson process is expanded to accomodate a gamma mixing distribution on λ, a consequence of this mixed (or compound) Poisson model is that the frequency distribution of eruptions in any given time-period of equal length follows the negative binomial distribution (NBD). Applications of the proposed model and comparisons between the generalized model and simple Poisson model are discussed based on the historical eruptive count data of volcanoes Mauna Loa (Hawaii) and Etna (Italy). Several relevant facts lead to the conclusion that the generalized model is preferable for practical use both in space and time.
BAYESIAN APPROACH OF DECISION PROBLEMS
Directory of Open Access Journals (Sweden)
DRAGOŞ STUPARU
2010-01-01
Full Text Available Management is nowadays a basic vector of economic development, a concept frequently used in our country as well as all over the world. Indifferently of the hierarchical level at which the managerial process is manifested, decision represents its essential moment, the supreme act of managerial activity. Its can be met in all fields of activity, practically having an unlimited degree of coverage, and in all the functions of management. It is common knowledge that the activity of any type of manger, no matter the hierarchical level he occupies, represents a chain of interdependent decisions, their aim being the elimination or limitation of the influence of disturbing factors that may endanger the achievement of predetermined objectives, and the quality of managerial decisions condition the progress and viability of any enterprise. Therefore, one of the principal characteristics of a successful manager is his ability to adopt the most optimal decisions of high quality. The quality of managerial decisions are conditioned by the manager’s general level of education and specialization, the manner in which they are preoccupied to assimilate the latest information and innovations in the domain of management’s theory and practice and the applying of modern managerial methods and techniques in the activity of management. We are presenting below the analysis of decision problems in hazardous conditions in terms of Bayesian theory – a theory that uses the probabilistic calculus.
Directory of Open Access Journals (Sweden)
Jordi Salmona
Full Text Available The exceptional biodiversity of Reunion Island is threatened by anthropogenic landscape changes that took place during the 350 years of human colonization. During this period the human population size increased dramatically from 250 to 800,000. The arrival of humans together with the development of agriculture, invasive species such as rats and cats, and deforestation has lead to the extinction of more than half of the original vertebrate species of the island. For the remaining species, significant work is being carried out to identify threats and conservation status, but little genetic work has been carried on some of the most endangered species. In the last decade theoretical studies have shown the ability of neutral genetic markers to infer the demographic history of endangered species and identify and date past population size changes (expansions or bottlenecks. In this study we provide the first genetic data on the critically endangered species the Reunion cuckoo-shrike Coracina newtoni. The Reunion cuckoo-shrike is a rare endemic forest bird surviving in a restricted 12-km(2 area of forested uplands and mountains. The total known population consists of less than one hundred individuals out of which 45 were genotyped using seventeen polymorphic microsatellite loci. We found a limited level of genetic variability and weak population structure, probably due to the limited geographic distribution. Using Bayesian methods, we identified a strong decline in population size during the Holocene, most likely caused by an ancient climatic or volcanic event around 5000 years ago. This result was surprising as it appeared in apparent contradiction with the accepted theory of recent population collapse due to deforestation and predator introduction. These results suggest that new methods allowing for more complex demographic models are necessary to reconstruct the demographic history of populations.
Salmona, Jordi; Salamolard, Marc; Fouillot, Damien; Ghestemme, Thomas; Larose, Jerry; Centon, Jean-François; Sousa, Vitor; Dawson, Deborah A.; Thebaud, Christophe; Chikhi, Lounès
2012-01-01
The exceptional biodiversity of Reunion Island is threatened by anthropogenic landscape changes that took place during the 350 years of human colonization. During this period the human population size increased dramatically from 250 to 800,000. The arrival of humans together with the development of agriculture, invasive species such as rats and cats, and deforestation has lead to the extinction of more than half of the original vertebrate species of the island. For the remaining species, significant work is being carried out to identify threats and conservation status, but little genetic work has been carried on some of the most endangered species. In the last decade theoretical studies have shown the ability of neutral genetic markers to infer the demographic history of endangered species and identify and date past population size changes (expansions or bottlenecks). In this study we provide the first genetic data on the critically endangered species the Reunion cuckoo-shrike Coracina newtoni. The Reunion cuckoo-shrike is a rare endemic forest bird surviving in a restricted 12-km2 area of forested uplands and mountains. The total known population consists of less than one hundred individuals out of which 45 were genotyped using seventeen polymorphic microsatellite loci. We found a limited level of genetic variability and weak population structure, probably due to the limited geographic distribution. Using Bayesian methods, we identified a strong decline in population size during the Holocene, most likely caused by an ancient climatic or volcanic event around 5000 years ago. This result was surprising as it appeared in apparent contradiction with the accepted theory of recent population collapse due to deforestation and predator introduction. These results suggest that new methods allowing for more complex demographic models are necessary to reconstruct the demographic history of populations. PMID:22916272
Bayesian demography 250 years after Bayes.
Bijak, Jakub; Bryant, John
2016-01-01
Bayesian statistics offers an alternative to classical (frequentist) statistics. It is distinguished by its use of probability distributions to describe uncertain quantities, which leads to elegant solutions to many difficult statistical problems. Although Bayesian demography, like Bayesian statistics more generally, is around 250 years old, only recently has it begun to flourish. The aim of this paper is to review the achievements of Bayesian demography, address some misconceptions, and make the case for wider use of Bayesian methods in population studies. We focus on three applications: demographic forecasts, limited data, and highly structured or complex models. The key advantages of Bayesian methods are the ability to integrate information from multiple sources and to describe uncertainty coherently. Bayesian methods also allow for including additional (prior) information next to the data sample. As such, Bayesian approaches are complementary to many traditional methods, which can be productively re-expressed in Bayesian terms. PMID:26902889
Bayesian demography 250 years after Bayes.
Bijak, Jakub; Bryant, John
2016-01-01
Bayesian statistics offers an alternative to classical (frequentist) statistics. It is distinguished by its use of probability distributions to describe uncertain quantities, which leads to elegant solutions to many difficult statistical problems. Although Bayesian demography, like Bayesian statistics more generally, is around 250 years old, only recently has it begun to flourish. The aim of this paper is to review the achievements of Bayesian demography, address some misconceptions, and make the case for wider use of Bayesian methods in population studies. We focus on three applications: demographic forecasts, limited data, and highly structured or complex models. The key advantages of Bayesian methods are the ability to integrate information from multiple sources and to describe uncertainty coherently. Bayesian methods also allow for including additional (prior) information next to the data sample. As such, Bayesian approaches are complementary to many traditional methods, which can be productively re-expressed in Bayesian terms.
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
Endels, Patrick; Adriaens, Dries; Bekker, Renee M.; Knevel, Irma C.; Decocq, Guillaume; Hermy, Martin
2007-01-01
Questions: 1. Do relationships among forest plant traits correspond to dispersability-persistence trade-offs or other intertrait correlations found in the literature? 2. Do species groups delineated by trait similarity, differ in occurrence in ancient vs. new forests or isolated vs more continuous f
Accounting And Forms Of Accountability In Ancient Civilizations: Mesopotamia And Ancient Egypt
SALVADOR CARMONA
2005-01-01
The aim of this paper is to identify the relevance and implications of ancient accounting practices to the contemporary theorizing of accounting. The paper provides a synthesis of the literature on ancient accounting particularly in relation to issues of human accountability, identifies its major achievements and outlines some of the key challenges facing researchers. We argue that far from being an idiosyncratic research field of marginal interest, research in ancient accounting is a rich an...
US Forest Service National Forest System Roads
US Forest Service, Department of Agriculture — A map service on the www depicting existing National Forest System Roads (NFSR) that are under the jurisdiction of the U.S. Forest Service. Each feature represents...
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.
Faience: the ceramic technology of ancient Egypt
Sparavigna, Amelia Carolina
2012-01-01
Faiences are ancient Egyptian ceramic materials, considered as "high-tech" products. The paper discussed the method by which the faiences were produced and the application of SEM and Raman spectroscopy to their analysis
NIMI TANTRA (Opthalmology of Ancient India)
Ramachandran, C.K.
1984-01-01
The art of opthalmology was well developed in ancient India and was known as Nimi Tantra. In this paper the author presents the main features of Nimi Tantra an authoritative treatises written by Nimi, a prominent opthalmologist of his time.
Ancient Magnetic Reversals: Clues to the Geodynamo.
Hoffman, Kenneth A.
1988-01-01
Discusses the question posed by some that the earth's magnetic field may reverse. States that rocks magnetized by ancient fields may offer clues to the underlying reversal mechanism in the earth's core. (TW)
Yi, Zhao; Dewan, Maneesh; Zhan, Yiqiang
2012-01-01
We describe Information Forests, an approach to classification that generalizes Random Forests by replacing the splitting criterion of non-leaf nodes from a discriminative one -- based on the entropy of the label distribution -- to a generative one -- based on maximizing the information divergence between the class-conditional distributions in the resulting partitions. The basic idea consists of deferring classification until a measure of "classification confidence" is sufficiently high, and instead breaking down the data so as to maximize this measure. In an alternative interpretation, Information Forests attempt to partition the data into subsets that are "as informative as possible" for the purpose of the task, which is to classify the data. Classification confidence, or informative content of the subsets, is quantified by the Information Divergence. Our approach relates to active learning, semi-supervised learning, mixed generative/discriminative learning.
Computationally efficient Bayesian inference for inverse problems.
Energy Technology Data Exchange (ETDEWEB)
Marzouk, Youssef M.; Najm, Habib N.; Rahn, Larry A.
2007-10-01
Bayesian statistics provides a foundation for inference from noisy and incomplete data, a natural mechanism for regularization in the form of prior information, and a quantitative assessment of uncertainty in the inferred results. Inverse problems - representing indirect estimation of model parameters, inputs, or structural components - can be fruitfully cast in this framework. Complex and computationally intensive forward models arising in physical applications, however, can render a Bayesian approach prohibitive. This difficulty is compounded by high-dimensional model spaces, as when the unknown is a spatiotemporal field. We present new algorithmic developments for Bayesian inference in this context, showing strong connections with the forward propagation of uncertainty. In particular, we introduce a stochastic spectral formulation that dramatically accelerates the Bayesian solution of inverse problems via rapid evaluation of a surrogate posterior. We also explore dimensionality reduction for the inference of spatiotemporal fields, using truncated spectral representations of Gaussian process priors. These new approaches are demonstrated on scalar transport problems arising in contaminant source inversion and in the inference of inhomogeneous material or transport properties. We also present a Bayesian framework for parameter estimation in stochastic models, where intrinsic stochasticity may be intermingled with observational noise. Evaluation of a likelihood function may not be analytically tractable in these cases, and thus several alternative Markov chain Monte Carlo (MCMC) schemes, operating on the product space of the observations and the parameters, are introduced.
Tactile length contraction as Bayesian inference.
Tong, Jonathan; Ngo, Vy; Goldreich, Daniel
2016-08-01
To perceive, the brain must interpret stimulus-evoked neural activity. This is challenging: The stochastic nature of the neural response renders its interpretation inherently uncertain. Perception would be optimized if the brain used Bayesian inference to interpret inputs in light of expectations derived from experience. Bayesian inference would improve perception on average but cause illusions when stimuli violate expectation. Intriguingly, tactile, auditory, and visual perception are all prone to length contraction illusions, characterized by the dramatic underestimation of the distance between punctate stimuli delivered in rapid succession; the origin of these illusions has been mysterious. We previously proposed that length contraction illusions occur because the brain interprets punctate stimulus sequences using Bayesian inference with a low-velocity expectation. A novel prediction of our Bayesian observer model is that length contraction should intensify if stimuli are made more difficult to localize. Here we report a tactile psychophysical study that tested this prediction. Twenty humans compared two distances on the forearm: a fixed reference distance defined by two taps with 1-s temporal separation and an adjustable comparison distance defined by two taps with temporal separation t ≤ 1 s. We observed significant length contraction: As t was decreased, participants perceived the two distances as equal only when the comparison distance was made progressively greater than the reference distance. Furthermore, the use of weaker taps significantly enhanced participants' length contraction. These findings confirm the model's predictions, supporting the view that the spatiotemporal percept is a best estimate resulting from a Bayesian inference process. PMID:27121574
Dimensionality reduction in Bayesian estimation algorithms
Directory of Open Access Journals (Sweden)
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.
Ancient Admixture in Human History
Patterson, Nick; Moorjani, Priya; Luo, Yontao; Mallick, Swapan; Rohland, Nadin; Zhan, Yiping; Genschoreck, Teri; Webster, Teresa; Reich, David
2012-01-01
Population mixture is an important process in biology. We present a suite of methods for learning about population mixtures, implemented in a software package called ADMIXTOOLS, that support formal tests for whether mixture occurred and make it possible to infer proportions and dates of mixture. We also describe the development of a new single nucleotide polymorphism (SNP) array consisting of 629,433 sites with clearly documented ascertainment that was specifically designed for population genetic analyses and that we genotyped in 934 individuals from 53 diverse populations. To illustrate the methods, we give a number of examples that provide new insights about the history of human admixture. The most striking finding is a clear signal of admixture into northern Europe, with one ancestral population related to present-day Basques and Sardinians and the other related to present-day populations of northeast Asia and the Americas. This likely reflects a history of admixture between Neolithic migrants and the indigenous Mesolithic population of Europe, consistent with recent analyses of ancient bones from Sweden and the sequencing of the genome of the Tyrolean “Iceman.” PMID:22960212
Ancient history of flatfish research
Berghahn, Rüdiger; Bennema, Floris Pieter
2013-01-01
Owing to both their special appearance and behavior flatfish have attracted the special attention of people since ages. The first records of humans having been in touch with flatfish date back to the Stone Age about 15,000 years B.C. Detailed descriptions were already given in the classical antiquity and were taken up 1400 years later in the Renaissance by the first ichthyologists, encyclopédists, and also by practical men. This was more than 200 years before a number of common flatfish species were given their scientific names by Linnaeus in 1758. Besides morphology, remarkable and sometimes amusing naturalistic observations and figures are bequeathed. Ancient history of flatfish research is still a wide and open array. Examples are presented how the yield of information and interpretation from these times increases with interdisciplinary cooperation including archeologists, zoologists, ichthyologists, historians, art historians, fisheries and fishery biologist. The timeline of this contribution ends with the start of modern fishery research at the end of the 19th century in the course of the rapidly increasing exploitation of fish stocks.
Rethinking the Ancient Sulfur Cycle
Fike, David A.; Bradley, Alexander S.; Rose, Catherine V.
2015-05-01
The sulfur biogeochemical cycle integrates the metabolic activity of multiple microbial pathways (e.g., sulfate reduction, disproportionation, and sulfide oxidation) along with abiotic reactions and geological processes that cycle sulfur through various reservoirs. The sulfur cycle impacts the global carbon cycle and climate primarily through the remineralization of organic carbon. Over geological timescales, cycling of sulfur is closely tied to the redox state of Earth's exosphere through the burial of oxidized (sulfate) and reduced (sulfide) sulfur species in marine sediments. Biological sulfur cycling is associated with isotopic fractionations that can be used to trace the fluxes through various metabolic pathways. The resulting isotopic data provide insights into sulfur cycling in both modern and ancient environments via isotopic signatures in sedimentary sulfate and sulfide phases. Here, we review the deep-time Î´34S record of marine sulfates and sulfides in light of recent advances in understanding how isotopic signatures are generated by microbial activity, how these signatures are encoded in marine sediments, and how they may be altered following deposition. The resulting picture shows a sulfur cycle intimately coupled to ambient carbon cycling, where sulfur isotopic records preserved in sedimentary rocks are critically dependent on sedimentological and geochemical conditions (e.g., iron availability) during deposition.
Surgical history of ancient China: Part 2.
Fu, Louis
2010-03-01
In this second part of ancient Chinese surgical history, the practice of bone setting in China began around 3000 years ago. Throughout this period, significant progress was made, some highlights of which are cited. These methods, comparable with Western orthopaedic technique, are still being practised today. In conclusion, the possible reasons for the lack of advancement in operative surgery are discussed, within context of the cultural, social and religious background of ancient China.
DEFF Research Database (Denmark)
Jacobs, Douglass F.; Oliet, Juan A.; Aronson, James;
2015-01-01
Forest loss and degradation is occurring at high rates but humankind is experiencing historical momentum that favors forest restoration. Approaches to restoration may follow various paradigms depending on stakeholder objectives, regional climate, or the degree of site degradation. The vast amount...... of land requiring restoration implies the need for spatial prioritization of restoration efforts according to cost-benefit analyses that include ecological risks. To design resistant and resilient ecosystems that can adapt to emerging circumstances, an adaptive management approach is needed. Global change...
Radiocarbon dating of ancient Japanese documents
Energy Technology Data Exchange (ETDEWEB)
Oda, H. [Nagoya Univ., Center for Chronological Research, Nagoya, Aichi (Japan)
2001-06-01
History is a reconstruction of past human activity, evidence of which is remained in the form of documents or relics. For the reconstruction of historic period, the radiocarbon dating of ancient documents provides important information. Although radiocarbon age is converted into calendar age with the calibration curve, the calibrated radiocarbon age is still different from the historical age when the document was written. The difference is known as 'old wood effect' for wooden cultural property. The discrepancy becomes more serious problem for recent sample which requires more accurate age determination. Using Tandetron accelerator mass spectrometer at Nagoya University, we have measured radiocarbon ages of Japanese ancient documents, sutras and printed books written dates of which are clarified from the paleographic standpoint. The purpose is to clarify the relation between calibrated radiocarbon age and historical age of ancient Japanese document by AMS radiocarbon dating. This paper reports 23 radiocarbon ages of ancient Japanese documents, sutras and printed books. The calibrated radiocarbon ages are in good agreement with the corresponding historical ages. It was shown by radiocarbon dating of the ancient documents that Japanese paper has little gap by 'old wood effect'; accordingly, ancient Japanese paper is a suitable sample for radiocarbon dating of recent historic period. (author)
Ancient Maya impacts on the Earth's surface: An Early Anthropocene analog?
Beach, Tim; Luzzadder-Beach, Sheryl; Cook, Duncan; Dunning, Nicholas; Kennett, Douglas J.; Krause, Samantha; Terry, Richard; Trein, Debora; Valdez, Fred
2015-09-01
The measure of the "Mayacene," a microcosm of the Early Anthropocene that occurred from c. 3000 to 1000 BP, comes from multiple Late Quaternary paleoenvironmental records. We synthesized the evidence for Maya impacts on climate, vegetation, hydrology and the lithosphere, from studies of soils, lakes, floodplains, wetlands and other ecosystems. Maya civilization had likely altered local to regional ecosystems and hydrology by the Preclassic Period (3000-1700 BP), but these impacts waned by 1000 BP. They altered ecosystems with vast urban and rural infrastructure that included thousands of reservoirs, wetland fields and canals, terraces, field ridges, and temples. Although there is abundant evidence that indicates the Maya altered their forests, even at the large urban complex of Tikal as much as 40% of the forest remained intact through the Classic period. Existing forests are still influenced by ancient Maya forest gardening, particularly by the large expanses of ancient stone structures, terraces, and wetland fields that form their substrates. A few studies suggest deforestation and other land uses probably also warmed and dried regional climate by the Classic Period (1700-1100 BP). A much larger body of research documents the Maya impacts on hydrology, in the form of dams, reservoirs, canals, eroded soils and urban design for runoff. Another metric of the "Mayacene" are paleosols, which contain chemical evidence for human occupation, revealed by high phosphorus concentrations and carbon isotope ratios of C4 species like maize in the C3-dominated tropical forest ecosystem. Paleosol sequences exhibit "Maya Clays," a facies that reflects a glut of rapidly eroded sediments that overlie pre-Maya paleosols. This stratigraphy is conspicuous in many dated soil profiles and marks the large-scale Maya transformation of the landscape in the Preclassic and Classic periods. Some of these also have increased phosphorous and carbon isotope evidence of C4 species. We synthesize
Bayesian Methods for Radiation Detection and Dosimetry
Groer, Peter G
2002-01-01
We performed work in three areas: radiation detection, external and internal radiation dosimetry. In radiation detection we developed Bayesian techniques to estimate the net activity of high and low activity radioactive samples. These techniques have the advantage that the remaining uncertainty about the net activity is described by probability densities. Graphs of the densities show the uncertainty in pictorial form. Figure 1 below demonstrates this point. We applied stochastic processes for a method to obtain Bayesian estimates of 222Rn-daughter products from observed counting rates. In external radiation dosimetry we studied and developed Bayesian methods to estimate radiation doses to an individual with radiation induced chromosome aberrations. We analyzed chromosome aberrations after exposure to gammas and neutrons and developed a method for dose-estimation after criticality accidents. The research in internal radiation dosimetry focused on parameter estimation for compartmental models from observed comp...
Adaptive approximate Bayesian computation for complex models
Lenormand, Maxime; Deffuant, Guillaume
2011-01-01
Approximate Bayesian computation (ABC) is a family of computational techniques in Bayesian statistics. These techniques allow to fit a model to data without relying on the computation of the model likelihood. They instead require to simulate a large number of times the model to be fitted. A number of refinements to the original rejection-based ABC scheme have been proposed, including the sequential improvement of posterior distributions. This technique allows to decrease the number of model simulations required, but it still presents several shortcomings which are particularly problematic for costly to simulate complex models. We here provide a new algorithm to perform adaptive approximate Bayesian computation, which is shown to perform better on both a toy example and a complex social model.
Learning Bayesian Networks from Correlated Data
Bae, Harold; Monti, Stefano; Montano, Monty; Steinberg, Martin H.; Perls, Thomas T.; Sebastiani, Paola
2016-05-01
Bayesian networks are probabilistic models that represent complex distributions in a modular way and have become very popular in many fields. There are many methods to build Bayesian networks from a random sample of independent and identically distributed observations. However, many observational studies are designed using some form of clustered sampling that introduces correlations between observations within the same cluster and ignoring this correlation typically inflates the rate of false positive associations. We describe a novel parameterization of Bayesian networks that uses random effects to model the correlation within sample units and can be used for structure and parameter learning from correlated data without inflating the Type I error rate. We compare different learning metrics using simulations and illustrate the method in two real examples: an analysis of genetic and non-genetic factors associated with human longevity from a family-based study, and an example of risk factors for complications of sickle cell anemia from a longitudinal study with repeated measures.
Bayesian Fusion of Multi-Band Images
Wei, Qi; Tourneret, Jean-Yves
2013-01-01
In this paper, a Bayesian fusion technique for remotely sensed multi-band images is presented. The observed images are related to the high spectral and high spatial resolution image to be recovered through physical degradations, e.g., spatial and spectral blurring and/or subsampling defined by the sensor characteristics. The fusion problem is formulated within a Bayesian estimation framework. An appropriate prior distribution exploiting geometrical consideration is introduced. To compute the Bayesian estimator of the scene of interest from its posterior distribution, a Markov chain Monte Carlo algorithm is designed to generate samples asymptotically distributed according to the target distribution. To efficiently sample from this high-dimension distribution, a Hamiltonian Monte Carlo step is introduced in the Gibbs sampling strategy. The efficiency of the proposed fusion method is evaluated with respect to several state-of-the-art fusion techniques. In particular, low spatial resolution hyperspectral and mult...
Bayesian Image Reconstruction Based on Voronoi Diagrams
Cabrera, G F; Hitschfeld, N
2007-01-01
We present a Bayesian Voronoi image reconstruction technique (VIR) for interferometric data. Bayesian analysis applied to the inverse problem allows us to derive the a-posteriori probability of a novel parameterization of interferometric images. We use a variable Voronoi diagram as our model in place of the usual fixed pixel grid. A quantization of the intensity field allows us to calculate the likelihood function and a-priori probabilities. The Voronoi image is optimized including the number of polygons as free parameters. We apply our algorithm to deconvolve simulated interferometric data. Residuals, restored images and chi^2 values are used to compare our reconstructions with fixed grid models. VIR has the advantage of modeling the image with few parameters, obtaining a better image from a Bayesian point of view.
Dynamic Bayesian Combination of Multiple Imperfect Classifiers
Simpson, Edwin; Psorakis, Ioannis; Smith, Arfon
2012-01-01
Classifier combination methods need to make best use of the outputs of multiple, imperfect classifiers to enable higher accuracy classifications. In many situations, such as when human decisions need to be combined, the base decisions can vary enormously in reliability. A Bayesian approach to such uncertain combination allows us to infer the differences in performance between individuals and to incorporate any available prior knowledge about their abilities when training data is sparse. In this paper we explore Bayesian classifier combination, using the computationally efficient framework of variational Bayesian inference. We apply the approach to real data from a large citizen science project, Galaxy Zoo Supernovae, and show that our method far outperforms other established approaches to imperfect decision combination. We go on to analyse the putative community structure of the decision makers, based on their inferred decision making strategies, and show that natural groupings are formed. Finally we present ...
Bayesian inference of the metazoan phylogeny
DEFF Research Database (Denmark)
Glenner, Henrik; Hansen, Anders J; Sørensen, Martin V;
2004-01-01
been the only feasible combined approach but is highly sensitive to long-branch attraction. Recent development of stochastic models for discrete morphological characters and computationally efficient methods for Bayesian inference has enabled combined molecular and morphological data analysis...... with rigorous statistical approaches less prone to such inconsistencies. We present the first statistically founded analysis of a metazoan data set based on a combination of morphological and molecular data and compare the results with a traditional parsimony analysis. Interestingly, the Bayesian analyses...... such as the ecdysozoans and lophotrochozoans. Parsimony, on the contrary, shows conflicting results, with morphology being congruent to the Bayesian results and the molecular data set producing peculiarities that are largely reflected in the combined analysis....
Variational Bayesian Inference of Line Spectra
DEFF Research Database (Denmark)
Badiu, Mihai Alin; Hansen, Thomas Lundgaard; Fleury, Bernard Henri
2016-01-01
In this paper, we address the fundamental problem of line spectral estimation in a Bayesian framework. We target model order and parameter estimation via variational inference in a probabilistic model in which the frequencies are continuous-valued, i.e., not restricted to a grid; and the coeffici......In this paper, we address the fundamental problem of line spectral estimation in a Bayesian framework. We target model order and parameter estimation via variational inference in a probabilistic model in which the frequencies are continuous-valued, i.e., not restricted to a grid......; and the coefficients are governed by a Bernoulli-Gaussian prior model turning model order selection into binary sequence detection. Unlike earlier works which retain only point estimates of the frequencies, we undertake a more complete Bayesian treatment by estimating the posterior probability density functions (pdfs...
Event generator tuning using Bayesian optimization
Ilten, Philip; Yang, Yunjie
2016-01-01
Monte Carlo event generators contain a large number of parameters that must be determined by comparing the output of the generator with experimental data. Generating enough events with a fixed set of parameter values to enable making such a comparison is extremely CPU intensive, which prohibits performing a simple brute-force grid-based tuning of the parameters. Bayesian optimization is a powerful method designed for such black-box tuning applications. In this article, we show that Monte Carlo event generator parameters can be accurately obtained using Bayesian optimization and minimal expert-level physics knowledge. A tune of the PYTHIA 8 event generator using $e^+e^-$ events, where 20 parameters are optimized, can be run on a modern laptop in just two days. Combining the Bayesian optimization approach with expert knowledge should enable producing better tunes in the future, by making it faster and easier to study discrepancies between Monte Carlo and experimental data.
Hessian PDF reweighting meets the Bayesian methods
Paukkunen, Hannu
2014-01-01
We discuss the Hessian PDF reweighting - a technique intended to estimate the effects that new measurements have on a set of PDFs. The method stems straightforwardly from considering new data in a usual $\\chi^2$-fit and it naturally incorporates also non-zero values for the tolerance, $\\Delta\\chi^2>1$. In comparison to the contemporary Bayesian reweighting techniques, there is no need to generate large ensembles of PDF Monte-Carlo replicas, and the observables need to be evaluated only with the central and the error sets of the original PDFs. In spite of the apparently rather different methodologies, we find that the Hessian and the Bayesian techniques are actually equivalent if the $\\Delta\\chi^2$ criterion is properly included to the Bayesian likelihood function that is a simple exponential.
A Large Sample Study of the Bayesian Bootstrap
Lo, Albert Y.
1987-01-01
An asymptotic justification of the Bayesian bootstrap is given. Large-sample Bayesian bootstrap probability intervals for the mean, the variance and bands for the distribution, the smoothed density and smoothed rate function are also provided.
1992-01-01
NASA's Technology Applications Center, with other government and academic agencies, provided technology for improved resources management to the Cibola National Forest. Landsat satellite images enabled vegetation over a large area to be classified for purposes of timber analysis, wildlife habitat, range measurement and development of general vegetation maps.
Bose, Purabi; Dijk, van Han
2016-01-01
This volume provides new insights and conceptual understandings of the human and gender dimension of vulnerability in relation to the dynamics of tenure reforms in the dryland forests of Asia and Africa. The book analyzes the interaction between biophysical factors such as climate variability (e.
Length Scales in Bayesian Automatic Adaptive Quadrature
Directory of Open Access Journals (Sweden)
Adam Gh.
2016-01-01
Full Text Available Two conceptual developments in the Bayesian automatic adaptive quadrature approach to the numerical solution of one-dimensional Riemann integrals [Gh. Adam, S. Adam, Springer LNCS 7125, 1–16 (2012] are reported. First, it is shown that the numerical quadrature which avoids the overcomputing and minimizes the hidden floating point loss of precision asks for the consideration of three classes of integration domain lengths endowed with specific quadrature sums: microscopic (trapezoidal rule, mesoscopic (Simpson rule, and macroscopic (quadrature sums of high algebraic degrees of precision. Second, sensitive diagnostic tools for the Bayesian inference on macroscopic ranges, coming from the use of Clenshaw-Curtis quadrature, are derived.
Bayesian estimation and tracking a practical guide
Haug, Anton J
2012-01-01
A practical approach to estimating and tracking dynamic systems in real-worl applications Much of the literature on performing estimation for non-Gaussian systems is short on practical methodology, while Gaussian methods often lack a cohesive derivation. Bayesian Estimation and Tracking addresses the gap in the field on both accounts, providing readers with a comprehensive overview of methods for estimating both linear and nonlinear dynamic systems driven by Gaussian and non-Gaussian noices. Featuring a unified approach to Bayesian estimation and tracking, the book emphasizes the derivation
Bayesian Optimisation Algorithm for Nurse Scheduling
Li, Jingpeng
2008-01-01
Our research has shown that schedules can be built mimicking a human scheduler by using a set of rules that involve domain knowledge. This chapter presents a Bayesian Optimization Algorithm (BOA) for the nurse scheduling problem that chooses such suitable scheduling rules from a set for each nurses assignment. Based on the idea of using probabilistic models, the BOA builds a Bayesian network for the set of promising solutions and samples these networks to generate new candidate solutions. Computational results from 52 real data instances demonstrate the success of this approach. It is also suggested that the learning mechanism in the proposed algorithm may be suitable for other scheduling problems.
A Bayesian Analysis of Spectral ARMA Model
Directory of Open Access Journals (Sweden)
Manoel I. Silvestre Bezerra
2012-01-01
Full Text Available Bezerra et al. (2008 proposed a new method, based on Yule-Walker equations, to estimate the ARMA spectral model. In this paper, a Bayesian approach is developed for this model by using the noninformative prior proposed by Jeffreys (1967. The Bayesian computations, simulation via Markov Monte Carlo (MCMC is carried out and characteristics of marginal posterior distributions such as Bayes estimator and confidence interval for the parameters of the ARMA model are derived. Both methods are also compared with the traditional least squares and maximum likelihood approaches and a numerical illustration with two examples of the ARMA model is presented to evaluate the performance of the procedures.
A Bayesian Concept Learning Approach to Crowdsourcing
DEFF Research Database (Denmark)
Viappiani, Paolo Renato; Zilles, Sandra; Hamilton, Howard J.;
2011-01-01
We develop a Bayesian approach to concept learning for crowdsourcing applications. A probabilistic belief over possible concept definitions is maintained and updated according to (noisy) observations from experts, whose behaviors are modeled using discrete types. We propose recommendation...... techniques, inference methods, and query selection strategies to assist a user charged with choosing a configuration that satisfies some (partially known) concept. Our model is able to simultaneously learn the concept definition and the types of the experts. We evaluate our model with simulations, showing...... that our Bayesian strategies are effective even in large concept spaces with many uninformative experts....
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...
Burns treatment in ancient times.
Pećanac, Marija; Janjić, Zlata; Komarcević, Aleksandar; Pajić, Milos; Dobanovacki, Dusanka; Misković, Sanja Skeledzija
2013-01-01
Discovery of fire at the dawn of prehistoric time brought not only the benefits to human beings offering the light and heat, but also misfortune due to burns; and that was the beginning of burns treatment. Egyptian doctors made medicines from plants, animal products and minerals, which they combined with magic and religious procedures. The earliest records described burns dressings with milk from mothers of male babies. Goddess Isis was called upon to help. Some remedies and procedures proved so successful that their application continued for centuries. The Edwin Smith papyrus (1500 BC) mentioned the treatment of burns with honey and grease. Ebers Papyrus (1500 BC) contains descriptions of application of mud, excrement, oil and plant extracts. They also used honey, Aloe and tannic acid to heal burns. Ancient Egyptians did not know about microorganisms but they knew that honey, moldy bread and copper salts could prevent infections from dirt in burns healing. Thyme, opium and belladona were used for pain relief. In the 4th century BC, Hippocrates recorded that Greek and Roman doctors used rendered pig fat, resin and bitumen to treat burns. Mixture of honey and bran, or lotion of wine and myrrh were used by Celsus. Honey was also known in Ayurveda (Indian medicine) time. Ayurvedic records Characa and Sushruta included honey in their dressing aids to purify sores and promote the healing. Burn treatment in Chinese medicine was traditional. It was a compilation of philosophy, knowledge and herbal medicine. The successful treatment of burns started in recent time and it has been made possible by better knowledge of the pathophysiology of thermal injuries and their consequences, medical technology advances and improved surgical techniques. PMID:23888738
Burns treatment in ancient times.
Pećanac, Marija; Janjić, Zlata; Komarcević, Aleksandar; Pajić, Milos; Dobanovacki, Dusanka; Misković, Sanja Skeledzija
2013-01-01
Discovery of fire at the dawn of prehistoric time brought not only the benefits to human beings offering the light and heat, but also misfortune due to burns; and that was the beginning of burns treatment. Egyptian doctors made medicines from plants, animal products and minerals, which they combined with magic and religious procedures. The earliest records described burns dressings with milk from mothers of male babies. Goddess Isis was called upon to help. Some remedies and procedures proved so successful that their application continued for centuries. The Edwin Smith papyrus (1500 BC) mentioned the treatment of burns with honey and grease. Ebers Papyrus (1500 BC) contains descriptions of application of mud, excrement, oil and plant extracts. They also used honey, Aloe and tannic acid to heal burns. Ancient Egyptians did not know about microorganisms but they knew that honey, moldy bread and copper salts could prevent infections from dirt in burns healing. Thyme, opium and belladona were used for pain relief. In the 4th century BC, Hippocrates recorded that Greek and Roman doctors used rendered pig fat, resin and bitumen to treat burns. Mixture of honey and bran, or lotion of wine and myrrh were used by Celsus. Honey was also known in Ayurveda (Indian medicine) time. Ayurvedic records Characa and Sushruta included honey in their dressing aids to purify sores and promote the healing. Burn treatment in Chinese medicine was traditional. It was a compilation of philosophy, knowledge and herbal medicine. The successful treatment of burns started in recent time and it has been made possible by better knowledge of the pathophysiology of thermal injuries and their consequences, medical technology advances and improved surgical techniques.
Artificial Neural Network Modeling of Forest Tree Growth
Gordon, C
1999-01-01
The problem of modeling forest tree growth curves with an artificial neural network (NN) is examined. The NN parametric form is shown to be a suitable model if each forest tree plot is assumed to consist of several differently growing sub-plots. The predictive Bayesian approach is used in estimating the NN output. Data from the correlated curve trend (CCT) experiments are used. The NN predictions are compared with those of one of the best parametric solutions, the Schnute model. Analysis of variance (ANOVA) methods are used to evaluate whether any observed differences are statistically significant. From a Frequentist perspective the differences between the Schnute and NN approach are found not to be significant. However, a Bayesian ANOVA indicates that there is a 93% probability of the NN approach producing better predictions on average.
A Fast Iterative Bayesian Inference Algorithm for Sparse Channel Estimation
DEFF Research Database (Denmark)
Pedersen, Niels Lovmand; Manchón, Carles Navarro; Fleury, Bernard Henri
2013-01-01
representation of the Bessel K probability density function; a highly efficient, fast iterative Bayesian inference method is then applied to the proposed model. The resulting estimator outperforms other state-of-the-art Bayesian and non-Bayesian estimators, either by yielding lower mean squared estimation error...
A default Bayesian hypothesis test for ANOVA designs
R. Wetzels; R.P.P.P. Grasman; E.J. Wagenmakers
2012-01-01
This article presents a Bayesian hypothesis test for analysis of variance (ANOVA) designs. The test is an application of standard Bayesian methods for variable selection in regression models. We illustrate the effect of various g-priors on the ANOVA hypothesis test. The Bayesian test for ANOVA desig
A Gentle Introduction to Bayesian Analysis : Applications to Developmental Research
Van de Schoot, Rens; Kaplan, David; Denissen, Jaap; Asendorpf, Jens B.; Neyer, Franz J.; van Aken, Marcel A G
2014-01-01
Bayesian statistical methods are becoming ever more popular in applied and fundamental research. In this study a gentle introduction to Bayesian analysis is provided. It is shown under what circumstances it is attractive to use Bayesian estimation, and how to interpret properly the results. First, t
Bayesian Just-So Stories in Psychology and Neuroscience
Bowers, Jeffrey S.; Davis, Colin J.
2012-01-01
According to Bayesian theories in psychology and neuroscience, minds and brains are (near) optimal in solving a wide range of tasks. We challenge this view and argue that more traditional, non-Bayesian approaches are more promising. We make 3 main arguments. First, we show that the empirical evidence for Bayesian theories in psychology is weak.…
Genetic diversity among ancient Nordic populations.
Melchior, Linea; Lynnerup, Niels; Siegismund, Hans R; Kivisild, Toomas; Dissing, Jørgen
2010-01-01
Using established criteria for work with fossil DNA we have analysed mitochondrial DNA from 92 individuals from 18 locations in Denmark ranging in time from the Mesolithic to the Medieval Age. Unequivocal assignment of mtDNA haplotypes was possible for 56 of the ancient individuals; however, the success rate varied substantially between sites; the highest rates were obtained with untouched, freshly excavated material, whereas heavy handling, archeological preservation and storage for many years influenced the ability to obtain authentic endogenic DNA. While the nucleotide diversity at two locations was similar to that among extant Danes, the diversity at four sites was considerably higher. This supports previous observations for ancient Britons. The overall occurrence of haplogroups did not deviate from extant Scandinavians, however, haplogroup I was significantly more frequent among the ancient Danes (average 13%) than among extant Danes and Scandinavians (approximately 2.5%) as well as among other ancient population samples reported. Haplogroup I could therefore have been an ancient Southern Scandinavian type "diluted" by later immigration events. Interestingly, the two Neolithic samples (4,200 YBP, Bell Beaker culture) that were typed were haplogroup U4 and U5a, respectively, and the single Bronze Age sample (3,300-3,500 YBP) was haplogroup U4. These two haplogroups have been associated with the Mesolithic populations of Central and Northern Europe. Therefore, at least for Southern Scandinavia, our findings do not support a possible replacement of a haplogroup U dominated hunter-gatherer population by a more haplogroup diverse Neolithic Culture.
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
The Ancient Martian Climate System
Haberle, Robert M.
2014-01-01
Today Mars is a cold, dry, desert planet. The atmosphere is thin and liquid water is not stable. But there is evidence that very early in its history it was warmer and wetter. Since Mariner 9 first detected fluvial features on its ancient terrains researchers have been trying to understand what climatic conditions could have permitted liquid water to flow on the surface. Though the evidence is compelling, the problem is not yet solved. The main issue is coping with the faint young sun. During the period when warmer conditions prevailed 3.5-3.8 Gy the sun's luminosity was approximately 25% less than it is today. How can we explain the presence of liquid water on the surface of Mars under such conditions? A similar problem exists for Earth, which would have frozen over under a faint sun even though the evidence suggests otherwise. Attempts to solve the "Faint Young Sun Paradox" rely on greenhouse warming from an atmosphere with a different mass and composition than we see today. This is true for both Mars and Earth. However, it is not a straightforward solution. Any greenhouse theory must (a) produce the warming and rainfall needed, (b) have a plausible source for the gases required, (c) be sustainable, and (d) explain how the atmosphere evolved to its present state. These are challenging requirements and judging from the literature they have yet to be met. In this talk I will review the large and growing body of work on the early Mars climate system. I will take a holistic approach that involves many disciplines since our goal is to present an integrated view that touches on each of the requirements listed in the preceding paragraph. I will begin with the observational evidence, which comes from the geology, mineralogy, and isotopic data. Each of the data sets presents a consistent picture of a warmer and wetter past with a thicker atmosphere. How much warmer and wetter and how much thicker is a matter of debate, but conditions then were certainly different than
Most frugal explanations in Bayesian networks
Kwisthout, J.H.P.
2015-01-01
Inferring the most probable explanation to a set of variables, given a partial observation of the remaining variables, is one of the canonical computational problems in Bayesian networks, with widespread applications in AI and beyond. This problem, known as MAP, is computationally intractable (NP-ha
Bayesian semiparametric dynamic Nelson-Siegel model
C. Cakmakli
2011-01-01
This paper proposes the Bayesian semiparametric dynamic Nelson-Siegel model where the density of the yield curve factors and thereby the density of the yields are estimated along with other model parameters. This is accomplished by modeling the error distributions of the factors according to a Diric
Von Neumann was not a Quantum Bayesian.
Stacey, Blake C
2016-05-28
Wikipedia has claimed for over 3 years now that John von Neumann was the 'first quantum Bayesian'. In context, this reads as stating that von Neumann inaugurated QBism, the approach to quantum theory promoted by Fuchs, Mermin and Schack. This essay explores how such a claim is, historically speaking, unsupported. PMID:27091166
Von Neumann Was Not a Quantum Bayesian
Blake C. Stacey
2014-01-01
Wikipedia has claimed for over three years now that John von Neumann was the "first quantum Bayesian." In context, this reads as stating that von Neumann inaugurated QBism, the approach to quantum theory promoted by Fuchs, Mermin and Schack. This essay explores how such a claim is, historically speaking, unsupported.
A Bayesian Approach to Interactive Retrieval
Tague, Jean M.
1973-01-01
A probabilistic model for interactive retrieval is presented. Bayesian statistical decision theory principles are applied: use of prior and sample information about the relationship of document descriptions to query relevance; maximization of expected value of a utility function, to the problem of optimally restructuring search strategies in an…
Bayesian regularization of diffusion tensor images
DEFF Research Database (Denmark)
Frandsen, Jesper; Hobolth, Asger; Østergaard, Leif;
2007-01-01
several directions. The measured diffusion coefficients and thereby the diffusion tensors are subject to noise, leading to possibly flawed representations of the three dimensional fibre bundles. In this paper we develop a Bayesian procedure for regularizing the diffusion tensor field, fully utilizing...
Inverse Problems in a Bayesian Setting
Matthies, Hermann G.
2016-02-13
In a Bayesian setting, inverse problems and uncertainty quantification (UQ)—the propagation of uncertainty through a computational (forward) model—are strongly connected. In the form of conditional expectation the Bayesian update becomes computationally attractive. We give a detailed account of this approach via conditional approximation, various approximations, and the construction of filters. Together with a functional or spectral approach for the forward UQ there is no need for time-consuming and slowly convergent Monte Carlo sampling. The developed sampling-free non-linear Bayesian update in form of a filter is derived from the variational problem associated with conditional expectation. This formulation in general calls for further discretisation to make the computation possible, and we choose a polynomial approximation. After giving details on the actual computation in the framework of functional or spectral approximations, we demonstrate the workings of the algorithm on a number of examples of increasing complexity. At last, we compare the linear and nonlinear Bayesian update in form of a filter on some examples.
Comprehension and computation in Bayesian problem solving
Directory of Open Access Journals (Sweden)
Eric D. Johnson
2015-07-01
Full Text Available Humans have long been characterized as poor probabilistic reasoners when presented with explicit numerical information. Bayesian word problems provide a well-known example of this, where even highly educated and cognitively skilled individuals fail to adhere to mathematical norms. It is widely agreed that natural frequencies can facilitate Bayesian reasoning relative to normalized formats (e.g. probabilities, percentages, both by clarifying logical set-subset relations and by simplifying numerical calculations. Nevertheless, between-study performance on transparent Bayesian problems varies widely, and generally remains rather unimpressive. We suggest there has been an over-focus on this representational facilitator (i.e. transparent problem structures at the expense of the specific logical and numerical processing requirements and the corresponding individual abilities and skills necessary for providing Bayesian-like output given specific verbal and numerical input. We further suggest that understanding this task-individual pair could benefit from considerations from the literature on mathematical cognition, which emphasizes text comprehension and problem solving, along with contributions of online executive working memory, metacognitive regulation, and relevant stored knowledge and skills. We conclude by offering avenues for future research aimed at identifying the stages in problem solving at which correct versus incorrect reasoners depart, and how individual difference might influence this time point.
Bayesian Vector Autoregressions with Stochastic Volatility
Uhlig, H.F.H.V.S.
1996-01-01
This paper proposes a Bayesian approach to a vector autoregression with stochastic volatility, where the multiplicative evolution of the precision matrix is driven by a multivariate beta variate.Exact updating formulas are given to the nonlinear filtering of the precision matrix.Estimation of the au
Scaling Bayesian network discovery through incremental recovery
Castelo, J.R.; Siebes, A.P.J.M.
1999-01-01
Bayesian networks are a type of graphical models that, e.g., allow one to analyze the interaction among the variables in a database. A well-known problem with the discovery of such models from a database is the ``problem of high-dimensionality''. That is, the discovery of a network from a database w
A Bayesian Bootstrap for a Finite Population
Lo, Albert Y.
1988-01-01
A Bayesian bootstrap for a finite population is introduced; its small-sample distributional properties are discussed and compared with those of the frequentist bootstrap for a finite population. It is also shown that the two are first-order asymptotically equivalent.
Bayesian calibration for forensic age estimation.
Ferrante, Luigi; Skrami, Edlira; Gesuita, Rosaria; Cameriere, Roberto
2015-05-10
Forensic medicine is increasingly called upon to assess the age of individuals. Forensic age estimation is mostly required in relation to illegal immigration and identification of bodies or skeletal remains. A variety of age estimation methods are based on dental samples and use of regression models, where the age of an individual is predicted by morphological tooth changes that take place over time. From the medico-legal point of view, regression models, with age as the dependent random variable entail that age tends to be overestimated in the young and underestimated in the old. To overcome this bias, we describe a new full Bayesian calibration method (asymmetric Laplace Bayesian calibration) for forensic age estimation that uses asymmetric Laplace distribution as the probability model. The method was compared with three existing approaches (two Bayesian and a classical method) using simulated data. Although its accuracy was comparable with that of the other methods, the asymmetric Laplace Bayesian calibration appears to be significantly more reliable and robust in case of misspecification of the probability model. The proposed method was also applied to a real dataset of values of the pulp chamber of the right lower premolar measured on x-ray scans of individuals of known age. PMID:25645903
Exploiting structure in cooperative Bayesian games
F.A. Oliehoek; S. Whiteson; M.T.J. Spaan
2012-01-01
Cooperative Bayesian games (BGs) can model decision-making problems for teams of agents under imperfect information, but require space and computation time that is exponential in the number of agents. While agent independence has been used to mitigate these problems in perfect information settings,
Perfect Bayesian equilibrium. Part II: epistemic foundations
Bonanno, Giacomo
2011-01-01
In a companion paper we introduced a general notion of perfect Bayesian equilibrium which can be applied to arbitrary extensive-form games. The essential ingredient of the proposed definition is the qualitative notion of AGM-consistency. In this paper we provide an epistemic foundation for AGM-consistency based on the AGM theory of belief revision.
Decision generation tools and Bayesian inference
Jannson, Tomasz; Wang, Wenjian; Forrester, Thomas; Kostrzewski, Andrew; Veeris, Christian; Nielsen, Thomas
2014-05-01
Digital Decision Generation (DDG) tools are important software sub-systems of Command and Control (C2) systems and technologies. In this paper, we present a special type of DDGs based on Bayesian Inference, related to adverse (hostile) networks, including such important applications as terrorism-related networks and organized crime ones.
Von Neumann Was Not a Quantum Bayesian
Stacey, Blake C
2014-01-01
Wikipedia has claimed for over two years now that John von Neumann was the "first quantum Bayesian." In context, this reads as stating that von Neumann inaugurated QBism, the approach to quantum theory promoted by Fuchs, Mermin and Schack. This essay explores how such a claim is, historically speaking, unsupported.
Bayesian calibration of car-following models
Van Hinsbergen, C.P.IJ.; Van Lint, H.W.C.; Hoogendoorn, S.P.; Van Zuylen, H.J.
2010-01-01
Recent research has revealed that there exist large inter-driver differences in car-following behavior such that different car-following models may apply to different drivers. This study applies Bayesian techniques to the calibration of car-following models, where prior distributions on each model p
Basics of Bayesian Learning - Basically Bayes
DEFF Research Database (Denmark)
Larsen, Jan
Tutorial presented at the IEEE Machine Learning for Signal Processing Workshop 2006, Maynooth, Ireland, September 8, 2006. The tutorial focuses on the basic elements of Bayesian learning and its relation to classical learning paradigms. This includes a critical discussion of the pros and cons...
On local optima in learning bayesian networks
DEFF Research Database (Denmark)
Dalgaard, Jens; Kocka, Tomas; Pena, Jose
2003-01-01
This paper proposes and evaluates the k-greedy equivalence search algorithm (KES) for learning Bayesian networks (BNs) from complete data. The main characteristic of KES is that it allows a trade-off between greediness and randomness, thus exploring different good local optima. When greediness...
Bayesian Estimation Supersedes the "t" Test
Kruschke, John K.
2013-01-01
Bayesian estimation for 2 groups provides complete distributions of credible values for the effect size, group means and their difference, standard deviations and their difference, and the normality of the data. The method handles outliers. The decision rule can accept the null value (unlike traditional "t" tests) when certainty in the estimate is…
Bayesian Estimation of Thermonuclear Reaction Rates
Iliadis, Christian; Coc, Alain; Timmes, Frank; Starrfield, Sumner
2016-01-01
The problem of estimating non-resonant astrophysical S-factors and thermonuclear reaction rates, based on measured nuclear cross sections, is of major interest for nuclear energy generation, neutrino physics, and element synthesis. Many different methods have been applied in the past to this problem, all of them based on traditional statistics. Bayesian methods, on the other hand, are now in widespread use in the physical sciences. In astronomy, for example, Bayesian statistics is applied to the observation of extra-solar planets, gravitational waves, and type Ia supernovae. However, nuclear physics, in particular, has been slow to adopt Bayesian methods. We present the first astrophysical S-factors and reaction rates based on Bayesian statistics. We develop a framework that incorporates robust parameter estimation, systematic effects, and non-Gaussian uncertainties in a consistent manner. The method is applied to the d(p,$\\gamma$)$^3$He, $^3$He($^3$He,2p)$^4$He, and $^3$He($\\alpha$,$\\gamma$)$^7$Be reactions,...
Bayesian analysis of Markov point processes
DEFF Research Database (Denmark)
Berthelsen, Kasper Klitgaard; Møller, Jesper
2006-01-01
Recently Møller, Pettitt, Berthelsen and Reeves introduced a new MCMC methodology for drawing samples from a posterior distribution when the likelihood function is only specified up to a normalising constant. We illustrate the method in the setting of Bayesian inference for Markov point processes...
Bayesian Averaging is Well-Temperated
DEFF Research Database (Denmark)
Hansen, Lars Kai
2000-01-01
Bayesian predictions are stochastic just like predictions of any other inference scheme that generalize from a finite sample. While a simple variational argument shows that Bayes averaging is generalization optimal given that the prior matches the teacher parameter distribution the situation...
Modelling crime linkage with Bayesian networks
J. de Zoete; M. Sjerps; D. Lagnado; N. Fenton
2015-01-01
When two or more crimes show specific similarities, such as a very distinct modus operandi, the probability that they were committed by the same offender becomes of interest. This probability depends on the degree of similarity and distinctiveness. We show how Bayesian networks can be used to model
Directory of Open Access Journals (Sweden)
S Elizabeth Alter
Full Text Available Commercial whaling decimated many whale populations, including the eastern Pacific gray whale, but little is known about how population dynamics or ecology differed prior to these removals. Of particular interest is the possibility of a large population decline prior to whaling, as such a decline could explain the ~5-fold difference between genetic estimates of prior abundance and estimates based on historical records. We analyzed genetic (mitochondrial control region and isotopic information from modern and prehistoric gray whales using serial coalescent simulations and Bayesian skyline analyses to test for a pre-whaling decline and to examine prehistoric genetic diversity, population dynamics and ecology. Simulations demonstrate that significant genetic differences observed between ancient and modern samples could be caused by a large, recent population bottleneck, roughly concurrent with commercial whaling. Stable isotopes show minimal differences between modern and ancient gray whale foraging ecology. Using rejection-based Approximate Bayesian Computation, we estimate the size of the population bottleneck at its minimum abundance and the pre-bottleneck abundance. Our results agree with previous genetic studies suggesting the historical size of the eastern gray whale population was roughly three to five times its current size.
Computational statistics using the Bayesian Inference Engine
Weinberg, Martin D.
2013-09-01
This paper introduces the Bayesian Inference Engine (BIE), a general parallel, optimized software package for parameter inference and model selection. This package is motivated by the analysis needs of modern astronomical surveys and the need to organize and reuse expensive derived data. The BIE is the first platform for computational statistics designed explicitly to enable Bayesian update and model comparison for astronomical problems. Bayesian update is based on the representation of high-dimensional posterior distributions using metric-ball-tree based kernel density estimation. Among its algorithmic offerings, the BIE emphasizes hybrid tempered Markov chain Monte Carlo schemes that robustly sample multimodal posterior distributions in high-dimensional parameter spaces. Moreover, the BIE implements a full persistence or serialization system that stores the full byte-level image of the running inference and previously characterized posterior distributions for later use. Two new algorithms to compute the marginal likelihood from the posterior distribution, developed for and implemented in the BIE, enable model comparison for complex models and data sets. Finally, the BIE was designed to be a collaborative platform for applying Bayesian methodology to astronomy. It includes an extensible object-oriented and easily extended framework that implements every aspect of the Bayesian inference. By providing a variety of statistical algorithms for all phases of the inference problem, a scientist may explore a variety of approaches with a single model and data implementation. Additional technical details and download details are available from http://www.astro.umass.edu/bie. The BIE is distributed under the GNU General Public License.
The ancient Chinese notes on hydrogeology
Zhou, Yu; Zwahlen, François; Wang, Yanxin
2011-08-01
The ancient Chinese notes on hydrogeology are summarized and interpreted, along with records of some related matters, like groundwater exploration and utilization, karst springs, water circulation, water conservation and saline-land transformation, mine drainage, and environmental hydrogeology. The report focuses only on the earliest recorded notes, mostly up until the Han Dynasty (206 BC - AD 25). Besides the references cited, the discussion in this report is based mainly on archaeological material, the preserved written classic literature, and some assumptions and/or conclusions that have been handed down in legends to later ages. Although most material relates to ancient China, the lessons learned may have practical significance worldwide. Compared to other contemporary parts of the world, ancient China, without doubt, took the lead in the field of groundwater hydrology. The great achievements and experience of the Chinese ancestors should provide motivation and inspiration for hydrogeologists to carry out their scientific research and exploration passionately and actively.
The Vindolanda Tablets and the Ancient Economy
DEFF Research Database (Denmark)
Evers, Kasper Grønlund
, a model is outlined which takes into account the different economic behaviours revealed by the tablets and attempts to fit them together into one coherent, economic system, whilst also relating the activities to questions of scale in the ancient economy; moreover, the conclusions drawn in the study......, the aim is to investigate how best to comprehend the economic system attested at Vindolanda and to consider the wider implications for studies of the ancient economy in general. This is accomplished by a three-step approach: first, the nature of the Vindolandan evidence is assessed, and the state...... of research on both studies of the ancient economy and the economy of early Roman Britain is accounted for, so as to highlight the value of the Vindolanda Tablets and lay the ground for the interpretations which follow. Secondly, the economic activities attested by the tablets are analysed in terms of market...
Twins in Ancient Greece: a synopsis.
Malamitsi-Puchner, Ariadne
2016-01-01
This brief outline associates twins with several aspects of life in Ancient Greece. In Greek mythology twins caused ambivalent reactions and were believed to have ambivalent feelings for each other. Very often, they were viewed as the representatives of the dualistic nature of the universe. Heteropaternal superfecundation, which dominates in ancient myths, explains on one hand, the god-like qualities and, on the other hand, the mortal nature of many twins. An assumption is presented that legends referring to twins might reflect the territorial expansions of Ancient Greeks in Northern Mediterranean, around the Black Sea, in Asia Minor, as well as North East Africa. In conclusion, in Greek antiquity, twins have been used as transitional figures between myth and reality. PMID:26135766
Did the ancient egyptians discover Algol?
Jetsu, L.; Porceddu, S.; Porceddu, S.; Lyytinen, J.; Kajatkari, P.; Markkanen, T.; Toivari-Viitala, J.
2013-02-01
Fabritius discovered the first variable star, Mira, in 1596. Holwarda determined the 11 months period of Mira in 1638. Montanari discovered the next variable star, Algol, in 1669. Its period, 2.867 days, was determined by Goodricke (178). Algol was associated with demon-like creatures, "Gorgon" in ancient Greek and "ghoul" in ancient Arab mythology. This indicates that its variability was discovered much before 1669 (Wilk 1996), but this mythological evidence is ambiguous (Davis 1975). For thousands of years, the Ancient Egyptian Scribes (AES) observed stars for timekeeping in a region, where there are nearly 300 clear nights a year. We discovered a significant periodicity of 2.850 days in their calendar for lucky and unlucky days dated to 1224 BC, "the Cairo Calendar". Several astrophysical and astronomical tests supported our conclusion that this was the period of Algol three millennia ago. The "ghoulish habits" of Algol could explain this 0.017 days period increase (Battersby 2012).
PIXE ANALYSIS ON AN ANCIENT SCROLL SAMPLE
Energy Technology Data Exchange (ETDEWEB)
Shutthanandan, V.; Thevuthasan, Suntharampillai; Iuliano, Edward M.; Seales, William B.
2008-12-01
For years, scientists have developed several new techniques to read texts of Herculaneum scrolls without destroying them. Recently, the use of a custom built high-resolution CT scanner was proposed to scan and then virtually unroll the scrolls for reading. Identification of any unique chemical signatures in the ancient ink would allow better calibration of the CT scanner to improve the chances of resolving the ink from the burned papyrus background. To support this effort, we carried out one pilot study to see whether the composition of the ink can be obtained from an ancient scroll sample using PIXE technique. PIXE data were collected and analyzed in two different regions of the ancient scroll sample (ink and blank regions). This preliminary work shows that elemental distributions from the ink used in this scroll mainly contained Al, Fe and Ti as well as minor trace amounts of Cr, Cu and Zn.
Palaeoparasitology - Human Parasites in Ancient Material.
Araújo, Adauto; Reinhard, Karl; Ferreira, Luiz Fernando
2015-01-01
Parasite finds in ancient material launched a new field of science: palaeoparasitology. Ever since the pioneering studies, parasites were identified in archaeological and palaeontological remains, some preserved for millions of years by fossilization. However, the palaeoparasitological record consists mainly of parasites found specifically in human archaeological material, preserved in ancient occupation sites, from prehistory until closer to 2015. The results include some helminth intestinal parasites still commonly found in 2015, such as Ascaris lumbricoides, Trichuris trichiura and hookworms, besides others such as Amoebidae and Giardia intestinalis, as well as viruses, bacteria, fungi and arthropods. These parasites as a whole provide important data on health, diet, climate and living conditions among ancient populations. This chapter describes the principal findings and their importance for knowledge on the origin and dispersal of infectious diseases.
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...
Will Passive Protection Save Congo Forests?
Galford, Gillian L; Soares-Filho, Britaldo S; Sonter, Laura J; Laporte, Nadine
2015-01-01
Central Africa's tropical forests are among the world's largest carbon reserves. Historically, they have experienced low rates of deforestation. Pressures to clear land are increasing due to development of infrastructure and livelihoods, foreign investment in agriculture, and shifting land use management, particularly in the Democratic Republic of Congo (DRC). The DRC contains the greatest area of intact African forests. These store approximately 22 billion tons of carbon in aboveground live biomass, yet only 10% are protected. Can the status quo of passive protection - forest management that is low or nonexistent - ensure the preservation of this forest and its carbon? We have developed the SimCongo model to simulate changes in land cover and land use based on theorized policy scenarios from 2010 to 2050. Three scenarios were examined: the first (Historical Trends) assumes passive forest protection; the next (Conservation) posits active protection of forests and activation of the national REDD+ action plan, and the last (Agricultural Development) assumes increased agricultural activities in forested land with concomitant increased deforestation. SimCongo is a cellular automata model based on Bayesian statistical methods tailored for the DRC, built with the Dinamica-EGO platform. The model is parameterized and validated with deforestation observations from the past and runs the scenarios from 2010 through 2050 with a yearly time step. We estimate the Historical Trends trajectory will result in average emissions of 139 million t CO2 year-1 by the 2040s, a 15% increase over current emissions. The Conservation scenario would result in 58% less clearing than Historical Trends and would conserve carbon-dense forest and woodland savanna areas. The Agricultural Development scenario leads to emissions of 212 million t CO2 year-1 by the 2040s. These scenarios are heuristic examples of policy's influence on forest conservation and carbon storage. Our results suggest that 1
Will Passive Protection Save Congo Forests?
Directory of Open Access Journals (Sweden)
Gillian L Galford
Full Text Available Central Africa's tropical forests are among the world's largest carbon reserves. Historically, they have experienced low rates of deforestation. Pressures to clear land are increasing due to development of infrastructure and livelihoods, foreign investment in agriculture, and shifting land use management, particularly in the Democratic Republic of Congo (DRC. The DRC contains the greatest area of intact African forests. These store approximately 22 billion tons of carbon in aboveground live biomass, yet only 10% are protected. Can the status quo of passive protection - forest management that is low or nonexistent - ensure the preservation of this forest and its carbon? We have developed the SimCongo model to simulate changes in land cover and land use based on theorized policy scenarios from 2010 to 2050. Three scenarios were examined: the first (Historical Trends assumes passive forest protection; the next (Conservation posits active protection of forests and activation of the national REDD+ action plan, and the last (Agricultural Development assumes increased agricultural activities in forested land with concomitant increased deforestation. SimCongo is a cellular automata model based on Bayesian statistical methods tailored for the DRC, built with the Dinamica-EGO platform. The model is parameterized and validated with deforestation observations from the past and runs the scenarios from 2010 through 2050 with a yearly time step. We estimate the Historical Trends trajectory will result in average emissions of 139 million t CO2 year-1 by the 2040s, a 15% increase over current emissions. The Conservation scenario would result in 58% less clearing than Historical Trends and would conserve carbon-dense forest and woodland savanna areas. The Agricultural Development scenario leads to emissions of 212 million t CO2 year-1 by the 2040s. These scenarios are heuristic examples of policy's influence on forest conservation and carbon storage. Our results
Improving standard practices for prediction in ungauged basins: Bayesian approach
Prieto, Cristina; Le-Vine, Nataliya; García, Eduardo; Medina, Raúl
2015-04-01
In hydrological modelling, the prediction of flows in ungauged basins is still a defiance. Among the different alternatives to quantify and reduce the uncertainty in the predictions, a Bayesian framework has proven to be advantageous. This framework allows flow prediction in ungauged basins based on regionalised hydrological indices. Being grounded on probability theory, the procedure requires a number of assumptions and decisions to be made. Among the most important ones are 1) selection of representative hydrological signatures, 2) selection of regionalization model functional form, and 3) a 'perfect' model/ input assumption. The contribution of this research is to address these three assumptions. First, to reduce an extensive set of available hydrological signatures we select a compact orthogonal set of information pieces using Principal Component Analysis. This advances the standard practice of semi-empirical selection of individual hydrological signatures. Second, we use functional-form-assumption-free Random Forests to regionalize the selected information. This allows the traditional assumption of linear regression between catchment properties and characteristics of hydrological response to be relaxes. And third, we propose utilizing non-traditional metrics to flag-up possible model/ input errors: Bayes' Factor and a newly-proposed 'Suitability' test. This addresses the typical non-realistic assumption that model is 'perfect' and the input is noise-free. The proposed methodological developments are illustrated for the empirical challenge of flow prediction in rivers in Northern Spain.
Forests and Forest Cover - Ozark National Forest Service Compartments (polygon)
NSGIC GIS Inventory (aka Ramona) — Ozark - St. Francis National Forests stand inventory data for vegetation, maintained in polygon format. Compartment is defined as a division of forest for purposes...
Forests and Forest Cover - MDC_NaturalForestCommunity
NSGIC GIS Inventory (aka Ramona) — A point feature class of NFCs - Natural Forest Communities. Natural Forest Community shall mean all stands of trees (including their associated understory) which...
Ancient neurilemmoma: A rare oral tumor
Directory of Open Access Journals (Sweden)
J Muruganandhan
2013-01-01
Full Text Available Neurilemmomas are benign tumors of neural origin composed of Schwann cell proliferation in characteristic patterns. Ancient neurilemmomas are usually longstanding growths that exhibit degenerative features that could be mistaken for malignancy. They are extremely rare in the oral cavity and present in older individuals of long duration. The authors report a case of ancient neurilemmoma in a young patient with short duration of growth. This unique case presented with remarkable histopathological features with respect to vascularity and atypia associated with degenerative change. It is essential to not mistake these features as malignant transformation so as to avoid radical procedures.
Mythological Emblem Glyphs of Ancient Maya Kings
DEFF Research Database (Denmark)
Helmke, Christophe
2012-01-01
Heinrich Berlin’s identification of Emblem Glyphs in 1958 has rightly been hailed as one of the major breakthroughs in the decipherment of ancient Maya writing. Although their exact function and meaning was unclear at the time, these are now recognized to serve as exalted regal titles that incorp......Heinrich Berlin’s identification of Emblem Glyphs in 1958 has rightly been hailed as one of the major breakthroughs in the decipherment of ancient Maya writing. Although their exact function and meaning was unclear at the time, these are now recognized to serve as exalted regal titles...
Evolution of medical education in ancient Greece
Institute of Scientific and Technical Information of China (English)
Emmanouil Pikoulis; Pavlos Msaouel; Efthimios D Avgerinos; Sofia Anagnostopoulou; Christos Tsigris
2008-01-01
@@ The study of ancient Greece is essential for the proper understanding of the evolution of modem Western medicine.An important innovation of classical Greek medicine was the development of a body of medical theory associated with natural philosophy,i.e.a strong secular tradition of free enquiry,or what would now be called "science" (Επιστημη).Medical education rests upon the ancient Greek foundations and its history remains a fascinating topic for modem physicians and medical teachers.
Symmetries in Images on Ancient Seals
Sparavigna, Amelia
2008-01-01
In this paper, we discuss the presence of symmetries in images engraved on ancient seals, in particular on stamp seals. Mainly used to secure the containers from tampering and for owner's identification, these objects appeared during the 5th millennium BC in Mesopotamia. Usually the seals were engraved with simple images, suitable to communicate an immediate information. Rotational symmetries are already displayed by the most ancient stamp seals, whose images reach a quasi-perfect symmetry in their small circular or ovoid spaces. Bilateral symmetries are quite common in Egyptian scarab seals.
A Modern Take on an Ancient Master
Institute of Scientific and Technical Information of China (English)
无
2011-01-01
A new English translation of The Analects gives a fresh perspective on Confucius and his philosophy by Zan Jifang Confucius(551-491 B.C.) is generally viewed as ancient China’s foremost thinker.His philosophy is probably best catalogued in The Analects,a record of the sage’s wisdom compiled after his death.This Confucian classic provides a shortcut to understanding Chinese culture. A new English edition of the ancient classic(published by the Foreign Languages Press)
Précis of bayesian rationality: The probabilistic approach to human reasoning.
Oaksford, Mike; Chater, Nick
2009-02-01
According to Aristotle, humans are the rational animal. The borderline between rationality and irrationality is fundamental to many aspects of human life including the law, mental health, and language interpretation. But what is it to be rational? One answer, deeply embedded in the Western intellectual tradition since ancient Greece, is that rationality concerns reasoning according to the rules of logic--the formal theory that specifies the inferential connections that hold with certainty between propositions. Piaget viewed logical reasoning as defining the end-point of cognitive development; and contemporary psychology of reasoning has focussed on comparing human reasoning against logical standards. Bayesian Rationality argues that rationality is defined instead by the ability to reason about uncertainty. Although people are typically poor at numerical reasoning about probability, human thought is sensitive to subtle patterns of qualitative Bayesian, probabilistic reasoning. In Chapters 1-4 of Bayesian Rationality (Oaksford & Chater 2007), the case is made that cognition in general, and human everyday reasoning in particular, is best viewed as solving probabilistic, rather than logical, inference problems. In Chapters 5-7 the psychology of "deductive" reasoning is tackled head-on: It is argued that purportedly "logical" reasoning problems, revealing apparently irrational behaviour, are better understood from a probabilistic point of view. Data from conditional reasoning, Wason's selection task, and syllogistic inference are captured by recasting these problems probabilistically. The probabilistic approach makes a variety of novel predictions which have been experimentally confirmed. The book considers the implications of this work, and the wider "probabilistic turn" in cognitive science and artificial intelligence, for understanding human rationality.
Ancient mitochondrial DNA provides high-resolution time scale of the peopling of the Americas.
Llamas, Bastien; Fehren-Schmitz, Lars; Valverde, Guido; Soubrier, Julien; Mallick, Swapan; Rohland, Nadin; Nordenfelt, Susanne; Valdiosera, Cristina; Richards, Stephen M; Rohrlach, Adam; Romero, Maria Inés Barreto; Espinoza, Isabel Flores; Cagigao, Elsa Tomasto; Jiménez, Lucía Watson; Makowski, Krzysztof; Reyna, Ilán Santiago Leboreiro; Lory, Josefina Mansilla; Torrez, Julio Alejandro Ballivián; Rivera, Mario A; Burger, Richard L; Ceruti, Maria Constanza; Reinhard, Johan; Wells, R Spencer; Politis, Gustavo; Santoro, Calogero M; Standen, Vivien G; Smith, Colin; Reich, David; Ho, Simon Y W; Cooper, Alan; Haak, Wolfgang
2016-04-01
The exact timing, route, and process of the initial peopling of the Americas remains uncertain despite much research. Archaeological evidence indicates the presence of humans as far as southern Chile by 14.6 thousand years ago (ka), shortly after the Pleistocene ice sheets blocking access from eastern Beringia began to retreat. Genetic estimates of the timing and route of entry have been constrained by the lack of suitable calibration points and low genetic diversity of Native Americans. We sequenced 92 whole mitochondrial genomes from pre-Columbian South American skeletons dating from 8.6 to 0.5 ka, allowing a detailed, temporally calibrated reconstruction of the peopling of the Americas in a Bayesian coalescent analysis. The data suggest that a small population entered the Americas via a coastal route around 16.0 ka, following previous isolation in eastern Beringia for ~2.4 to 9 thousand years after separation from eastern Siberian populations. Following a rapid movement throughout the Americas, limited gene flow in South America resulted in a marked phylogeographic structure of populations, which persisted through time. All of the ancient mitochondrial lineages detected in this study were absent from modern data sets, suggesting a high extinction rate. To investigate this further, we applied a novel principal components multiple logistic regression test to Bayesian serial coalescent simulations. The analysis supported a scenario in which European colonization caused a substantial loss of pre-Columbian lineages. PMID:27051878
Records of solar eclipse observations in ancient China
Institute of Scientific and Technical Information of China (English)
无
2009-01-01
Like ancient people at other places of the world, the ancient Chinese lived in awe of the Sun. As they felt solar eclipses extremely significant events, they closely observed the occurrence of solar eclipse. Ancient astronomers further realized very early that solar eclipses were one of the important astronomical phenomena to revise and improve the ancient calendar. Interestingly, ancient emperors regarded solar eclipses as warnings from heaven that might affect the stability of their throne. Consequently, observing and recording solar eclipses became official, which dated far back to ancient China when numerous relevant descriptions were recorded in historical books. These records contribute substantially to China as an ancient civilization, as well as to the research of the long-term variation of the rotation rate of the Earth during >2000 years before the 17th century. This paper briefly reviews the perception, observations and recording of solar eclipses by ancient Chinese astronomers.
Records of solar eclipse observations in ancient China
Institute of Scientific and Technical Information of China (English)
HAN YanBen; QIAO OiYuan
2009-01-01
Like ancient people at other places of the world, the ancient Chinese lived in awe of the Sun. As they felt solar eclipses extremely significant events, they closely observed the occurrence of solar eclipse. Ancient astronomers further realized very early that solar eclipses were one of the important astro-nomical phenomena to revise and improve the ancient calendar. Interestingly, ancient emperors re-garded solar eclipses as warnings from heaven that might affect the stability of their throne. Conse-quently, observing and recording solar eclipses became official, which dated far back to ancient China when numerous relevant descriptions were recorded in historical books. These records contribute substantially to China as an ancient civilization, as well as to the research of the long-term variation of the rotation rate of the Earth during >2000 years before the 17th century. This paper briefly reviews the perception, observations and recording of solar eclipses by ancient Chinese astronomers.
Records of solar eclipse observations in ancient China
Han, Yanben; Qiao, Qiyuan
2009-11-01
Like ancient people at other places of the world, the ancient Chinese lived in awe of the Sun. As they felt solar eclipses extremely significant events, they closely observed the occurrence of solar eclipse. Ancient astronomers further realized very early that solar eclipses were one of the important astronomical phenomena to revise and improve the ancient calendar. Interestingly, ancient emperors regarded solar eclipses as warnings from heaven that might affect the stability of their throne. Consequently, observing and recording solar eclipses became official, which dated far back to ancient China when numerous relevant descriptions were recorded in historical books. These records contribute substantially to China as an ancient civilization, as well as to the research of the long-term variation of the rotation rate of the Earth during >2000 years before the 17th century. This paper briefly reviews the perception, observations and recording of solar eclipses by ancient Chinese astronomers.
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
DEFF Research Database (Denmark)
Jagger, Pamela; Luckert, Martin K.; Duchelle, Amy E.;
2014-01-01
We explore the relationship between tenure and forest income in 271 villages throughout the tropics. We find that state-owned forests generate more forest income than private and community-owned forests both per household and per hectare. We explore whether forest income varies according...... to the extent of rule enforcement, and congruence (i.e., overlap of user rights between owners and users). We find negative associations between enforcement and smallholder forest income for state-owned and community forests, and positive associations for privately owned forests. Where user rights are limited...... to formal owners we find negative associations for state-owned forests. Overlapping user rights are positively associated with forest income for community forests. Our findings suggest that policy reforms emphasizing enforcement and reducing overlapping claims to forest resources should consider possible...
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.
Evidence of pre-Columbian settlements in the forest of the Tuxtla Volcanic Field, Veracruz, Mexico
Araceli Zamora-Camacho; Juan Manuel Espíndola; Peter Schaaf; Angel Ramírez; María de Lourdes Godínez Calderón
2015-01-01
The basaltic Los Tuxtlas Volcanic Field (LTVF) is located at the western margin of the Gulf of Mexico in the State of Veracruz, Mexico. The field is a massif composed of four large volcanic structures and hundreds of scoria cones, lava domes and maars. This area was in the past covered by a dense forest in whose margins flourished several of the ancient cities of importance in central and southern Veracruz. Within the forest no enduring archeological ruins have been found; but ...
Der Sarkissian, Clio; Balanovsky, Oleg; Brandt, Guido; Khartanovich, Valery; Buzhilova, Alexandra; Koshel, Sergey; Zaporozhchenko, Valery; Gronenborn, Detlef; Moiseyev, Vyacheslav; Kolpakov, Eugen; Shumkin, Vladimir; Alt, Kurt W; Balanovska, Elena; Cooper, Alan; Haak, Wolfgang
2013-01-01
North East Europe harbors a high diversity of cultures and languages, suggesting a complex genetic history. Archaeological, anthropological, and genetic research has revealed a series of influences from Western and Eastern Eurasia in the past. While genetic data from modern-day populations is commonly used to make inferences about their origins and past migrations, ancient DNA provides a powerful test of such hypotheses by giving a snapshot of the past genetic diversity. In order to better understand the dynamics that have shaped the gene pool of North East Europeans, we generated and analyzed 34 mitochondrial genotypes from the skeletal remains of three archaeological sites in northwest Russia. These sites were dated to the Mesolithic and the Early Metal Age (7,500 and 3,500 uncalibrated years Before Present). We applied a suite of population genetic analyses (principal component analysis, genetic distance mapping, haplotype sharing analyses) and compared past demographic models through coalescent simulations using Bayesian Serial SimCoal and Approximate Bayesian Computation. Comparisons of genetic data from ancient and modern-day populations revealed significant changes in the mitochondrial makeup of North East Europeans through time. Mesolithic foragers showed high frequencies and diversity of haplogroups U (U2e, U4, U5a), a pattern observed previously in European hunter-gatherers from Iberia to Scandinavia. In contrast, the presence of mitochondrial DNA haplogroups C, D, and Z in Early Metal Age individuals suggested discontinuity with Mesolithic hunter-gatherers and genetic influx from central/eastern Siberia. We identified remarkable genetic dissimilarities between prehistoric and modern-day North East Europeans/Saami, which suggests an important role of post-Mesolithic migrations from Western Europe and subsequent population replacement/extinctions. This work demonstrates how ancient DNA can improve our understanding of human population movements across
Directory of Open Access Journals (Sweden)
Clio Der Sarkissian
Full Text Available North East Europe harbors a high diversity of cultures and languages, suggesting a complex genetic history. Archaeological, anthropological, and genetic research has revealed a series of influences from Western and Eastern Eurasia in the past. While genetic data from modern-day populations is commonly used to make inferences about their origins and past migrations, ancient DNA provides a powerful test of such hypotheses by giving a snapshot of the past genetic diversity. In order to better understand the dynamics that have shaped the gene pool of North East Europeans, we generated and analyzed 34 mitochondrial genotypes from the skeletal remains of three archaeological sites in northwest Russia. These sites were dated to the Mesolithic and the Early Metal Age (7,500 and 3,500 uncalibrated years Before Present. We applied a suite of population genetic analyses (principal component analysis, genetic distance mapping, haplotype sharing analyses and compared past demographic models through coalescent simulations using Bayesian Serial SimCoal and Approximate Bayesian Computation. Comparisons of genetic data from ancient and modern-day populations revealed significant changes in the mitochondrial makeup of North East Europeans through time. Mesolithic foragers showed high frequencies and diversity of haplogroups U (U2e, U4, U5a, a pattern observed previously in European hunter-gatherers from Iberia to Scandinavia. In contrast, the presence of mitochondrial DNA haplogroups C, D, and Z in Early Metal Age individuals suggested discontinuity with Mesolithic hunter-gatherers and genetic influx from central/eastern Siberia. We identified remarkable genetic dissimilarities between prehistoric and modern-day North East Europeans/Saami, which suggests an important role of post-Mesolithic migrations from Western Europe and subsequent population replacement/extinctions. This work demonstrates how ancient DNA can improve our understanding of human population
Fossil avian eggshell preserves ancient DNA
DEFF Research Database (Denmark)
Oskam, Charlotte L; Haile, James; McLay, Emma;
2010-01-01
Owing to exceptional biomolecule preservation, fossil avian eggshell has been used extensively in geochronology and palaeodietary studies. Here, we show, to our knowledge, for the first time that fossil eggshell is a previously unrecognized source of ancient DNA (aDNA). We describe the successful...
Fast neutron activation analysis of ancient mirror
International Nuclear Information System (INIS)
About fifty specimens of ancient Chinese bronze mirror from various dynasties are analysed by fast neutron radiated from neutron generator. The contents of copper, tin and lead in the mirror are listed in this paper. Experimental method and measurement equipment are described too
LD Students and the Ancient Mariner.
Cohen, Barbara L.
1988-01-01
Synectics, the making of analogies, was used with learning disabled high school seniors to provide them with a creative process that aids in developing a deeper understanding of literature. After studying Coleridge's "Rime of the Ancient Mariner," the students completed a six-step process and produced a short writing assignment. (VW)
Paragons of Education in Ancient Times
Institute of Scientific and Technical Information of China (English)
1997-01-01
MOTHERS contributed greatly to children’s education in ancient China long before schools took shape. Behind many prominent figures lay greatmothers whose personal example and verbal instruction benefited their children throughout life. There is an old sayingabout the "stern father and compassionate mother."However, you will always
The Roots of Science in Ancient China.
Fisher, Arthur
1982-01-01
A 45-year-old research project (culminating in the multivolume "Science and Civilization in China") is examining major scientific innovations in ancient China and attempting to explain why, although the Chinese gained a technological edge in the past, they did not make the forward leap into modern science. (JN)
The Challenges of Qualitatively Coding Ancient Texts
Slingerland, Edward; Chudek, Maciej
2012-01-01
We respond to several important and valid concerns about our study ("The Prevalence of Folk Dualism in Early China," "Cognitive Science" 35: 997-1007) by Klein and Klein, defending our interpretation of our data. We also argue that, despite the undeniable challenges involved in qualitatively coding texts from ancient cultures, the standard tools…
A probabilistic model of Ancient Egyptian writing
Nederhof, Mark Jan; Rahman, Fahrurrozi
2015-01-01
This article investigates a probabilistic model to describe how signs form words in Ancient Egyptian writing. This applies to both hieroglyphic and hieratic texts. The model uses an intermediate layer of sign functions. Experiments are concerned with finding the most likely sequence of sign functions that relates a given sequence of signs and a given sequence of phonemes. Postprint
[Ancient tattooing from today's point of view].
Zimmermann, R; Zimmermann, K
1981-06-01
Both literary and arachaeological evidence indicates that, up to now, ancient tattoos can be traced with certainty in painting only among Thracians. A comparison with modern tattoos reveals differences of motivation and motifs, whereas localization, technique, and removal show similarities. The illustrations demonstrate some tattoos typical for Thracians on Greek vases.
Ancient whole grain gluten-free flatbreads
The USDA food guide recommends that at least ½ of all the grains eaten should be whole grains. The FDA allows food Health Claim labels for food containing 51% whole gains and 11 g of dietary fiber. This is the only report demonstrating innovative ancient whole grain gluten-free (no yeast or chemical...
Microscopical Examination of Ancient Silver Coins
International Nuclear Information System (INIS)
The microstructure of three silver coins of the IIId century B.C. from the Illyrian king Monounios, the ancient Greek city of Dyrrachion and of Korkyra was studied with XRF and microscopy. From this investigation it turned out that these coins have different chemical composition and microstructure that imply different minting method
Ancient Pyramids Help Students Learn Math Concepts
Smith, Courtney D.; Stump, Amanda M.; Lazaros, Edward J.
2010-01-01
This article presents an activity that allows students to use mathematics and critical-thinking skills to emulate processes used by the ancient Egyptians to prepare the site for the Pyramids of Giza. To accomplish this, they use three different methods. First, they create a square using only simple technological tools that were available to the…
An ancient musical instrument returns home
Institute of Scientific and Technical Information of China (English)
1997-01-01
After 300 years abroad, an ancient Chinese musical instrument returned home with its face lifted and a Japanese name. Originally a one-stringed plucker, the Daisho Modo now features a whole family of electric high-, medium-pitched and bass instruments. With crisp tone and wide range, the Daisho Modo is
Unlocking the Mysteries of Ancient Egypt.
Riechers, Maggie
1995-01-01
Describes the work of Egyptologist William Murnane who is recording the ritual scenes and inscriptions of a great columned hall from the days of the pharaohs. The 134 columns, covered with divine imagery and hieroglyphic inscriptions represent an unpublished religious text. Briefly discusses ancient Egyptian culture. Includes several photographs…
Moessbauer effect study of ancient Egyptian pottery
International Nuclear Information System (INIS)
Moessbauer spectroscopy was used in examining ancient Egyptian pottery. From the values of Moessbauer parameters and the differences for the individual samples, conclusions could be drawn as to the temperature of baking and the kind of clay used in various archaeological periods. (A.K.)
Ancient DNA analysis of dental calculus.
Weyrich, Laura S; Dobney, Keith; Cooper, Alan
2015-02-01
Dental calculus (calcified tartar or plaque) is today widespread on modern human teeth around the world. A combination of soft starchy foods, changing acidity of the oral environment, genetic pre-disposition, and the absence of dental hygiene all lead to the build-up of microorganisms and food debris on the tooth crown, which eventually calcifies through a complex process of mineralisation. Millions of oral microbes are trapped and preserved within this mineralised matrix, including pathogens associated with the oral cavity and airways, masticated food debris, and other types of extraneous particles that enter the mouth. As a result, archaeologists and anthropologists are increasingly using ancient human dental calculus to explore broad aspects of past human diet and health. Most recently, high-throughput DNA sequencing of ancient dental calculus has provided valuable insights into the evolution of the oral microbiome and shed new light on the impacts of some of the major biocultural transitions on human health throughout history and prehistory. Here, we provide a brief historical overview of archaeological dental calculus research, and discuss the current approaches to ancient DNA sampling and sequencing. Novel applications of ancient DNA from dental calculus are discussed, highlighting the considerable scope of this new research field for evolutionary biology and modern medicine.
A Roman Dodecahedron as an ancient rangefinder
Sparavigna, Amelia Carolina
2012-01-01
Rangefinders are instruments used for ballistics and for surveying in general. I report about some of them, ranging from the ancient Rome to modern methods. In particular, I am discussing the use of Roman Dodecahedra, bronze artifacts of gallo-roman origin, for measuring distance
Precursors of Vocational Psychology in Ancient Civilizations.
Dumont, Frank; Carson, Andrew D.
1995-01-01
Examines philosophical theories produced by two ancient civilizations (Eastern Mediterranean and Chinese) for applications to an applied psychology of work. Includes analysis of Egyptians, Semites, and Greeks, with a special emphasis on Plato. Suggests that many basic elements of vocational psychology were present during the first millennium B.C.…
Mitochondrial phylogenomics of modern and ancient equids
DEFF Research Database (Denmark)
Vilstrup, Julia T; Seguin-Orlando, Andaine; Stiller, Mathias;
2013-01-01
to calibrate reliable molecular clocks. Additional mitochondrial genome sequence data, including radiocarbon dated ancient equids, will be required before revisiting the exact timing of the lineage radiation leading up to modern equids, which for now were found to have possibly shared a common ancestor as far...
[Ancient tattooing from today's point of view].
Zimmermann, R; Zimmermann, K
1981-06-01
Both literary and arachaeological evidence indicates that, up to now, ancient tattoos can be traced with certainty in painting only among Thracians. A comparison with modern tattoos reveals differences of motivation and motifs, whereas localization, technique, and removal show similarities. The illustrations demonstrate some tattoos typical for Thracians on Greek vases. PMID:7021475
Defining Astrology in Ancient and Classical History
Campion, Nicholas
2015-05-01
Astrology in the ancient and classical worlds can be partly defined by its role, and partly by the way in which scholars spoke about it. The problem is complicated by the fact that the word is Greek - it has no Babylonian or Egyptian cognates - and even in Greece it was interchangeable with its cousin, 'astronomy'. Yet if we are to understand the role of the sky, stars and planets in culture, debates about the nature of ancient astrology, by both classical and modern scholars, must be taken into account. This talk will consider modern scholars' typologies of ancient astrology, together with ancient debates from Cicero in the 1st century BC, to Plotinus (204/5-270 AD) and Isidore of Seville (c. 560 - 4 April 636). It will consider the implications for our understanding of astronomy's role in culture, and conclude that in the classical period astrology may be best understood through its diversity and allegiance to competing philosophies, and that its functions were therefore similarly varied.
The Ancient Kemetic Roots of Library and Information Science.
Zulu, Itibari M.
This paper argues that the ancient people of Kemet (Egypt), "the black land," built and operated the first major libraries and institutions of higher education in the world. Topics of discussion include the Ancient Egyptians as an African people; a chronology of Ancient Kemet; literature in Kemet; a history of Egyptian Librarianship; the…
Outreach Testing of Ancient Astronomy
Sanmartin, J. R. S.; Blanco, M. B. M.
2015-10-01
fundamental quantity being given by half the difference between solar distances to vertical at winter and summer solstices, with value about 23.5°. Day and year periods greatly differing by about 2 ½ orders of magnitude, 1 day against 365 days, helps students to correctly visualize and interpret the experimental measurements. Since the gnomon serves to observe at night the moon shadow too, students can also determine the inclination of the lunar orbital plane, as about 5 degrees away from the ecliptic, thus explaining why eclipses are infrequent. Independently, earth taking longer between spring and fall equinoxes than from fall to spring (the solar anomaly), as again verified by the students, was explained in ancient Greek science, which posited orbits universally as circles or their combination, by introducing the eccentric circle, with earth placed some distance away from the orbital centre when considering the relative motion of the sun, which would be closer to the earth in winter. In a sense, this can be seen as hint and approximation of the elliptic orbit proposed by Kepler many centuries later. EPSC Abstracts Vol. 10, EPSC2015-40, 2015 European Planetary Science Congress 2015 c Author(s) 2015 EPSC European Planetary Science Congress Secondly, by observing lunar phases and eclipses from the ground, students could also determine, following Aristarchus of Samos in the 3rd century BC, 4 length ratios involving moon and sun distances to earth, and radii of all three, moon, sun, and earth. The angular width of the moon could be first determined with simplest optical devices as about half a degree; this yields the ratio between moon diameter 2RM and distance DM to earth. Next, eclipses of sun prove its angular width, and thus ratio 2RS/DS, similar to the lunar one, though the relatively high lunar orbital eccentricity, 0.055, does result in not quite a full eclipse if at lunar apogee. Further, at a half-moon phase, when the angle sun-moon-earth is a right one, the angle
Outreach Testing of Ancient Astronomy
Sanmartin, J. R. S.; Blanco, M. B. M.
2015-10-01
fundamental quantity being given by half the difference between solar distances to vertical at winter and summer solstices, with value about 23.5°. Day and year periods greatly differing by about 2 ½ orders of magnitude, 1 day against 365 days, helps students to correctly visualize and interpret the experimental measurements. Since the gnomon serves to observe at night the moon shadow too, students can also determine the inclination of the lunar orbital plane, as about 5 degrees away from the ecliptic, thus explaining why eclipses are infrequent. Independently, earth taking longer between spring and fall equinoxes than from fall to spring (the solar anomaly), as again verified by the students, was explained in ancient Greek science, which posited orbits universally as circles or their combination, by introducing the eccentric circle, with earth placed some distance away from the orbital centre when considering the relative motion of the sun, which would be closer to the earth in winter. In a sense, this can be seen as hint and approximation of the elliptic orbit proposed by Kepler many centuries later. EPSC Abstracts Vol. 10, EPSC2015-40, 2015 European Planetary Science Congress 2015 c Author(s) 2015 EPSC European Planetary Science Congress Secondly, by observing lunar phases and eclipses from the ground, students could also determine, following Aristarchus of Samos in the 3rd century BC, 4 length ratios involving moon and sun distances to earth, and radii of all three, moon, sun, and earth. The angular width of the moon could be first determined with simplest optical devices as about half a degree; this yields the ratio between moon diameter 2RM and distance DM to earth. Next, eclipses of sun prove its angular width, and thus ratio 2RS/DS, similar to the lunar one, though the relatively high lunar orbital eccentricity, 0.055, does result in not quite a full eclipse if at lunar apogee. Further, at a half-moon phase, when the angle sun-moon-earth is a right one, the angle
Bayesian parameter estimation for effective field theories
Wesolowski, S; Furnstahl, R J; Phillips, D R; Thapaliya, A
2015-01-01
We present procedures based on Bayesian statistics for effective field theory (EFT) parameter estimation from data. The extraction of low-energy constants (LECs) is guided by theoretical expectations that supplement such information in a quantifiable way through the specification of Bayesian priors. A prior for natural-sized LECs reduces the possibility of overfitting, and leads to a consistent accounting of different sources of uncertainty. A set of diagnostic tools are developed that analyze the fit and ensure that the priors do not bias the EFT parameter estimation. The procedures are illustrated using representative model problems and the extraction of LECs for the nucleon mass expansion in SU(2) chiral perturbation theory from synthetic lattice data.
Applications of Bayesian spectrum representation in acoustics
Botts, Jonathan M.
This dissertation utilizes a Bayesian inference framework to enhance the solution of inverse problems where the forward model maps to acoustic spectra. A Bayesian solution to filter design inverts a acoustic spectra to pole-zero locations of a discrete-time filter model. Spatial sound field analysis with a spherical microphone array is a data analysis problem that requires inversion of spatio-temporal spectra to directions of arrival. As with many inverse problems, a probabilistic analysis results in richer solutions than can be achieved with ad-hoc methods. In the filter design problem, the Bayesian inversion results in globally optimal coefficient estimates as well as an estimate the most concise filter capable of representing the given spectrum, within a single framework. This approach is demonstrated on synthetic spectra, head-related transfer function spectra, and measured acoustic reflection spectra. The Bayesian model-based analysis of spatial room impulse responses is presented as an analogous problem with equally rich solution. The model selection mechanism provides an estimate of the number of arrivals, which is necessary to properly infer the directions of simultaneous arrivals. Although, spectrum inversion problems are fairly ubiquitous, the scope of this dissertation has been limited to these two and derivative problems. The Bayesian approach to filter design is demonstrated on an artificial spectrum to illustrate the model comparison mechanism and then on measured head-related transfer functions to show the potential range of application. Coupled with sampling methods, the Bayesian approach is shown to outperform least-squares filter design methods commonly used in commercial software, confirming the need for a global search of the parameter space. The resulting designs are shown to be comparable to those that result from global optimization methods, but the Bayesian approach has the added advantage of a filter length estimate within the same unified
Narrowband interference parameterization for sparse Bayesian recovery
Ali, Anum
2015-09-11
This paper addresses the problem of narrowband interference (NBI) in SC-FDMA systems by using tools from compressed sensing and stochastic geometry. The proposed NBI cancellation scheme exploits the frequency domain sparsity of the unknown signal and adopts a Bayesian sparse recovery procedure. This is done by keeping a few randomly chosen sub-carriers data free to sense the NBI signal at the receiver. As Bayesian recovery requires knowledge of some NBI parameters (i.e., mean, variance and sparsity rate), we use tools from stochastic geometry to obtain analytical expressions for the required parameters. Our simulation results validate the analysis and depict suitability of the proposed recovery method for NBI mitigation. © 2015 IEEE.
Bayesian networks for enterprise risk assessment
Bonafede, C E
2006-01-01
According to different typologies of activity and priority, risks can assume diverse meanings and it can be assessed in different ways. In general risk is measured in terms of a probability combination of an event (frequency) and its consequence (impact). To estimate the frequency and the impact (severity) historical data or expert opinions (either qualitative or quantitative data) are used. Moreover qualitative data must be converted in numerical values to be used in the model. In the case of enterprise risk assessment the considered risks are, for instance, strategic, operational, legal and of image, which many times are difficult to be quantified. So in most cases only expert data, gathered by scorecard approaches, are available for risk analysis. The Bayesian Network is a useful tool to integrate different information and in particular to study the risk's joint distribution by using data collected from experts. In this paper we want to show a possible approach for building a Bayesian networks in the parti...
Bayesianism and inference to the best explanation
Directory of Open Access Journals (Sweden)
Valeriano IRANZO
2008-01-01
Full Text Available Bayesianism and Inference to the best explanation (IBE are two different models of inference. Recently there has been some debate about the possibility of “bayesianizing” IBE. Firstly I explore several alternatives to include explanatory considerations in Bayes’s Theorem. Then I distinguish two different interpretations of prior probabilities: “IBE-Bayesianism” (IBE-Bay and “frequentist-Bayesianism” (Freq-Bay. After detailing the content of the latter, I propose a rule for assessing the priors. I also argue that Freq-Bay: (i endorses a role for explanatory value in the assessment of scientific hypotheses; (ii avoids a purely subjectivist reading of prior probabilities; and (iii fits better than IBE-Bayesianism with two basic facts about science, i.e., the prominent role played by empirical testing and the existence of many scientific theories in the past that failed to fulfil their promises and were subsequently abandoned.
QBism, the Perimeter of Quantum Bayesianism
Fuchs, Christopher A
2010-01-01
This article summarizes the Quantum Bayesian point of view of quantum mechanics, with special emphasis on the view's outer edges---dubbed QBism. QBism has its roots in personalist Bayesian probability theory, is crucially dependent upon the tools of quantum information theory, and most recently, has set out to investigate whether the physical world might be of a type sketched by some false-started philosophies of 100 years ago (pragmatism, pluralism, nonreductionism, and meliorism). Beyond conceptual issues, work at Perimeter Institute is focused on the hard technical problem of finding a good representation of quantum mechanics purely in terms of probabilities, without amplitudes or Hilbert-space operators. The best candidate representation involves a mysterious entity called a symmetric informationally complete quantum measurement. Contemplation of it gives a way of thinking of the Born Rule as an addition to the rules of probability theory, applicable when an agent considers gambling on the consequences of...
Distributed Bayesian Networks for User Modeling
DEFF Research Database (Denmark)
Tedesco, Roberto; Dolog, Peter; Nejdl, Wolfgang;
2006-01-01
The World Wide Web is a popular platform for providing eLearning applications to a wide spectrum of users. However – as users differ in their preferences, background, requirements, and goals – applications should provide personalization mechanisms. In the Web context, user models used...... by such adaptive applications are often partial fragments of an overall user model. The fragments have then to be collected and merged into a global user profile. In this paper we investigate and present algorithms able to cope with distributed, fragmented user models – based on Bayesian Networks – in the context...... of Web-based eLearning platforms. The scenario we are tackling assumes learners who use several systems over time, which are able to create partial Bayesian Networks for user models based on the local system context. In particular, we focus on how to merge these partial user models. Our merge mechanism...
Machine learning a Bayesian and optimization perspective
Theodoridis, Sergios
2015-01-01
This tutorial text gives a unifying perspective on machine learning by covering both probabilistic and deterministic approaches, which rely on optimization techniques, as well as Bayesian inference, which is based on a hierarchy of probabilistic models. The book presents the major machine learning methods as they have been developed in different disciplines, such as statistics, statistical and adaptive signal processing and computer science. Focusing on the physical reasoning behind the mathematics, all the various methods and techniques are explained in depth, supported by examples and problems, giving an invaluable resource to the student and researcher for understanding and applying machine learning concepts. The book builds carefully from the basic classical methods to the most recent trends, with chapters written to be as self-contained as possible, making the text suitable for different courses: pattern recognition, statistical/adaptive signal processing, statistical/Bayesian learning, as well as shor...
Bayesian image reconstruction: Application to emission tomography
Energy Technology Data Exchange (ETDEWEB)
Nunez, J.; Llacer, J.
1989-02-01
In this paper we propose a Maximum a Posteriori (MAP) method of image reconstruction in the Bayesian framework for the Poisson noise case. We use entropy to define the prior probability and likelihood to define the conditional probability. The method uses sharpness parameters which can be theoretically computed or adjusted, allowing us to obtain MAP reconstructions without the problem of the grey'' reconstructions associated with the pre Bayesian reconstructions. We have developed several ways to solve the reconstruction problem and propose a new iterative algorithm which is stable, maintains positivity and converges to feasible images faster than the Maximum Likelihood Estimate method. We have successfully applied the new method to the case of Emission Tomography, both with simulated and real data. 41 refs., 4 figs., 1 tab.
The Bayesian Who Knew Too Much
Benétreau-Dupin, Yann
2014-01-01
In several papers, John Norton has argued that Bayesianism cannot handle ignorance adequately due to its inability to distinguish between neutral and disconfirming evidence. He argued that this inability sows confusion in, e.g., anthropic reasoning in cosmology or the Doomsday argument, by allowing one to draw unwarranted conclusions from a lack of knowledge. Norton has suggested criteria for a candidate for representation of neutral support. Imprecise credences (families of credal probability functions) constitute a Bayesian-friendly framework that allows us to avoid inadequate neutral priors and better handle ignorance. The imprecise model generally agrees with Norton's representation of ignorance but requires that his criterion of self-duality be reformulated or abandoned
Software Health Management with Bayesian Networks
Mengshoel, Ole; Schumann, JOhann
2011-01-01
Most modern aircraft as well as other complex machinery is equipped with diagnostics systems for its major subsystems. During operation, sensors provide important information about the subsystem (e.g., the engine) and that information is used to detect and diagnose faults. Most of these systems focus on the monitoring of a mechanical, hydraulic, or electromechanical subsystem of the vehicle or machinery. Only recently, health management systems that monitor software have been developed. In this paper, we will discuss our approach of using Bayesian networks for Software Health Management (SWHM). We will discuss SWHM requirements, which make advanced reasoning capabilities for the detection and diagnosis important. Then we will present our approach to using Bayesian networks for the construction of health models that dynamically monitor a software system and is capable of detecting and diagnosing faults.
Learning Bayesian networks using genetic algorithm
Institute of Scientific and Technical Information of China (English)
Chen Fei; Wang Xiufeng; Rao Yimei
2007-01-01
A new method to evaluate the fitness of the Bayesian networks according to the observed data is provided. The main advantage of this criterion is that it is suitable for both the complete and incomplete cases while the others not.Moreover it facilitates the computation greatly. In order to reduce the search space, the notation of equivalent class proposed by David Chickering is adopted. Instead of using the method directly, the novel criterion, variable ordering, and equivalent class are combined,moreover the proposed mthod avoids some problems caused by the previous one. Later, the genetic algorithm which allows global convergence, lack in the most of the methods searching for Bayesian network is applied to search for a good model in thisspace. To speed up the convergence, the genetic algorithm is combined with the greedy algorithm. Finally, the simulation shows the validity of the proposed approach.
Bayesian Population Projections for the United Nations.
Raftery, Adrian E; Alkema, Leontine; Gerland, Patrick
2014-02-01
The United Nations regularly publishes projections of the populations of all the world's countries broken down by age and sex. These projections are the de facto standard and are widely used by international organizations, governments and researchers. Like almost all other population projections, they are produced using the standard deterministic cohort-component projection method and do not yield statements of uncertainty. We describe a Bayesian method for producing probabilistic population projections for most countries that the United Nations could use. It has at its core Bayesian hierarchical models for the total fertility rate and life expectancy at birth. We illustrate the method and show how it can be extended to address concerns about the UN's current assumptions about the long-term distribution of fertility. The method is implemented in the R packages bayesTFR, bayesLife, bayesPop and bayesDem.
Approximate Bayesian Computation: a nonparametric perspective
Blum, Michael
2010-01-01
Approximate Bayesian Computation is a family of likelihood-free inference techniques that are well-suited to models defined in terms of a stochastic generating mechanism. In a nutshell, Approximate Bayesian Computation proceeds by computing summary statistics s_obs from the data and simulating summary statistics for different values of the parameter theta. The posterior distribution is then approximated by an estimator of the conditional density g(theta|s_obs). In this paper, we derive the asymptotic bias and variance of the standard estimators of the posterior distribution which are based on rejection sampling and linear adjustment. Additionally, we introduce an original estimator of the posterior distribution based on quadratic adjustment and we show that its bias contains a fewer number of terms than the estimator with linear adjustment. Although we find that the estimators with adjustment are not universally superior to the estimator based on rejection sampling, we find that they can achieve better perfor...
Bayesian information fusion networks for biosurveillance applications.
Mnatsakanyan, Zaruhi R; Burkom, Howard S; Coberly, Jacqueline S; Lombardo, Joseph S
2009-01-01
This study introduces new information fusion algorithms to enhance disease surveillance systems with Bayesian decision support capabilities. A detection system was built and tested using chief complaints from emergency department visits, International Classification of Diseases Revision 9 (ICD-9) codes from records of outpatient visits to civilian and military facilities, and influenza surveillance data from health departments in the National Capital Region (NCR). Data anomalies were identified and distribution of time offsets between events in the multiple data streams were established. The Bayesian Network was built to fuse data from multiple sources and identify influenza-like epidemiologically relevant events. Results showed increased specificity compared with the alerts generated by temporal anomaly detection algorithms currently deployed by NCR health departments. Further research should be done to investigate correlations between data sources for efficient fusion of the collected data.
Bayesian Magnetohydrodynamic Seismology of Coronal Loops
Arregui, Inigo
2011-01-01
We perform a Bayesian parameter inference in the context of resonantly damped transverse coronal loop oscillations. The forward problem is solved in terms of parametric results for kink waves in one-dimensional flux tubes in the thin tube and thin boundary approximations. For the inverse problem, we adopt a Bayesian approach to infer the most probable values of the relevant parameters, for given observed periods and damping times, and to extract their confidence levels. The posterior probability distribution functions are obtained by means of Markov Chain Monte Carlo simulations, incorporating observed uncertainties in a consistent manner. We find well localized solutions in the posterior probability distribution functions for two of the three parameters of interest, namely the Alfven travel time and the transverse inhomogeneity length-scale. The obtained estimates for the Alfven travel time are consistent with previous inversion results, but the method enables us to additionally constrain the transverse inho...
A Bayesian nonparametric meta-analysis model.
Karabatsos, George; Talbott, Elizabeth; Walker, Stephen G
2015-03-01
In a meta-analysis, it is important to specify a model that adequately describes the effect-size distribution of the underlying population of studies. The conventional normal fixed-effect and normal random-effects models assume a normal effect-size population distribution, conditionally on parameters and covariates. For estimating the mean overall effect size, such models may be adequate, but for prediction, they surely are not if the effect-size distribution exhibits non-normal behavior. To address this issue, we propose a Bayesian nonparametric meta-analysis model, which can describe a wider range of effect-size distributions, including unimodal symmetric distributions, as well as skewed and more multimodal distributions. We demonstrate our model through the analysis of real meta-analytic data arising from behavioral-genetic research. We compare the predictive performance of the Bayesian nonparametric model against various conventional and more modern normal fixed-effects and random-effects models.
Distributed Detection via Bayesian Updates and Consensus
Liu, Qipeng; Wang, Xiaofan
2014-01-01
In this paper, we discuss a class of distributed detection algorithms which can be viewed as implementations of Bayes' law in distributed settings. Some of the algorithms are proposed in the literature most recently, and others are first developed in this paper. The common feature of these algorithms is that they all combine (i) certain kinds of consensus protocols with (ii) Bayesian updates. They are different mainly in the aspect of the type of consensus protocol and the order of the two operations. After discussing their similarities and differences, we compare these distributed algorithms by numerical examples. We focus on the rate at which these algorithms detect the underlying true state of an object. We find that (a) The algorithms with consensus via geometric average is more efficient than that via arithmetic average; (b) The order of consensus aggregation and Bayesian update does not apparently influence the performance of the algorithms; (c) The existence of communication delay dramatically slows do...
Probabilistic forecasting and Bayesian data assimilation
Reich, Sebastian
2015-01-01
In this book the authors describe the principles and methods behind probabilistic forecasting and Bayesian data assimilation. Instead of focusing on particular application areas, the authors adopt a general dynamical systems approach, with a profusion of low-dimensional, discrete-time numerical examples designed to build intuition about the subject. Part I explains the mathematical framework of ensemble-based probabilistic forecasting and uncertainty quantification. Part II is devoted to Bayesian filtering algorithms, from classical data assimilation algorithms such as the Kalman filter, variational techniques, and sequential Monte Carlo methods, through to more recent developments such as the ensemble Kalman filter and ensemble transform filters. The McKean approach to sequential filtering in combination with coupling of measures serves as a unifying mathematical framework throughout Part II. Assuming only some basic familiarity with probability, this book is an ideal introduction for graduate students in ap...
Bayesian Peak Picking for NMR Spectra
Cheng, Yichen
2014-02-01
Protein structure determination is a very important topic in structural genomics, which helps people to understand varieties of biological functions such as protein-protein interactions, protein–DNA interactions and so on. Nowadays, nuclear magnetic resonance (NMR) has often been used to determine the three-dimensional structures of protein in vivo. This study aims to automate the peak picking step, the most important and tricky step in NMR structure determination. We propose to model the NMR spectrum by a mixture of bivariate Gaussian densities and use the stochastic approximation Monte Carlo algorithm as the computational tool to solve the problem. Under the Bayesian framework, the peak picking problem is casted as a variable selection problem. The proposed method can automatically distinguish true peaks from false ones without preprocessing the data. To the best of our knowledge, this is the first effort in the literature that tackles the peak picking problem for NMR spectrum data using Bayesian method.
A Bayesian approach to person perception.
Clifford, C W G; Mareschal, I; Otsuka, Y; Watson, T L
2015-11-01
Here we propose a Bayesian approach to person perception, outlining the theoretical position and a methodological framework for testing the predictions experimentally. We use the term person perception to refer not only to the perception of others' personal attributes such as age and sex but also to the perception of social signals such as direction of gaze and emotional expression. The Bayesian approach provides a formal description of the way in which our perception combines current sensory evidence with prior expectations about the structure of the environment. Such expectations can lead to unconscious biases in our perception that are particularly evident when sensory evidence is uncertain. We illustrate the ideas with reference to our recent studies on gaze perception which show that people have a bias to perceive the gaze of others as directed towards themselves. We also describe a potential application to the study of the perception of a person's sex, in which a bias towards perceiving males is typically observed.
Bayesian parameter estimation for effective field theories
Wesolowski, S.; Klco, N.; Furnstahl, R. J.; Phillips, D. R.; Thapaliya, A.
2016-07-01
We present procedures based on Bayesian statistics for estimating, from data, the parameters of effective field theories (EFTs). The extraction of low-energy constants (LECs) is guided by theoretical expectations in a quantifiable way through the specification of Bayesian priors. A prior for natural-sized LECs reduces the possibility of overfitting, and leads to a consistent accounting of different sources of uncertainty. A set of diagnostic tools is developed that analyzes the fit and ensures that the priors do not bias the EFT parameter estimation. The procedures are illustrated using representative model problems, including the extraction of LECs for the nucleon-mass expansion in SU(2) chiral perturbation theory from synthetic lattice data.
BONNSAI: correlated stellar observables in Bayesian methods
Schneider, F R N; Fossati, L; Langer, N; de Koter, A
2016-01-01
In an era of large spectroscopic surveys of stars and big data, sophisticated statistical methods become more and more important in order to infer fundamental stellar parameters such as mass and age. Bayesian techniques are powerful methods because they can match all available observables simultaneously to stellar models while taking prior knowledge properly into account. However, in most cases it is assumed that observables are uncorrelated which is generally not the case. Here, we include correlations in the Bayesian code BONNSAI by incorporating the covariance matrix in the likelihood function. We derive a parametrisation of the covariance matrix that, in addition to classical uncertainties, only requires the specification of a correlation parameter that describes how observables co-vary. Our correlation parameter depends purely on the method with which observables have been determined and can be analytically derived in some cases. This approach therefore has the advantage that correlations can be accounte...
U.S. Environmental Protection Agency — Forests provide economic and ecological value. High percentages of forest cover (FORPCTFuture) generally indicate healthier ecosystems and cleaner surface water....
Yu, Jihnhee; Hutson, Alan D; Siddiqui, Adnan H; Kedron, Mary A
2016-02-01
In some small clinical trials, toxicity is not a primary endpoint; however, it often has dire effects on patients' quality of life and is even life-threatening. For such clinical trials, rigorous control of the overall incidence of adverse events is desirable, while simultaneously collecting safety information. In this article, we propose group sequential toxicity monitoring strategies to control overall toxicity incidents below a certain level as opposed to performing hypothesis testing, which can be incorporated into an existing study design based on the primary endpoint. We consider two sequential methods: a non-Bayesian approach in which stopping rules are obtained based on the 'future' probability of an excessive toxicity rate; and a Bayesian adaptation modifying the proposed non-Bayesian approach, which can use the information obtained at interim analyses. Through an extensive Monte Carlo study, we show that the Bayesian approach often provides better control of the overall toxicity rate than the non-Bayesian approach. We also investigate adequate toxicity estimation after the studies. We demonstrate the applicability of our proposed methods in controlling the symptomatic intracranial hemorrhage rate for treating acute ischemic stroke patients.
The Size-Weight Illusion is not anti-Bayesian after all: a unifying Bayesian account.
Peters, Megan A K; Ma, Wei Ji; Shams, Ladan
2016-01-01
When we lift two differently-sized but equally-weighted objects, we expect the larger to be heavier, but the smaller feels heavier. However, traditional Bayesian approaches with "larger is heavier" priors predict the smaller object should feel lighter; this Size-Weight Illusion (SWI) has thus been labeled "anti-Bayesian" and has stymied psychologists for generations. We propose that previous Bayesian approaches neglect the brain's inference process about density. In our Bayesian model, objects' perceived heaviness relationship is based on both their size and inferred density relationship: observers evaluate competing, categorical hypotheses about objects' relative densities, the inference about which is then used to produce the final estimate of weight. The model can qualitatively and quantitatively reproduce the SWI and explain other researchers' findings, and also makes a novel prediction, which we confirmed. This same computational mechanism accounts for other multisensory phenomena and illusions; that the SWI follows the same process suggests that competitive-prior Bayesian inference can explain human perception across many domains.
Forest Opening in Multipurpose Private Forest - Case Study
Hribernik, Boštjan; Potočnik, Igor
2013-01-01
In the past, forest opening with forest roads was planned on the basis of forest wood production. By discovering the importance of other forest roles, gradual integration of individual role into planning processes of forest opening started. The modern approach to the planning of forest opening of multipurpose forests requires a simultaneous consideration of all forest roles. Economic justification for enlarging the existing forest road network is based on the density of forest roads, where th...
US Forest Service Healthy Forest Restoration Act
US Forest Service, Department of Agriculture — A map service on the www depicting areas designated within National Forest System Lands, in 37 States, that are eligible for insect and disease treatments under...
US Forest Service Administrative Forest Boundaries
US Forest Service, Department of Agriculture — A map service on the www depicting all the National Forest System lands administered by an unit. These areas encompasse private lands, other governmental agency...
US Forest Service National Forest System Trails
US Forest Service, Department of Agriculture — A map service on the world wide web that depicts National Forest Service trails that have been approved for publication. This service is used internally 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 ...
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...
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...
Approximate Bayesian inference for complex ecosystems
Michael P H Stumpf
2014-01-01
Mathematical models have been central to ecology for nearly a century. Simple models of population dynamics have allowed us to understand fundamental aspects underlying the dynamics and stability of ecological systems. What has remained a challenge, however, is to meaningfully interpret experimental or observational data in light of mathematical models. Here, we review recent developments, notably in the growing field of approximate Bayesian computation (ABC), that allow us to calibrate mathe...
Forming Object Concept Using Bayesian Network
Nakamura, Tomoaki; Nagai, Takayuki
2010-01-01
This chapter hase discussed a novel framework for object understanding. Implementation of the proposed framework using Bayesian Network has been presented. Although the result given in this paper is preliminary one, we have shown that the system can form object concept by observing the performance by human hands. The on-line learning is left for the future works. Moreover the model should be extended so that it can represent the object usage and work objects.
Bayesian belief networks in business continuity.
Phillipson, Frank; Matthijssen, Edwin; Attema, Thomas
2014-01-01
Business continuity professionals aim to mitigate the various challenges to the continuity of their company. The goal is a coherent system of measures that encompass detection, prevention and recovery. Choices made in one part of the system affect other parts as well as the continuity risks of the company. In complex organisations, however, these relations are far from obvious. This paper proposes the use of Bayesian belief networks to expose these relations, and presents a modelling framework for this approach. PMID:25193453
Informed Source Separation: A Bayesian Tutorial
Knuth, Kevin
2013-01-01
Source separation problems are ubiquitous in the physical sciences; any situation where signals are superimposed calls for source separation to estimate the original signals. In this tutorial I will discuss the Bayesian approach to the source separation problem. This approach has a specific advantage in that it requires the designer to explicitly describe the signal model in addition to any other information or assumptions that go into the problem description. This leads naturally to the idea...
Market Segmentation Using Bayesian Model Based Clustering
Van Hattum, P.
2009-01-01
This dissertation deals with two basic problems in marketing, that are market segmentation, which is the grouping of persons who share common aspects, and market targeting, which is focusing your marketing efforts on one or more attractive market segments. For the grouping of persons who share common aspects a Bayesian model based clustering approach is proposed such that it can be applied to data sets that are specifically used for market segmentation. The cluster algorithm can handle very l...
Approximate Bayesian computation in population genetics.
Beaumont, Mark A; Zhang, Wenyang; Balding, David J.
2002-01-01
We propose a new method for approximate Bayesian statistical inference on the basis of summary statistics. The method is suited to complex problems that arise in population genetics, extending ideas developed in this setting by earlier authors. Properties of the posterior distribution of a parameter, such as its mean or density curve, are approximated without explicit likelihood calculations. This is achieved by fitting a local-linear regression of simulated parameter values on simulated summ...
Bayesian nonparametric duration model with censorship
Directory of Open Access Journals (Sweden)
Joseph Hakizamungu
2007-10-01
Full Text Available This paper is concerned with nonparametric i.i.d. durations models censored observations and we establish by a simple and unified approach the general structure of a bayesian nonparametric estimator for a survival function S. For Dirichlet prior distributions, we describe completely the structure of the posterior distribution of the survival function. These results are essentially supported by prior and posterior independence properties.
Bayesian modeling and classification of neural signals
Lewicki, Michael S.
1994-01-01
Signal processing and classification algorithms often have limited applicability resulting from an inaccurate model of the signal's underlying structure. We present here an efficient, Bayesian algorithm for modeling a signal composed of the superposition of brief, Poisson-distributed functions. This methodology is applied to the specific problem of modeling and classifying extracellular neural waveforms which are composed of a superposition of an unknown number of action potentials CAPs). ...
Bayesian Estimation and Inference Using Stochastic Electronics.
Thakur, Chetan Singh; Afshar, Saeed; Wang, Runchun M; Hamilton, Tara J; Tapson, Jonathan; van Schaik, André
2016-01-01
In this paper, we present the implementation of two types of Bayesian inference problems to demonstrate the potential of building probabilistic algorithms in hardware using single set of building blocks with the ability to perform these computations in real time. The first implementation, referred to as the BEAST (Bayesian Estimation and Stochastic Tracker), demonstrates a simple problem where an observer uses an underlying Hidden Markov Model (HMM) to track a target in one dimension. In this implementation, sensors make noisy observations of the target position at discrete time steps. The tracker learns the transition model for target movement, and the observation model for the noisy sensors, and uses these to estimate the target position by solving the Bayesian recursive equation online. We show the tracking performance of the system and demonstrate how it can learn the observation model, the transition model, and the external distractor (noise) probability interfering with the observations. In the second implementation, referred to as the Bayesian INference in DAG (BIND), we show how inference can be performed in a Directed Acyclic Graph (DAG) using stochastic circuits. We show how these building blocks can be easily implemented using simple digital logic gates. An advantage of the stochastic electronic implementation is that it is robust to certain types of noise, which may become an issue in integrated circuit (IC) technology with feature sizes in the order of tens of nanometers due to their low noise margin, the effect of high-energy cosmic rays and the low supply voltage. In our framework, the flipping of random individual bits would not affect the system performance because information is encoded in a bit stream. PMID:27047326
Bayesian biclustering of gene expression data
Liu Jun S; Gu Jiajun
2008-01-01
Abstract Background Biclustering of gene expression data searches for local patterns of gene expression. A bicluster (or a two-way cluster) is defined as a set of genes whose expression profiles are mutually similar within a subset of experimental conditions/samples. Although several biclustering algorithms have been studied, few are based on rigorous statistical models. Results We developed a Bayesian biclustering model (BBC), and implemented a Gibbs sampling procedure for its statistical in...
Nonparametric Bayesian Storyline Detection from Microtexts
Krishnan, Vinodh; Eisenstein, Jacob
2016-01-01
News events and social media are composed of evolving storylines, which capture public attention for a limited period of time. Identifying these storylines would enable many high-impact applications, such as tracking public interest and opinion in ongoing crisis events. However, this requires integrating temporal and linguistic information, and prior work takes a largely heuristic approach. We present a novel online non-parametric Bayesian framework for storyline detection, using the distance...
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...
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...
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 ...
Bayesian Estimation and Inference Using Stochastic Electronics.
Thakur, Chetan Singh; Afshar, Saeed; Wang, Runchun M; Hamilton, Tara J; Tapson, Jonathan; van Schaik, André
2016-01-01
In this paper, we present the implementation of two types of Bayesian inference problems to demonstrate the potential of building probabilistic algorithms in hardware using single set of building blocks with the ability to perform these computations in real time. The first implementation, referred to as the BEAST (Bayesian Estimation and Stochastic Tracker), demonstrates a simple problem where an observer uses an underlying Hidden Markov Model (HMM) to track a target in one dimension. In this implementation, sensors make noisy observations of the target position at discrete time steps. The tracker learns the transition model for target movement, and the observation model for the noisy sensors, and uses these to estimate the target position by solving the Bayesian recursive equation online. We show the tracking performance of the system and demonstrate how it can learn the observation model, the transition model, and the external distractor (noise) probability interfering with the observations. In the second implementation, referred to as the Bayesian INference in DAG (BIND), we show how inference can be performed in a Directed Acyclic Graph (DAG) using stochastic circuits. We show how these building blocks can be easily implemented using simple digital logic gates. An advantage of the stochastic electronic implementation is that it is robust to certain types of noise, which may become an issue in integrated circuit (IC) technology with feature sizes in the order of tens of nanometers due to their low noise margin, the effect of high-energy cosmic rays and the low supply voltage. In our framework, the flipping of random individual bits would not affect the system performance because information is encoded in a bit stream.
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...
Bayesian Variable Selection via Particle Stochastic Search.
Shi, Minghui; Dunson, David B
2011-02-01
We focus on Bayesian variable selection in regression models. One challenge is to search the huge model space adequately, while identifying high posterior probability regions. In the past decades, the main focus has been on the use of Markov chain Monte Carlo (MCMC) algorithms for these purposes. In this article, we propose a new computational approach based on sequential Monte Carlo (SMC), which we refer to as particle stochastic search (PSS). We illustrate PSS through applications to linear regression and probit models.
Bayesian Spatial Modelling with R-INLA
Finn Lindgren; Håvard Rue
2015-01-01
The principles behind the interface to continuous domain spatial models in the R- INLA software package for R are described. The integrated nested Laplace approximation (INLA) approach proposed by Rue, Martino, and Chopin (2009) is a computationally effective alternative to MCMC for Bayesian inference. INLA is designed for latent Gaussian models, a very wide and flexible class of models ranging from (generalized) linear mixed to spatial and spatio-temporal models. Combined with the stochastic...
Genetic diversity among ancient Nordic populations.
Directory of Open Access Journals (Sweden)
Linea Melchior
Full Text Available Using established criteria for work with fossil DNA we have analysed mitochondrial DNA from 92 individuals from 18 locations in Denmark ranging in time from the Mesolithic to the Medieval Age. Unequivocal assignment of mtDNA haplotypes was possible for 56 of the ancient individuals; however, the success rate varied substantially between sites; the highest rates were obtained with untouched, freshly excavated material, whereas heavy handling, archeological preservation and storage for many years influenced the ability to obtain authentic endogenic DNA. While the nucleotide diversity at two locations was similar to that among extant Danes, the diversity at four sites was considerably higher. This supports previous observations for ancient Britons. The overall occurrence of haplogroups did not deviate from extant Scandinavians, however, haplogroup I was significantly more frequent among the ancient Danes (average 13% than among extant Danes and Scandinavians (approximately 2.5% as well as among other ancient population samples reported. Haplogroup I could therefore have been an ancient Southern Scandinavian type "diluted" by later immigration events. Interestingly, the two Neolithic samples (4,200 YBP, Bell Beaker culture that were typed were haplogroup U4 and U5a, respectively, and the single Bronze Age sample (3,300-3,500 YBP was haplogroup U4. These two haplogroups have been associated with the Mesolithic populations of Central and Northern Europe. Therefore, at least for Southern Scandinavia, our findings do not support a possible replacement of a haplogroup U dominated hunter-gatherer population by a more haplogroup diverse Neolithic Culture.
Sparse Bayesian learning in ISAR tomography imaging
Institute of Scientific and Technical Information of China (English)
SU Wu-ge; WANG Hong-qiang; DENG Bin; WANG Rui-jun; QIN Yu-liang
2015-01-01
Inverse synthetic aperture radar (ISAR) imaging can be regarded as a narrow-band version of the computer aided tomography (CT). The traditional CT imaging algorithms for ISAR, including the polar format algorithm (PFA) and the convolution back projection algorithm (CBP), usually suffer from the problem of the high sidelobe and the low resolution. The ISAR tomography image reconstruction within a sparse Bayesian framework is concerned. Firstly, the sparse ISAR tomography imaging model is established in light of the CT imaging theory. Then, by using the compressed sensing (CS) principle, a high resolution ISAR image can be achieved with limited number of pulses. Since the performance of existing CS-based ISAR imaging algorithms is sensitive to the user parameter, this makes the existing algorithms inconvenient to be used in practice. It is well known that the Bayesian formalism of recover algorithm named sparse Bayesian learning (SBL) acts as an effective tool in regression and classification, which uses an efficient expectation maximization procedure to estimate the necessary parameters, and retains a preferable property of thel0-norm diversity measure. Motivated by that, a fully automated ISAR tomography imaging algorithm based on SBL is proposed. Experimental results based on simulated and electromagnetic (EM) data illustrate the effectiveness and the superiority of the proposed algorithm over the existing algorithms.
Particle identification in ALICE: a Bayesian approach
Adam, Jaroslav; Aggarwal, Madan Mohan; Aglieri Rinella, Gianluca; Agnello, Michelangelo; Agrawal, Neelima; Ahammed, Zubayer; Ahmad, Shakeel; Ahn, Sang Un; Aiola, Salvatore; Akindinov, Alexander; Alam, Sk Noor; Silva De Albuquerque, Danilo; Aleksandrov, Dmitry; Alessandro, Bruno; Alexandre, Didier; Alfaro Molina, Jose Ruben; Alici, Andrea; Alkin, Anton; Millan Almaraz, Jesus Roberto; Alme, Johan; Alt, Torsten; Altinpinar, Sedat; Altsybeev, Igor; Alves Garcia Prado, Caio; Andrei, Cristian; Andronic, Anton; Anguelov, Venelin; Anticic, Tome; Antinori, Federico; Antonioli, Pietro; Aphecetche, Laurent Bernard; Appelshaeuser, Harald; Arcelli, Silvia; Arnaldi, Roberta; Arnold, Oliver Werner; Arsene, Ionut Cristian; Arslandok, Mesut; Audurier, Benjamin; Augustinus, Andre; Averbeck, Ralf Peter; Azmi, Mohd Danish; Badala, Angela; Baek, Yong Wook; Bagnasco, Stefano; Bailhache, Raphaelle Marie; Bala, Renu; Balasubramanian, Supraja; Baldisseri, Alberto; Baral, Rama Chandra; Barbano, Anastasia Maria; Barbera, Roberto; Barile, Francesco; Barnafoldi, Gergely Gabor; Barnby, Lee Stuart; Ramillien Barret, Valerie; Bartalini, Paolo; Barth, Klaus; Bartke, Jerzy Gustaw; Bartsch, Esther; Basile, Maurizio; Bastid, Nicole; Basu, Sumit; Bathen, Bastian; Batigne, Guillaume; Batista Camejo, Arianna; Batyunya, Boris; Batzing, Paul Christoph; Bearden, Ian Gardner; Beck, Hans; Bedda, Cristina; Behera, Nirbhay Kumar; Belikov, Iouri; Bellini, Francesca; Bello Martinez, Hector; Bellwied, Rene; Belmont Iii, Ronald John; Belmont Moreno, Ernesto; Belyaev, Vladimir; Benacek, Pavel; Bencedi, Gyula; Beole, Stefania; Berceanu, Ionela; Bercuci, Alexandru; Berdnikov, Yaroslav; Berenyi, Daniel; Bertens, Redmer Alexander; Berzano, Dario; Betev, Latchezar; Bhasin, Anju; Bhat, Inayat Rasool; Bhati, Ashok Kumar; Bhattacharjee, Buddhadeb; Bhom, Jihyun; Bianchi, Livio; Bianchi, Nicola; Bianchin, Chiara; Bielcik, Jaroslav; Bielcikova, Jana; Bilandzic, Ante; Biro, Gabor; Biswas, Rathijit; Biswas, Saikat; Bjelogrlic, Sandro; Blair, Justin Thomas; Blau, Dmitry; Blume, Christoph; Bock, Friederike; Bogdanov, Alexey; Boggild, Hans; Boldizsar, Laszlo; Bombara, Marek; Book, Julian Heinz; Borel, Herve; Borissov, Alexander; Borri, Marcello; Bossu, Francesco; Botta, Elena; Bourjau, Christian; Braun-Munzinger, Peter; Bregant, Marco; Breitner, Timo Gunther; Broker, Theo Alexander; Browning, Tyler Allen; Broz, Michal; Brucken, Erik Jens; Bruna, Elena; Bruno, Giuseppe Eugenio; Budnikov, Dmitry; Buesching, Henner; Bufalino, Stefania; Buncic, Predrag; Busch, Oliver; Buthelezi, Edith Zinhle; Bashir Butt, Jamila; Buxton, Jesse Thomas; Cabala, Jan; Caffarri, Davide; Cai, Xu; Caines, Helen Louise; Calero Diaz, Liliet; Caliva, Alberto; Calvo Villar, Ernesto; Camerini, Paolo; Carena, Francesco; Carena, Wisla; Carnesecchi, Francesca; Castillo Castellanos, Javier Ernesto; Castro, Andrew John; Casula, Ester Anna Rita; Ceballos Sanchez, Cesar; Cepila, Jan; Cerello, Piergiorgio; Cerkala, Jakub; Chang, Beomsu; Chapeland, Sylvain; Chartier, Marielle; Charvet, Jean-Luc Fernand; Chattopadhyay, Subhasis; Chattopadhyay, Sukalyan; Chauvin, Alex; Chelnokov, Volodymyr; Cherney, Michael Gerard; Cheshkov, Cvetan Valeriev; Cheynis, Brigitte; Chibante Barroso, Vasco Miguel; Dobrigkeit Chinellato, David; Cho, Soyeon; Chochula, Peter; Choi, Kyungeon; Chojnacki, Marek; Choudhury, Subikash; Christakoglou, Panagiotis; Christensen, Christian Holm; Christiansen, Peter; Chujo, Tatsuya; Chung, Suh-Urk; Cicalo, Corrado; Cifarelli, Luisa; Cindolo, Federico; Cleymans, Jean Willy Andre; Colamaria, Fabio Filippo; Colella, Domenico; Collu, Alberto; Colocci, Manuel; Conesa Balbastre, Gustavo; Conesa Del Valle, Zaida; Connors, Megan Elizabeth; Contreras Nuno, Jesus Guillermo; Cormier, Thomas Michael; Corrales Morales, Yasser; Cortes Maldonado, Ismael; Cortese, Pietro; Cosentino, Mauro Rogerio; Costa, Filippo; Crochet, Philippe; Cruz Albino, Rigoberto; Cuautle Flores, Eleazar; Cunqueiro Mendez, Leticia; Dahms, Torsten; Dainese, Andrea; Danisch, Meike Charlotte; Danu, Andrea; Das, Debasish; Das, Indranil; Das, Supriya; Dash, Ajay Kumar; Dash, Sadhana; De, Sudipan; De Caro, Annalisa; De Cataldo, Giacinto; De Conti, Camila; De Cuveland, Jan; De Falco, Alessandro; De Gruttola, Daniele; De Marco, Nora; De Pasquale, Salvatore; Deisting, Alexander; Deloff, Andrzej; Denes, Ervin Sandor; Deplano, Caterina; Dhankher, Preeti; Di Bari, Domenico; Di Mauro, Antonio; Di Nezza, Pasquale; Diaz Corchero, Miguel Angel; Dietel, Thomas; Dillenseger, Pascal; Divia, Roberto; Djuvsland, Oeystein; Dobrin, Alexandru Florin; Domenicis Gimenez, Diogenes; Donigus, Benjamin; Dordic, Olja; Drozhzhova, Tatiana; Dubey, Anand Kumar; Dubla, Andrea; Ducroux, Laurent; Dupieux, Pascal; Ehlers Iii, Raymond James; Elia, Domenico; Endress, Eric; Engel, Heiko; Epple, Eliane; Erazmus, Barbara Ewa; Erdemir, Irem; Erhardt, Filip; Espagnon, Bruno; Estienne, Magali Danielle; Esumi, Shinichi; Eum, Jongsik; Evans, David; Evdokimov, Sergey; Eyyubova, Gyulnara; Fabbietti, Laura; Fabris, Daniela; Faivre, Julien; Fantoni, Alessandra; Fasel, Markus; Feldkamp, Linus; Feliciello, Alessandro; Feofilov, Grigorii; Ferencei, Jozef; Fernandez Tellez, Arturo; Gonzalez Ferreiro, Elena; Ferretti, Alessandro; Festanti, Andrea; Feuillard, Victor Jose Gaston; Figiel, Jan; Araujo Silva Figueredo, Marcel; Filchagin, Sergey; Finogeev, Dmitry; Fionda, Fiorella; Fiore, Enrichetta Maria; Fleck, Martin Gabriel; Floris, Michele; Foertsch, Siegfried Valentin; Foka, Panagiota; Fokin, Sergey; Fragiacomo, Enrico; Francescon, Andrea; Frankenfeld, Ulrich Michael; Fronze, Gabriele Gaetano; Fuchs, Ulrich; Furget, Christophe; Furs, Artur; Fusco Girard, Mario; Gaardhoeje, Jens Joergen; Gagliardi, Martino; Gago Medina, Alberto Martin; Gallio, Mauro; Gangadharan, Dhevan Raja; Ganoti, Paraskevi; Gao, Chaosong; Garabatos Cuadrado, Jose; Garcia-Solis, Edmundo Javier; Gargiulo, Corrado; Gasik, Piotr Jan; Gauger, Erin Frances; Germain, Marie; Gheata, Andrei George; Gheata, Mihaela; Ghosh, Premomoy; Ghosh, Sanjay Kumar; Gianotti, Paola; Giubellino, Paolo; Giubilato, Piero; Gladysz-Dziadus, Ewa; Glassel, Peter; Gomez Coral, Diego Mauricio; Gomez Ramirez, Andres; Sanchez Gonzalez, Andres; Gonzalez, Victor; Gonzalez Zamora, Pedro; Gorbunov, Sergey; Gorlich, Lidia Maria; Gotovac, Sven; Grabski, Varlen; Grachov, Oleg Anatolievich; Graczykowski, Lukasz Kamil; Graham, Katie Leanne; Grelli, Alessandro; Grigoras, Alina Gabriela; Grigoras, Costin; Grigoryev, Vladislav; Grigoryan, Ara; Grigoryan, Smbat; Grynyov, Borys; Grion, Nevio; Gronefeld, Julius Maximilian; Grosse-Oetringhaus, Jan Fiete; Grosso, Raffaele; Guber, Fedor; Guernane, Rachid; Guerzoni, Barbara; Gulbrandsen, Kristjan Herlache; Gunji, Taku; Gupta, Anik; Gupta, Ramni; Haake, Rudiger; Haaland, Oystein Senneset; Hadjidakis, Cynthia Marie; Haiduc, Maria; Hamagaki, Hideki; Hamar, Gergoe; Hamon, Julien Charles; Harris, John William; Harton, Austin Vincent; Hatzifotiadou, Despina; Hayashi, Shinichi; Heckel, Stefan Thomas; Hellbar, Ernst; Helstrup, Haavard; Herghelegiu, Andrei Ionut; Herrera Corral, Gerardo Antonio; Hess, Benjamin Andreas; Hetland, Kristin Fanebust; Hillemanns, Hartmut; Hippolyte, Boris; Horak, David; Hosokawa, Ritsuya; Hristov, Peter Zahariev; Humanic, Thomas; Hussain, Nur; Hussain, Tahir; Hutter, Dirk; Hwang, Dae Sung; Ilkaev, Radiy; Inaba, Motoi; Incani, Elisa; Ippolitov, Mikhail; Irfan, Muhammad; Ivanov, Marian; Ivanov, Vladimir; Izucheev, Vladimir; Jacazio, Nicolo; Jacobs, Peter Martin; Jadhav, Manoj Bhanudas; Jadlovska, Slavka; Jadlovsky, Jan; Jahnke, Cristiane; Jakubowska, Monika Joanna; Jang, Haeng Jin; Janik, Malgorzata Anna; Pahula Hewage, Sandun; Jena, Chitrasen; Jena, Satyajit; Jimenez Bustamante, Raul Tonatiuh; Jones, Peter Graham; Jusko, Anton; Kalinak, Peter; Kalweit, Alexander Philipp; Kamin, Jason Adrian; Kang, Ju Hwan; Kaplin, Vladimir; Kar, Somnath; Karasu Uysal, Ayben; Karavichev, Oleg; Karavicheva, Tatiana; Karayan, Lilit; Karpechev, Evgeny; Kebschull, Udo Wolfgang; Keidel, Ralf; Keijdener, Darius Laurens; Keil, Markus; Khan, Mohammed Mohisin; Khan, Palash; Khan, Shuaib Ahmad; Khanzadeev, Alexei; Kharlov, Yury; Kileng, Bjarte; Kim, Do Won; Kim, Dong Jo; Kim, Daehyeok; Kim, Hyeonjoong; Kim, Jinsook; Kim, Minwoo; Kim, Se Yong; Kim, Taesoo; Kirsch, Stefan; Kisel, Ivan; Kiselev, Sergey; Kisiel, Adam Ryszard; Kiss, Gabor; Klay, Jennifer Lynn; Klein, Carsten; Klein, Jochen; Klein-Boesing, Christian; Klewin, Sebastian; Kluge, Alexander; Knichel, Michael Linus; Knospe, Anders Garritt; Kobdaj, Chinorat; Kofarago, Monika; Kollegger, Thorsten; Kolozhvari, Anatoly; Kondratev, Valerii; Kondratyeva, Natalia; Kondratyuk, Evgeny; Konevskikh, Artem; Kopcik, Michal; Kostarakis, Panagiotis; Kour, Mandeep; Kouzinopoulos, Charalampos; Kovalenko, Oleksandr; Kovalenko, Vladimir; Kowalski, Marek; Koyithatta Meethaleveedu, Greeshma; Kralik, Ivan; Kravcakova, Adela; Krivda, Marian; Krizek, Filip; Kryshen, Evgeny; Krzewicki, Mikolaj; Kubera, Andrew Michael; Kucera, Vit; Kuhn, Christian Claude; Kuijer, Paulus Gerardus; Kumar, Ajay; Kumar, Jitendra; Kumar, Lokesh; Kumar, Shyam; Kurashvili, Podist; Kurepin, Alexander; Kurepin, Alexey; Kuryakin, Alexey; Kweon, Min Jung; Kwon, Youngil; La Pointe, Sarah Louise; La Rocca, Paola; Ladron De Guevara, Pedro; Lagana Fernandes, Caio; Lakomov, Igor; Langoy, Rune; Lara Martinez, Camilo Ernesto; Lardeux, Antoine Xavier; Lattuca, Alessandra; Laudi, Elisa; Lea, Ramona; Leardini, Lucia; Lee, Graham Richard; Lee, Seongjoo; Lehas, Fatiha; Lemmon, Roy Crawford; Lenti, Vito; Leogrande, Emilia; Leon Monzon, Ildefonso; Leon Vargas, Hermes; Leoncino, Marco; Levai, Peter; Li, Shuang; Li, Xiaomei; Lien, Jorgen Andre; Lietava, Roman; Lindal, Svein; Lindenstruth, Volker; Lippmann, Christian; Lisa, Michael Annan; Ljunggren, Hans Martin; Lodato, Davide Francesco; Lonne, Per-Ivar; Loginov, Vitaly; Loizides, Constantinos; Lopez, Xavier Bernard; Lopez Torres, Ernesto; Lowe, Andrew John; Luettig, Philipp Johannes; Lunardon, Marcello; Luparello, Grazia; Lutz, Tyler Harrison; Maevskaya, Alla; Mager, Magnus; Mahajan, Sanjay; Mahmood, Sohail Musa; Maire, Antonin; Majka, Richard Daniel; Malaev, Mikhail; Maldonado Cervantes, Ivonne Alicia; Malinina, Liudmila; Mal'Kevich, Dmitry; Malzacher, Peter; Mamonov, Alexander; Manko, Vladislav; Manso, Franck; Manzari, Vito; Marchisone, Massimiliano; Mares, Jiri; Margagliotti, Giacomo Vito; Margotti, Anselmo; Margutti, Jacopo; Marin, Ana Maria; Markert, Christina; Marquard, Marco; Martin, Nicole Alice; Martin Blanco, Javier; Martinengo, Paolo; Martinez Hernandez, Mario Ivan; Martinez-Garcia, Gines; Martinez Pedreira, Miguel; Mas, Alexis Jean-Michel; Masciocchi, Silvia; Masera, Massimo; Masoni, Alberto; Mastroserio, Annalisa; Matyja, Adam Tomasz; Mayer, Christoph; Mazer, Joel Anthony; Mazzoni, Alessandra Maria; Mcdonald, Daniel; Meddi, Franco; Melikyan, Yuri; Menchaca-Rocha, Arturo Alejandro; Meninno, Elisa; Mercado-Perez, Jorge; Meres, Michal; Miake, Yasuo; Mieskolainen, Matti Mikael; Mikhaylov, Konstantin; Milano, Leonardo; Milosevic, Jovan; Mischke, Andre; Mishra, Aditya Nath; Miskowiec, Dariusz Czeslaw; Mitra, Jubin; Mitu, Ciprian Mihai; Mohammadi, Naghmeh; Mohanty, Bedangadas; Molnar, Levente; Montano Zetina, Luis Manuel; Montes Prado, Esther; Moreira De Godoy, Denise Aparecida; Perez Moreno, Luis Alberto; Moretto, Sandra; Morreale, Astrid; Morsch, Andreas; Muccifora, Valeria; Mudnic, Eugen; Muhlheim, Daniel Michael; Muhuri, Sanjib; Mukherjee, Maitreyee; Mulligan, James Declan; Gameiro Munhoz, Marcelo; Munzer, Robert Helmut; Murakami, Hikari; Murray, Sean; Musa, Luciano; Musinsky, Jan; Naik, Bharati; Nair, Rahul; Nandi, Basanta Kumar; Nania, Rosario; Nappi, Eugenio; Naru, Muhammad Umair; Ferreira Natal Da Luz, Pedro Hugo; Nattrass, Christine; Rosado Navarro, Sebastian; Nayak, Kishora; Nayak, Ranjit; Nayak, Tapan Kumar; Nazarenko, Sergey; Nedosekin, Alexander; Nellen, Lukas; Ng, Fabian; Nicassio, Maria; Niculescu, Mihai; Niedziela, Jeremi; Nielsen, Borge Svane; Nikolaev, Sergey; Nikulin, Sergey; Nikulin, Vladimir; Noferini, Francesco; Nomokonov, Petr; Nooren, Gerardus; Cabanillas Noris, Juan Carlos; Norman, Jaime; Nyanin, Alexander; Nystrand, Joakim Ingemar; Oeschler, Helmut Oskar; Oh, Saehanseul; Oh, Sun Kun; Ohlson, Alice Elisabeth; Okatan, Ali; Okubo, Tsubasa; Olah, Laszlo; Oleniacz, Janusz; Oliveira Da Silva, Antonio Carlos; Oliver, Michael Henry; Onderwaater, Jacobus; Oppedisano, Chiara; Orava, Risto; Oravec, Matej; Ortiz Velasquez, Antonio; Oskarsson, Anders Nils Erik; Otwinowski, Jacek Tomasz; Oyama, Ken; Ozdemir, Mahmut; Pachmayer, Yvonne Chiara; Pagano, Davide; Pagano, Paola; Paic, Guy; Pal, Susanta Kumar; Pan, Jinjin; Pandey, Ashutosh Kumar; Papikyan, Vardanush; Pappalardo, Giuseppe; Pareek, Pooja; Park, Woojin; Parmar, Sonia; Passfeld, Annika; Paticchio, Vincenzo; Patra, Rajendra Nath; Paul, Biswarup; Pei, Hua; Peitzmann, Thomas; Pereira Da Costa, Hugo Denis Antonio; Peresunko, Dmitry Yurevich; Perez Lara, Carlos Eugenio; Perez Lezama, Edgar; Peskov, Vladimir; Pestov, Yury; Petracek, Vojtech; Petrov, Viacheslav; Petrovici, Mihai; Petta, Catia; Piano, Stefano; Pikna, Miroslav; Pillot, Philippe; Ozelin De Lima Pimentel, Lais; Pinazza, Ombretta; Pinsky, Lawrence; Piyarathna, Danthasinghe; Ploskon, Mateusz Andrzej; Planinic, Mirko; Pluta, Jan Marian; Pochybova, Sona; Podesta Lerma, Pedro Luis Manuel; Poghosyan, Martin; Polishchuk, Boris; Poljak, Nikola; Poonsawat, Wanchaloem; Pop, Amalia; Porteboeuf, Sarah Julie; Porter, R Jefferson; Pospisil, Jan; Prasad, Sidharth Kumar; Preghenella, Roberto; Prino, Francesco; Pruneau, Claude Andre; Pshenichnov, Igor; Puccio, Maximiliano; Puddu, Giovanna; Pujahari, Prabhat Ranjan; Punin, Valery; Putschke, Jorn Henning; Qvigstad, Henrik; Rachevski, Alexandre; Raha, Sibaji; Rajput, Sonia; Rak, Jan; Rakotozafindrabe, Andry Malala; Ramello, Luciano; Rami, Fouad; Raniwala, Rashmi; Raniwala, Sudhir; Rasanen, Sami Sakari; Rascanu, Bogdan Theodor; Rathee, Deepika; Read, Kenneth Francis; Redlich, Krzysztof; Reed, Rosi Jan; Rehman, Attiq Ur; Reichelt, Patrick Simon; Reidt, Felix; Ren, Xiaowen; Renfordt, Rainer Arno Ernst; Reolon, Anna Rita; Reshetin, Andrey; Reygers, Klaus Johannes; Riabov, Viktor; Ricci, Renato Angelo; Richert, Tuva Ora Herenui; Richter, Matthias Rudolph; Riedler, Petra; Riegler, Werner; Riggi, Francesco; Ristea, Catalin-Lucian; Rocco, Elena; Rodriguez Cahuantzi, Mario; Rodriguez Manso, Alis; Roeed, Ketil; Rogochaya, Elena; Rohr, David Michael; Roehrich, Dieter; Ronchetti, Federico; Ronflette, Lucile; Rosnet, Philippe; Rossi, Andrea; Roukoutakis, Filimon; Roy, Ankhi; Roy, Christelle Sophie; Roy, Pradip Kumar; Rubio Montero, Antonio Juan; Rui, Rinaldo; Russo, Riccardo; Ryabinkin, Evgeny; Ryabov, Yury; Rybicki, Andrzej; Saarinen, Sampo; Sadhu, Samrangy; Sadovskiy, Sergey; Safarik, Karel; Sahlmuller, Baldo; Sahoo, Pragati; Sahoo, Raghunath; Sahoo, Sarita; Sahu, Pradip Kumar; Saini, Jogender; Sakai, Shingo; Saleh, Mohammad Ahmad; Salzwedel, Jai Samuel Nielsen; Sambyal, Sanjeev Singh; Samsonov, Vladimir; Sandor, Ladislav; Sandoval, Andres; Sano, Masato; Sarkar, Debojit; Sarkar, Nachiketa; Sarma, Pranjal; Scapparone, Eugenio; Scarlassara, Fernando; Schiaua, Claudiu Cornel; Schicker, Rainer Martin; Schmidt, Christian Joachim; Schmidt, Hans Rudolf; Schuchmann, Simone; Schukraft, Jurgen; Schulc, Martin; Schutz, Yves Roland; Schwarz, Kilian Eberhard; Schweda, Kai Oliver; Scioli, Gilda; Scomparin, Enrico; Scott, Rebecca Michelle; Sefcik, Michal; Seger, Janet Elizabeth; Sekiguchi, Yuko; Sekihata, Daiki; Selyuzhenkov, Ilya; Senosi, Kgotlaesele; Senyukov, Serhiy; Serradilla Rodriguez, Eulogio; Sevcenco, Adrian; Shabanov, Arseniy; Shabetai, Alexandre; Shadura, Oksana; Shahoyan, Ruben; Shahzad, Muhammed Ikram; Shangaraev, Artem; Sharma, Ankita; Sharma, Mona; Sharma, Monika; Sharma, Natasha; Sheikh, Ashik Ikbal; Shigaki, Kenta; Shou, Qiye; Shtejer Diaz, Katherin; Sibiryak, Yury; Siddhanta, Sabyasachi; Sielewicz, Krzysztof Marek; Siemiarczuk, Teodor; Silvermyr, David Olle Rickard; Silvestre, Catherine Micaela; Simatovic, Goran; Simonetti, Giuseppe; Singaraju, Rama Narayana; Singh, Ranbir; Singha, Subhash; Singhal, Vikas; Sinha, Bikash; Sarkar - Sinha, Tinku; Sitar, Branislav; Sitta, Mario; Skaali, Bernhard; Slupecki, Maciej; Smirnov, Nikolai; Snellings, Raimond; Snellman, Tomas Wilhelm; Song, Jihye; Song, Myunggeun; Song, Zixuan; Soramel, Francesca; Sorensen, Soren Pontoppidan; Derradi De Souza, Rafael; Sozzi, Federica; Spacek, Michal; Spiriti, Eleuterio; Sputowska, Iwona Anna; Spyropoulou-Stassinaki, Martha; Stachel, Johanna; Stan, Ionel; Stankus, Paul; Stenlund, Evert Anders; Steyn, Gideon Francois; Stiller, Johannes Hendrik; Stocco, Diego; Strmen, Peter; Alarcon Do Passo Suaide, Alexandre; Sugitate, Toru; Suire, Christophe Pierre; Suleymanov, Mais Kazim Oglu; Suljic, Miljenko; Sultanov, Rishat; Sumbera, Michal; Sumowidagdo, Suharyo; Szabo, Alexander; Szanto De Toledo, Alejandro; Szarka, Imrich; Szczepankiewicz, Adam; Szymanski, Maciej Pawel; Tabassam, Uzma; Takahashi, Jun; Tambave, Ganesh Jagannath; Tanaka, Naoto; Tarhini, Mohamad; Tariq, Mohammad; Tarzila, Madalina-Gabriela; Tauro, Arturo; Tejeda Munoz, Guillermo; Telesca, Adriana; Terasaki, Kohei; Terrevoli, Cristina; Teyssier, Boris; Thaeder, Jochen Mathias; Thakur, Dhananjaya; Thomas, Deepa; Tieulent, Raphael Noel; Timmins, Anthony Robert; Toia, Alberica; Trogolo, Stefano; Trombetta, Giuseppe; Trubnikov, Victor; Trzaska, Wladyslaw Henryk; Tsuji, Tomoya; Tumkin, Alexandr; Turrisi, Rosario; Tveter, Trine Spedstad; Ullaland, Kjetil; Uras, Antonio; Usai, Gianluca; Utrobicic, Antonija; Vala, Martin; Valencia Palomo, Lizardo; Vallero, Sara; Van Der Maarel, Jasper; Van Hoorne, Jacobus Willem; Van Leeuwen, Marco; Vanat, Tomas; Vande Vyvre, Pierre; Varga, Dezso; Vargas Trevino, Aurora Diozcora; Vargyas, Marton; Varma, Raghava; Vasileiou, Maria; Vasiliev, Andrey; Vauthier, Astrid; Vechernin, Vladimir; Veen, Annelies Marianne; Veldhoen, Misha; Velure, Arild; Vercellin, Ermanno; Vergara Limon, Sergio; Vernet, Renaud; Verweij, Marta; Vickovic, Linda; Viesti, Giuseppe; Viinikainen, Jussi Samuli; Vilakazi, Zabulon; Villalobos Baillie, Orlando; Villatoro Tello, Abraham; Vinogradov, Alexander; Vinogradov, Leonid; Vinogradov, Yury; Virgili, Tiziano; Vislavicius, Vytautas; Viyogi, Yogendra; Vodopyanov, Alexander; Volkl, Martin Andreas; Voloshin, Kirill; Voloshin, Sergey; Volpe, Giacomo; Von Haller, Barthelemy; Vorobyev, Ivan; Vranic, Danilo; Vrlakova, Janka; Vulpescu, Bogdan; Wagner, Boris; Wagner, Jan; Wang, Hongkai; Wang, Mengliang; Watanabe, Daisuke; Watanabe, Yosuke; Weber, Michael; Weber, Steffen Georg; Weiser, Dennis Franz; Wessels, Johannes Peter; Westerhoff, Uwe; Whitehead, Andile Mothegi; Wiechula, Jens; Wikne, Jon; Wilk, Grzegorz Andrzej; Wilkinson, Jeremy John; Williams, Crispin; Windelband, Bernd Stefan; Winn, Michael Andreas; Yang, Hongyan; Yang, Ping; Yano, Satoshi; Yasin, Zafar; Yin, Zhongbao; Yokoyama, Hiroki; Yoo, In-Kwon; Yoon, Jin Hee; Yurchenko, Volodymyr; Yushmanov, Igor; Zaborowska, Anna; Zaccolo, Valentina; Zaman, Ali; Zampolli, Chiara; Correia Zanoli, Henrique Jose; Zaporozhets, Sergey; Zardoshti, Nima; Zarochentsev, Andrey; Zavada, Petr; Zavyalov, Nikolay; Zbroszczyk, Hanna Paulina; Zgura, Sorin Ion; Zhalov, Mikhail; Zhang, Haitao; Zhang, Xiaoming; Zhang, Yonghong; Chunhui, Zhang; Zhang, Zuman; Zhao, Chengxin; Zhigareva, Natalia; Zhou, Daicui; Zhou, You; Zhou, Zhuo; Zhu, Hongsheng; Zhu, Jianhui; Zichichi, Antonino; Zimmermann, Alice; Zimmermann, Markus Bernhard; Zinovjev, Gennady; Zyzak, Maksym
2016-01-01
We present a Bayesian approach to particle identification (PID) within the ALICE experiment. The aim is to more effectively combine the particle identification capabilities of its various detectors. After a brief explanation of the adopted methodology and formalism, the performance of the Bayesian PID approach for charged pions, kaons and protons in the central barrel of ALICE is studied. PID is performed via measurements of specific energy loss (dE/dx) and time-of-flight. PID efficiencies and misidentification probabilities are extracted and compared with Monte Carlo simulations using high purity samples of identified particles in the decay channels ${\\rm K}_{\\rm S}^{\\rm 0}\\rightarrow \\pi^+\\pi^-$, $\\phi\\rightarrow {\\rm K}^-{\\rm K}^+$ and $\\Lambda\\rightarrow{\\rm p}\\pi^-$ in p–Pb collisions at $\\sqrt{s_{\\rm NN}}= 5.02$TeV. In order to thoroughly assess the validity of the Bayesian approach, this methodology was used to obtain corrected $p_{\\rm T}$ spectra of pions, kaons, protons, and D$^0$ mesons in pp coll...
Bayesian Analysis of Individual Level Personality Dynamics
Directory of Open Access Journals (Sweden)
Edward Cripps
2016-07-01
Full Text Available A Bayesian technique with analyses of within-person processes at the level of the individual is presented. The approach is used to examine if the patterns of within-person responses on a 12 trial simulation task are consistent with the predictions of ITA theory (Dweck, 1999. ITA theory states that the performance of an individual with an entity theory of ability is more likely to spiral down following a failure experience than the performance of an individual with an incremental theory of ability. This is because entity theorists interpret failure experiences as evidence of a lack of ability, which they believe is largely innate and therefore relatively ﬁxed; whilst incremental theorists believe in the malleability of abilities and interpret failure experiences as evidence of more controllable factors such as poor strategy or lack of effort. The results of our analyses support ITA theory at both the within- and between-person levels of analyses and demonstrate the beneﬁts of Bayesian techniques for the analysis of within-person processes. These include more formal speciﬁcation of the theory and the ability to draw inferences about each individual, which allows for more nuanced interpretations of individuals within a personality category, such as differences in the individual probabilities of spiralling. While Bayesian techniques have many potential advantages for the analyses of within-person processes at the individual level, ease of use is not one of them for psychologists trained in traditional frequentist statistical techniques.
Bayesian Recurrent Neural Network for Language Modeling.
Chien, Jen-Tzung; Ku, Yuan-Chu
2016-02-01
A language model (LM) is calculated as the probability of a word sequence that provides the solution to word prediction for a variety of information systems. A recurrent neural network (RNN) is powerful to learn the large-span dynamics of a word sequence in the continuous space. However, the training of the RNN-LM is an ill-posed problem because of too many parameters from a large dictionary size and a high-dimensional hidden layer. This paper presents a Bayesian approach to regularize the RNN-LM and apply it for continuous speech recognition. We aim to penalize the too complicated RNN-LM by compensating for the uncertainty of the estimated model parameters, which is represented by a Gaussian prior. The objective function in a Bayesian classification network is formed as the regularized cross-entropy error function. The regularized model is constructed not only by calculating the regularized parameters according to the maximum a posteriori criterion but also by estimating the Gaussian hyperparameter by maximizing the marginal likelihood. A rapid approximation to a Hessian matrix is developed to implement the Bayesian RNN-LM (BRNN-LM) by selecting a small set of salient outer-products. The proposed BRNN-LM achieves a sparser model than the RNN-LM. Experiments on different corpora show the robustness of system performance by applying the rapid BRNN-LM under different conditions.
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 Inference of a Multivariate Regression Model
Directory of Open Access Journals (Sweden)
Marick S. Sinay
2014-01-01
Full Text Available We explore Bayesian inference of a multivariate linear regression model with use of a flexible prior for the covariance structure. The commonly adopted Bayesian setup involves the conjugate prior, multivariate normal distribution for the regression coefficients and inverse Wishart specification for the covariance matrix. Here we depart from this approach and propose a novel Bayesian estimator for the covariance. A multivariate normal prior for the unique elements of the matrix logarithm of the covariance matrix is considered. Such structure allows for a richer class of prior distributions for the covariance, with respect to strength of beliefs in prior location hyperparameters, as well as the added ability, to model potential correlation amongst the covariance structure. The posterior moments of all relevant parameters of interest are calculated based upon numerical results via a Markov chain Monte Carlo procedure. The Metropolis-Hastings-within-Gibbs algorithm is invoked to account for the construction of a proposal density that closely matches the shape of the target posterior distribution. As an application of the proposed technique, we investigate a multiple regression based upon the 1980 High School and Beyond Survey.
Bayesian Methods for Radiation Detection and Dosimetry
International Nuclear Information System (INIS)
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 compartmental activities. From the estimated probability densities of the model parameters we were able to derive the densities for compartmental activities for a two compartment catenary model at different times. We also calculated the average activities and their standard deviation for a simple two compartment model
Bayesian and Dempster–Shafer fusion
Indian Academy of Sciences (India)
Subhash Challa; Don Koks
2004-04-01
The Kalman Filter is traditionally viewed as a prediction–correction ﬁltering algorithm. In this work we show that it can be viewed as a Bayesian fusion algorithm and derive it using Bayesian arguments. We begin with an outline of Bayes theory, using it to discuss well-known quantities such as priors, likelihood and posteriors, and we provide the basic Bayesian fusion equation. We derive the Kalman Filter from this equation using a novel method to evaluate the Chapman–Kolmogorov prediction integral. We then use the theory to fuse data from multiple sensors. Vying with this approach is the Dempster–Shafer theory, which deals with measures of “belief”, and is based on the nonclassical idea of “mass” as opposed to probability. Although these two measures look very similar, there are some differences. We point them out through outlining the ideas of the Dempster– Shafer theory and presenting the basic Dempster–Shafer fusion equation. Finally we compare the two methods, and discuss the relative merits and demerits using an illustrative example.
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
Mondrian Forests: Efficient Online Random Forests
Lakshminarayanan, Balaji; Roy, Daniel M.; Teh, Yee Whye
2014-01-01
Ensembles of randomized decision trees, usually referred to as random forests, are widely used for classification and regression tasks in machine learning and statistics. Random forests achieve competitive predictive performance and are computationally efficient to train and test, making them excellent candidates for real-world prediction tasks. The most popular random forest variants (such as Breiman's random forest and extremely randomized trees) operate on batches of training data. Online ...
Evidence and Implications of Frequent Fires in Ancient Shrub Tundra
Energy Technology Data Exchange (ETDEWEB)
Higuera, P E; Brubaker, L B; Anderson, P M; Brown, T A; Kennedy, A T; Hu, F S
2008-03-06
Understanding feedbacks between terrestrial and atmospheric systems is vital for predicting the consequences of global change, particularly in the rapidly changing Arctic. Fire is a key process in this context, but the consequences of altered fire regimes in tundra ecosystems are rarely considered, largely because tundra fires occur infrequently on the modern landscape. We present paleoecological data that indicate frequent tundra fires in northcentral Alaska between 14,000 and 10,000 years ago. Charcoal and pollen from lake sediments reveal that ancient birchdominated shrub tundra burned as often as modern boreal forests in the region, every 144 years on average (+/- 90 s.d.; n = 44). Although paleoclimate interpretations and data from modern tundra fires suggest that increased burning was aided by low effective moisture, vegetation cover clearly played a critical role in facilitating the paleo-fires by creating an abundance of fine fuels. These records suggest that greater fire activity will likely accompany temperature-related increases in shrub-dominated tundra predicted for the 21st century and beyond. Increased tundra burning will have broad impacts on physical and biological systems as well as land-atmosphere interactions in the Arctic, including the potential to release stored organic carbon to the atmosphere.
Rise and fall of Kantu: A historical study of an ancient Tibeto-Burmese speaking group
Institute of Scientific and Technical Information of China (English)
He Ping
2006-01-01
On the basis of Chinese records and previous academic achievements in and outside China,the author makes a deeper study on the history of Kantu.As an ancient Tibeto-Burmese speaking group,Kantu was likely to have developed from the Qiongdu(Kontu)of Xinan yi(ancient ethnic groups in southwestern China).During the 12th-13th centuries,the Kantu group resided in an extensive area expanding from the border area between present Sichuan and Yunnan provinces of China to Burma.In the late 13th century,the Yuan troops occupied the area of Kantu.Since then,there have been no more record about Kantu in Chinese annals,and they were likely merged into the groups of"Luoluo"(Lolo).In Burma,most of the Kantu people had been merged into the local peoples,with only a few remaining in remote mountain forests of northern Burma and still keeping their own name and customs.Thus,these people ale lust the living sources for our studies on ancient Kantu.
Directory of Open Access Journals (Sweden)
Yufei Huang
2007-06-01
Full Text Available Reverse engineering of genetic regulatory networks from time series microarray data are investigated. We propose a dynamic Bayesian networks (DBNs modeling and a full Bayesian learning scheme. The proposed DBN directly models the continuous expression levels and also is associated with parameters that indicate the degree as well as the type of regulations. To learn the network from data, we proposed a reversible jump Markov chain Monte Carlo (RJMCMC algorithm. The RJMCMC algorithm can provide not only more accurate inference results than the deterministic alternative algorithms but also an estimate of the a posteriori probabilities (APPs of the network topology. The estimated APPs provide useful information on the confidence of the inferred results and can also be used for efficient Bayesian data integration. The proposed approach is tested on yeast cell cycle microarray data and the results are compared with the KEGG pathway map.
Learning Local Components to Understand Large Bayesian Networks
DEFF Research Database (Denmark)
Zeng, Yifeng; Xiang, Yanping; Cordero, Jorge;
2009-01-01
Bayesian networks are known for providing an intuitive and compact representation of probabilistic information and allowing the creation of models over a large and complex domain. Bayesian learning and reasoning are nontrivial for a large Bayesian network. In parallel, it is a tough job for users...... (domain experts) to extract accurate information from a large Bayesian network due to dimensional difficulty. We define a formulation of local components and propose a clustering algorithm to learn such local components given complete data. The algorithm groups together most inter-relevant attributes...... in a domain. We evaluate its performance on three benchmark Bayesian networks and provide results in support. We further show that the learned components may represent local knowledge more precisely in comparison to the full Bayesian networks when working with a small amount of data....
What do we know about our graduates? Graduate analysis for forest sciences and related curricula
Schmidt, P.; Lewark, S.; Strange, N.
2010-01-01
Forestry as such is an old trade; already the ancient Romans did it. Its education is less old, about two centuries. Apparently, as Lewark remarked in his introduction, in general foresters educated at universities matched the need of the forestry sector.. Only about 40 years ago, the need to know m
Bayesian networks as a tool for epidemiological systems analysis
Lewis, F.I.
2012-01-01
Bayesian network analysis is a form of probabilistic modeling which derives from empirical data a directed acyclic graph (DAG) describing the dependency structure between random variables. Bayesian networks are increasingly finding application in areas such as computational and systems biology, and more recently in epidemiological analyses. The key distinction between standard empirical modeling approaches, such as generalised linear modeling, and Bayesian network analyses is that the latter ...
Small sample Bayesian analyses in assessment of weapon performance
Institute of Scientific and Technical Information of China (English)
无
2007-01-01
Abundant test data are required in assessment of weapon performance.When weapon test data are insufficient,Bayesian analyses in small sample circumstance should be considered and the test data should be provided by simulations.The several Bayesian approaches are discussed and some limitations are founded.An improvement is put forward after limitations of Bayesian approaches available are analyzed and t he improved approach is applied to assessment of some new weapon performance.
BAYESIAN ESTIMATION OF RELIABILITY IN TWOPARAMETER GEOMETRIC DISTRIBUTION
Directory of Open Access Journals (Sweden)
Sudhansu S. Maiti
2015-12-01
Full Text Available Bayesian estimation of reliability of a component, tR ( = P(X ≥ t, when X follows two-parameter geometric distribution, has been considered. Maximum Likelihood Estimator (MLE, an Unbiased Estimator and Bayesian Estimator have been compared. Bayesian estimation of component reliability R = P ( X ≤ Y , arising under stress-strength setup, when Y is assumed to follow independent two-parameter geometric distribution has also been discussed assuming independent priors for parameters under different loss functions.
Chain ladder method: Bayesian bootstrap versus classical bootstrap
Peters, Gareth W.; Mario V. W\\"uthrich; Shevchenko, Pavel V.
2010-01-01
The intention of this paper is to estimate a Bayesian distribution-free chain ladder (DFCL) model using approximate Bayesian computation (ABC) methodology. We demonstrate how to estimate quantities of interest in claims reserving and compare the estimates to those obtained from classical and credibility approaches. In this context, a novel numerical procedure utilising Markov chain Monte Carlo (MCMC), ABC and a Bayesian bootstrap procedure was developed in a truly distribution-free setting. T...
A tutorial introduction to Bayesian models of cognitive development
Perfors, Amy; Tenenbaum, Joshua B.; Griffiths, Thomas L.; Xu, Fei
2010-01-01
We present an introduction to Bayesian inference as it is used in probabilistic models of cognitive development. Our goal is to provide an intuitive and accessible guide to the what, the how, and the why of the Bayesian approach: what sorts of problems and data the framework is most relevant for, and how and why it may be useful for developmentalists. We emphasize a qualitative understanding of Bayesian inference, but also include information about additional resources for those interested in...
Bayesian just-so stories in psychology and neuroscience
Bowers, J.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 three main arguments. First, we show that the empirical evidence for Bayesian theories in psychology is weak at best. This weakness relates to the many arbitrary ways that priors, likelihoods, and utility functions can be altered in order to account fo...
Bayesian just-so stories in cognitive psychology and neuroscience.
Bowers, J.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 three main arguments. First, we show that the empirical evidence for Bayesian theories in psychology is weak at best. This weakness relates to the many arbitrary ways that priors, likelihoods, and utility functions can be altered in order to account fo...
The Bayesian Modelling Of Inflation Rate In Romania
Mihaela Simionescu
2014-01-01
Bayesian econometrics knew a considerable increase in popularity in the last years, joining the interests of various groups of researchers in economic sciences and additional ones as specialists in econometrics, commerce, industry, marketing, finance, micro-economy, macro-economy and other domains. The purpose of this research is to achieve an introduction in Bayesian approach applied in economics, starting with Bayes theorem. For the Bayesian linear regression models the methodology of estim...
Bayesian non- and semi-parametric methods and applications
Rossi, Peter
2014-01-01
This book reviews and develops Bayesian non-parametric and semi-parametric methods for applications in microeconometrics and quantitative marketing. Most econometric models used in microeconomics and marketing applications involve arbitrary distributional assumptions. As more data becomes available, a natural desire to provide methods that relax these assumptions arises. Peter Rossi advocates a Bayesian approach in which specific distributional assumptions are replaced with more flexible distributions based on mixtures of normals. The Bayesian approach can use either a large but fixed number