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.
Modelling biogeochemical cycles in forest ecosystems: a Bayesian approach
Bagnara, Maurizio
2015-01-01
Forest models are tools for explaining and predicting the dynamics of forest ecosystems. They simulate forest behavior by integrating information on the underlying processes in trees, soil and atmosphere. Bayesian calibration is the application of probability theory to parameter estimation. It is a method, applicable to all models, that quantifies output uncertainty and identifies key parameters and variables. This study aims at testing the Bayesian procedure for calibration to different t...
Dating ancient Chinese celadon porcelain by neutron activation analysis and bayesian classification
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)
A Very Simple Safe-Bayesian Random Forest.
Quadrianto, Novi; Ghahramani, Zoubin
2015-06-01
Random forests works by averaging several predictions of de-correlated trees. We show a conceptually radical approach to generate a random forest: random sampling of many trees from a prior distribution, and subsequently performing a weighted ensemble of predictive probabilities. Our approach uses priors that allow sampling of decision trees even before looking at the data, and a power likelihood that explores the space spanned by combination of decision trees. While each tree performs Bayesian inference to compute its predictions, our aggregation procedure uses the power likelihood rather than the likelihood and is therefore strictly speaking not Bayesian. Nonetheless, we refer to it as a Bayesian random forest but with a built-in safety. The safeness comes as it has good predictive performance even if the underlying probabilistic model is wrong. We demonstrate empirically that our Safe-Bayesian random forest outperforms MCMC or SMC based Bayesian decision trees in term of speed and accuracy, and achieves competitive performance to entropy or Gini optimised random forest, yet is very simple to construct. PMID:26357350
A Bayesian spatio-temporal analysis of forest fires in Portugal
Silva, Giovani Loiola; Dias, Maria Inês
2013-01-01
In the last decade, forest fires have become a natural disaster in Portugal, causing great forest devastation, leading to both economic and environmental losses and putting at risk populations and the livelihoods of the forest itself. In this work, we present Bayesian hierarchical models to analyze spatio-temporal fire data on the proportion of burned area in Portugal, by municipalities and over three decades. Mixture of distributions was employed to model jointly the proportion of area burn...
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
Bayesian chronological modeling of SunWatch, a fort ancient village in Dayton, Ohio
Krus, A.M.; Cook, R.; Hamilton, W.D.
2015-01-01
Radiocarbon results from houses, pits, and burials at the SunWatch site, Dayton, Ohio, are presented within an interpretative Bayesian statistical framework. The primary model incorporates dates from archaeological features in an unordered phase and uses charcoal outlier modeling (Bronk Ramsey 2009b) to account for issues of wood charcoal 14C dates predating their context. The results of the primary model estimate occupation lasted for 1–245 yr (95% probability), starting in cal AD 1175–1385 ...
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
Whitehouse, Nicki J.
2006-08-01
This paper presents a new review of our knowledge of the ancient forest beetle fauna from Holocene archaeological and palaeoecological sites in Great Britain and Ireland. It examines the colonisation, dispersal and decline of beetle species, highlighting the scale and nature of human activities in the shaping of the landscape of the British Isles. In particular, the paper discusses effects upon the insect fauna, and examines in detail the fossil record from the Humberhead Levels, eastern England. It discusses the local extirpation of up to 40 species in Britain and 15 species in Ireland. An evaluation of the timing of extirpations is made, suggesting that many species in Britain disappear from the fossil record between ca 3000 and 1000 cal BC (ca 5000-3000 cal BP), although some taxa may well have survived until considerably later. In Ireland, there are two distinct trends, with a group of species which seem to be absent after ca 2000 cal BC (ca 4000 cal BP) and a further group which survives until at least as late as the medieval period. The final clearance of the Irish landscape over the last few hundred years was so dramatic, however, that some species which are not especially unusual in a British context were decimated. Reasons behind the extirpation of taxa are examined in detail, and include a combination of forest clearance and human activities, isolation of populations, lack of temporal continuity of habitats, edaphic and competition factors affecting distribution of host trees (particularly pine), lack of forest fires and a decline in open forest systems. The role of climate change in extirpations is also evaluated. Consideration is given to the significance of these specialised ancient forest inhabitants in Ireland in the absence of an early Holocene land-bridge which suggests that colonisation was aided by other mechanisms, such as human activities and wood rafting. Finally, the paper discusses the Continental origins of the British and Irish fauna and
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
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
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
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
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.
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.
Pollination biology of the urban populations of an ancient forest, spring ephemeral plant
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.
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
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
Ball, Jessica Lynne
Light Detection and Ranging (LiDAR) data has shown great potential to estimate spatially explicit forest variables, including above-ground biomass, stem density, tree height, and more. Due to its ability to garner information about the vertical and horizontal structure of forest canopies effectively and efficiently, LiDAR sensors have played a key role in the development of operational air and space-borne instruments capable of gathering information about forest structure at regional, continental, and global scales. Combining LiDAR datasets with field-based validation measurements to build predictive models is becoming an attractive solution to the problem of quantifying and mapping forest structure for private forest land owners and local, state, and federal government entities alike. As with any statistical model using spatially indexed data, the potential to violate modeling assumptions resulting from spatial correlation is high. This thesis explores several different modeling frameworks that aim to accommodate correlation structures within model residuals. The development is motivated using LiDAR and forest inventory datasets. Special attention is paid to estimation and propagation of parameter and model uncertainty through to prediction units. Inference follows a Bayesian statistical paradigm. Results suggest the proposed frameworks help ensure model assumptions are met and prediction performance can be improved by pursuing spatially enabled models.
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
Performance Analysis of Random Forests with SVM and KNN in Classification of Ancient Kannada Scripts
Soumya A
2014-07-01
Full Text Available Ancient inscriptions which reveal the details of yester years are difficult to interpret by modern readers and efforts are being made in automating such tasks of deciphering historical records. The Kannada script which is used to write in Kannada language has gradually evolved from the ancient script known as Brahmi. Kannada script has traveled a long way from the earlier Brahmi model and has undergone a number of changes during the regimes of Ashoka, Shatavahana, Kadamba, Ganga, Rashtrakuta, Chalukya, Hoysala , Vijayanagara and Wodeyar dynasties. In this paper we discuss on Classification of ancient Kannada Scripts during three different periods Ashoka, Kadamba and Satavahana. A reconstructed grayscale ancient Kannada epigraph image is input, which is binarized using Otsu’s method. Normalized Central and Zernike Moment features are extracted for classification. The RF Classifier designed is tested on handwritten base characters belonging to Ashoka, Satavahana and Kadamba dynasties. For each dynasty, 105 handwritten samples with 35 base characters are considered. The classification rates for the training and testing base characters from Satavahana period, for varying number of trees and thresholds of RF are determined. Finally a Comparative analysis of the Classification rates is made for the designed RF with SVM and k-NN classifiers, for the ancient Kannada base characters from 3 different eras Ashoka, Kadamba and Satavahana period.
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
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...
Richness of Ancient Forest Plant Species Indicates Suitable Habitats for Macrofungi
Hofmeister, J.; Hošek, J.; Brabec, Marek; Dvořák, D.; Beran, M.; Deckerová, H.; Burel, J.; Kříž, M.; Borovička, Jan; Běťák, J.; Vašutová, Martina
2014-01-01
Roč. 23, č. 8 (2014), s. 2015-2031. ISSN 0960-3115 Grant ostatní: GA MŽP(CZ) SP/2D1/146/08 Institutional support: RVO:67985807 ; RVO:67985831 ; RVO:67179843 Keywords : diversity * forest continuity * forest management * Herb-layer plant species * red-listed species * species richness * surrogacy Subject RIV: BB - Applied Statistics, Operational Research; EH - Ecology, Behaviour (GLU-S); EH - Ecology, Behaviour (UEK-B) Impact factor: 2.365, year: 2014
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.
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...
Insect leaf-chewing damage tracks herbivore richness in modern and ancient forests.
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.
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 ...
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. PMID:20669043
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.
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.
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…
Willerslev, Eske; Cooper, Alan
2004-01-01
In the past two decades, ancient DNA research has progressed from the retrieval of small fragments of mitochondrial DNA from a few late Holocene specimens, to large-scale studies of ancient populations, phenotypically important nuclear loci, and even whole mitochondrial genome sequences of extinct species. However, the field is still regularly marred by erroneous reports, which underestimate the extent of contamination within laboratories and samples themselves. An improved understanding of t...
Mitochondrial phylogenomics of modern and ancient equids
Vilstrup, Julia T; Seguin-Orlando, Andaine; Stiller, Mathias; Ginolhac, Aurelien; Raghavan, Maanasa; Nielsen, Sandra C A; Weinstock, Jacobo; Froese, Duane; Vasiliev, Sergei K; Ovodov, Nikolai D; Clary, Joel; Helgen, Kristofer M; Fleischer, Robert C; Cooper, Alan; Shapiro, Beth; Orlando, Ludovic Antoine Alexandre
2013-01-01
sequences from all seven extant lineages within the genus Equus. Bayesian and Maximum Likelihood phylogenetic inference confirms that zebras are monophyletic within the genus, and the Plains and Grevy's zebras form a well-supported monophyletic group. Using ancient DNA techniques, we further characterize...
The forest are subject to many direct and indirect influences, apart from atmospheric pollutants and the potential effects of climatic changes, timber production and hunting have a major impact in the Austrian forests. Ozone, sulfur dioxide, nitrogen oxides, ammonia, inorganic fluoride, chloride compounds, heavy metals (cadmium and lead), organic pollutants (chlorinated hydrocarbons, trichloroacetic acid and nitrophenols), acidifying compounds and eutrophying compounds are the main forest pollutants. As forests cover nearly 50 % of the Austrian territory, changes affecting them constitute a potentially significant parameter in the national greenhouse gas balance. Carbon stocks and the annual carbon balance were calculated and a estimation of the potential impact of climate change by means of dynamic computer simulation and risk assesment were performed. The results are illustrated in a cartographic chart. Other topics discussed in this chapter are forest management, forest damage (game, cattle, abiotic and biotic influences), changes in land use, biodiversity, crown condition and long-term monitoring to determine the impact of environmental stress. Figs. 2, Table 1. (nevyjel)
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
Der Sarkissian, Clio; Allentoft, Morten Erik; Avila Arcos, Maria del Carmen;
2015-01-01
The past decade has witnessed a revolution in ancient DNA (aDNA) research. Although the field's focus was previously limited to mitochondrial DNA and a few nuclear markers, whole genome sequences from the deep past can now be retrieved. This breakthrough is tightly connected to the massive sequence...... increasing the number of sequence reads to billions effectively means that contamination issues that have haunted aDNA research for decades, particularly in human studies, can now be efficiently and confidently quantified. At present, whole genomes have been sequenced from ancient anatomically modern humans......, 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...
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
Bayesian Magic in Asteroseismology
Kallinger, T.
2015-09-01
Only a few years ago asteroseismic observations were so rare that scientists had plenty of time to work on individual data sets. They could tune their algorithms in any possible way to squeeze out the last bit of information. Nowadays this is impossible. With missions like MOST, CoRoT, and Kepler we basically drown in new data every day. To handle this in a sufficient way statistical methods become more and more important. This is why Bayesian techniques started their triumph march across asteroseismology. I will go with you on a journey through Bayesian Magic Land, that brings us to the sea of granulation background, the forest of peakbagging, and the stony alley of model comparison.
A Bayesian Modelling of Wildfires in Portugal
Silva, Giovani L.; Soares, Paulo; Marques, Susete; Dias, Inês M.; Oliveira, Manuela M.; Borges, Guilherme J.
2015-01-01
In the last decade wildfires became a serious problem in Portugal due to different issues such as climatic characteristics and nature of Portuguese forest. In order to analyse wildfire data, we employ beta regression for modelling the proportion of burned forest area, under a Bayesian perspective. Our main goal is to find out fire risk factors that influence the proportion of area burned and what may make a forest type susceptible or resistant to fire. Then, we analyse wildfire...
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.
Kirstein, Roland
2005-01-01
This paper presents a modification of the inspection game: The ?Bayesian Monitoring? model rests on the assumption that judges are interested in enforcing compliant behavior and making correct decisions. They may base their judgements on an informative but imperfect signal which can be generated costlessly. In the original inspection game, monitoring is costly and generates a perfectly informative signal. While the inspection game has only one mixed strategy equilibrium, three Perfect Bayesia...
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
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…
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
Jensen, Finn Verner; Nielsen, Thomas Dyhre
2016-01-01
Mathematically, a Bayesian graphical model is a compact representation of the joint probability distribution for a set of variables. The most frequently used type of Bayesian graphical models are Bayesian networks. The structural part of a Bayesian graphical model is a graph consisting of nodes and...... largely due to the availability of efficient inference algorithms for answering probabilistic queries about the states of the variables in the network. Furthermore, to support the construction of Bayesian network models, learning algorithms are also available. We give an overview of the Bayesian network...
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.
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)
Rubin, Donald B.
1981-01-01
The Bayesian bootstrap is the Bayesian analogue of the bootstrap. Instead of simulating the sampling distribution of a statistic estimating a parameter, the Bayesian bootstrap simulates the posterior distribution of the parameter; operationally and inferentially the methods are quite similar. Because both methods of drawing inferences are based on somewhat peculiar model assumptions and the resulting inferences are generally sensitive to these assumptions, neither method should be applied wit...
Ancient and modern environmental DNA
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....../Holocene transition, with implications for the extinction of megafauna. Furthermore, eDNA can reflect the biodiversity of extant flora and fauna, both qualitatively and quantitatively, allowing detection of rare species. As such, trace studies of plant and vertebrate DNA in the environment have revolutionized our...
Bayesian statistics an introduction
Lee, Peter M
2012-01-01
Bayesian Statistics is the school of thought that combines prior beliefs with the likelihood of a hypothesis to arrive at posterior beliefs. The first edition of Peter Lee’s book appeared in 1989, but the subject has moved ever onwards, with increasing emphasis on Monte Carlo based techniques. This new fourth edition looks at recent techniques such as variational methods, Bayesian importance sampling, approximate Bayesian computation and Reversible Jump Markov Chain Monte Carlo (RJMCMC), providing a concise account of the way in which the Bayesian approach to statistics develops as wel
Understanding Computational Bayesian Statistics
Bolstad, William M
2011-01-01
A hands-on introduction to computational statistics from a Bayesian point of view Providing a solid grounding in statistics while uniquely covering the topics from a Bayesian perspective, Understanding Computational Bayesian Statistics successfully guides readers through this new, cutting-edge approach. With its hands-on treatment of the topic, the book shows how samples can be drawn from the posterior distribution when the formula giving its shape is all that is known, and how Bayesian inferences can be based on these samples from the posterior. These ideas are illustrated on common statistic
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…
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...
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.
Bayesian exploratory factor analysis
Gabriella Conti; Sylvia Frühwirth-Schnatter; James Heckman; Rémi Piatek
2014-01-01
This paper develops and applies a Bayesian approach to Exploratory Factor Analysis that improves on ad hoc classical approaches. Our framework relies on dedicated factor models and simultaneously determines the number of factors, the allocation of each measurement to a unique factor, and the corresponding factor loadings. Classical identifi cation criteria are applied and integrated into our Bayesian procedure to generate models that are stable and clearly interpretable. A Monte Carlo study c...
Bayesian Exploratory Factor Analysis
Conti, Gabriella; Frühwirth-Schnatter, Sylvia; Heckman, James J.; Piatek, Rémi
2014-01-01
This paper develops and applies a Bayesian approach to Exploratory Factor Analysis that improves on ad hoc classical approaches. Our framework relies on dedicated factor models and simultaneously determines the number of factors, the allocation of each measurement to a unique factor, and the corresponding factor loadings. Classical identification criteria are applied and integrated into our Bayesian procedure to generate models that are stable and clearly interpretable. A Monte Carlo study co...
Bayesian Exploratory Factor Analysis
Gabriella Conti; Sylvia Fruehwirth-Schnatter; Heckman, James J.; Remi Piatek
2014-01-01
This paper develops and applies a Bayesian approach to Exploratory Factor Analysis that improves on \\emph{ad hoc} classical approaches. Our framework relies on dedicated factor models and simultaneously determines the number of factors, the allocation of each measurement to a unique factor, and the corresponding factor loadings. Classical identification criteria are applied and integrated into our Bayesian procedure to generate models that are stable and clearly interpretable. A Monte Carlo s...
Bayesian exploratory factor analysis
Conti, Gabriella; Frühwirth-Schnatter, Sylvia; Heckman, James J.; Piatek, Rémi
2014-01-01
This paper develops and applies a Bayesian approach to Exploratory Factor Analysis that improves on ad hoc classical approaches. Our framework relies on dedicated factor models and simultaneously determines the number of factors, the allocation of each measurement to a unique factor, and the corresponding factor loadings. Classical identification criteria are applied and integrated into our Bayesian procedure to generate models that are stable and clearly interpretable. A Monte Carlo st...
Bayesian exploratory factor analysis
Conti, Gabriella; Frühwirth-Schnatter, Sylvia; Heckman, James; Piatek, Rémi
2014-01-01
This paper develops and applies a Bayesian approach to Exploratory Factor Analysis that improves on ad hoc classical approaches. Our framework relies on dedicated factor models and simultaneously determines the number of factors, the allocation of each measurement to a unique factor, and the corresponding factor loadings. Classical identification criteria are applied and integrated into our Bayesian procedure to generate models that are stable and clearly interpretable. A Monte Carlo study co...
Carbonetto, Peter; Kisynski, Jacek; De Freitas, Nando; Poole, David L
2012-01-01
The Bayesian Logic (BLOG) language was recently developed for defining first-order probability models over worlds with unknown numbers of objects. It handles important problems in AI, including data association and population estimation. This paper extends BLOG by adopting generative processes over function spaces - known as nonparametrics in the Bayesian literature. We introduce syntax for reasoning about arbitrary collections of objects, and their properties, in an intuitive manner. By expl...
Bayesian default probability models
Andrlíková, Petra
2014-01-01
This paper proposes a methodology for default probability estimation for low default portfolios, where the statistical inference may become troublesome. The author suggests using logistic regression models with the Bayesian estimation of parameters. The piecewise logistic regression model and Box-Cox transformation of credit risk score is used to derive the estimates of probability of default, which extends the work by Neagu et al. (2009). The paper shows that the Bayesian models are more acc...
[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.
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
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…
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…
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...
Bayesian least squares deconvolution
Asensio Ramos, A.; Petit, P.
2015-11-01
Aims: We develop a fully Bayesian least squares deconvolution (LSD) that can be applied to the reliable detection of magnetic signals in noise-limited stellar spectropolarimetric observations using multiline techniques. Methods: We consider LSD under the Bayesian framework and we introduce a flexible Gaussian process (GP) prior for the LSD profile. This prior allows the result to automatically adapt to the presence of signal. We exploit several linear algebra identities to accelerate the calculations. The final algorithm can deal with thousands of spectral lines in a few seconds. Results: We demonstrate the reliability of the method with synthetic experiments and we apply it to real spectropolarimetric observations of magnetic stars. We are able to recover the magnetic signals using a small number of spectral lines, together with the uncertainty at each velocity bin. This allows the user to consider if the detected signal is reliable. The code to compute the Bayesian LSD profile is freely available.
Bayesian least squares deconvolution
Ramos, A Asensio
2015-01-01
Aims. To develop a fully Bayesian least squares deconvolution (LSD) that can be applied to the reliable detection of magnetic signals in noise-limited stellar spectropolarimetric observations using multiline techniques. Methods. We consider LSD under the Bayesian framework and we introduce a flexible Gaussian Process (GP) prior for the LSD profile. This prior allows the result to automatically adapt to the presence of signal. We exploit several linear algebra identities to accelerate the calculations. The final algorithm can deal with thousands of spectral lines in a few seconds. Results. We demonstrate the reliability of the method with synthetic experiments and we apply it to real spectropolarimetric observations of magnetic stars. We are able to recover the magnetic signals using a small number of spectral lines, together with the uncertainty at each velocity bin. This allows the user to consider if the detected signal is reliable. The code to compute the Bayesian LSD profile is freely available.
Loredo, T J
2004-01-01
I describe a framework for adaptive scientific exploration based on iterating an Observation--Inference--Design cycle that allows adjustment of hypotheses and observing protocols in response to the results of observation on-the-fly, as data are gathered. The framework uses a unified Bayesian methodology for the inference and design stages: Bayesian inference to quantify what we have learned from the available data and predict future data, and Bayesian decision theory to identify which new observations would teach us the most. When the goal of the experiment is simply to make inferences, the framework identifies a computationally efficient iterative ``maximum entropy sampling'' strategy as the optimal strategy in settings where the noise statistics are independent of signal properties. Results of applying the method to two ``toy'' problems with simulated data--measuring the orbit of an extrasolar planet, and locating a hidden one-dimensional object--show the approach can significantly improve observational eff...
Bayesian and frequentist inequality tests
David M. Kaplan; Zhuo, Longhao
2016-01-01
Bayesian and frequentist criteria are fundamentally different, but often posterior and sampling distributions are asymptotically equivalent (and normal). We compare Bayesian and frequentist hypothesis tests of inequality restrictions in such cases. For finite-dimensional parameters, if the null hypothesis is that the parameter vector lies in a certain half-space, then the Bayesian test has (frequentist) size $\\alpha$; if the null hypothesis is any other convex subspace, then the Bayesian test...
Bayesian multiple target tracking
Streit, Roy L
2013-01-01
This second edition has undergone substantial revision from the 1999 first edition, recognizing that a lot has changed in the multiple target tracking field. One of the most dramatic changes is in the widespread use of particle filters to implement nonlinear, non-Gaussian Bayesian trackers. This book views multiple target tracking as a Bayesian inference problem. Within this framework it develops the theory of single target tracking, multiple target tracking, and likelihood ratio detection and tracking. In addition to providing a detailed description of a basic particle filter that implements
Bayesian Exploratory Factor Analysis
Conti, Gabriella; Frühwirth-Schnatter, Sylvia; Heckman, James J.;
2014-01-01
This paper develops and applies a Bayesian approach to Exploratory Factor Analysis that improves on ad hoc classical approaches. Our framework relies on dedicated factor models and simultaneously determines the number of factors, the allocation of each measurement to a unique factor, and the...... corresponding factor loadings. Classical identification criteria are applied and integrated into our Bayesian procedure to generate models that are stable and clearly interpretable. A Monte Carlo study confirms the validity of the approach. The method is used to produce interpretable low dimensional aggregates...
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
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.
Bayesian Geostatistical Design
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...
Krejsa, Jiří; Věchet, S.
Bratislava: Slovak University of Technology in Bratislava, 2010, s. 217-222. ISBN 978-80-227-3353-3. [Robotics in Education . Bratislava (SK), 16.09.2010-17.09.2010] Institutional research plan: CEZ:AV0Z20760514 Keywords : mobile robot localization * bearing only beacons * Bayesian filters Subject RIV: JD - Computer Applications, Robotics
Antoniou, Constantinos; Harrison, Glenn W.; Lau, Morten I.;
2015-01-01
A large literature suggests that many individuals do not apply Bayes’ Rule when making decisions that depend on them correctly pooling prior information and sample data. We replicate and extend a classic experimental study of Bayesian updating from psychology, employing the methods of experimenta...
Bayesian Independent Component Analysis
Winther, Ole; Petersen, Kaare Brandt
2007-01-01
In this paper we present an empirical Bayesian framework for independent component analysis. The framework provides estimates of the sources, the mixing matrix and the noise parameters, and is flexible with respect to choice of source prior and the number of sources and sensors. Inside the engine...
Noncausal Bayesian Vector Autoregression
Lanne, Markku; Luoto, Jani
We propose a Bayesian inferential procedure for the noncausal vector autoregressive (VAR) model that is capable of capturing nonlinearities and incorporating effects of missing variables. In particular, we devise a fast and reliable posterior simulator that yields the predictive distribution as a...
Loredo, Thomas J.
2004-04-01
I describe a framework for adaptive scientific exploration based on iterating an Observation-Inference-Design cycle that allows adjustment of hypotheses and observing protocols in response to the results of observation on-the-fly, as data are gathered. The framework uses a unified Bayesian methodology for the inference and design stages: Bayesian inference to quantify what we have learned from the available data and predict future data, and Bayesian decision theory to identify which new observations would teach us the most. When the goal of the experiment is simply to make inferences, the framework identifies a computationally efficient iterative ``maximum entropy sampling'' strategy as the optimal strategy in settings where the noise statistics are independent of signal properties. Results of applying the method to two ``toy'' problems with simulated data-measuring the orbit of an extrasolar planet, and locating a hidden one-dimensional object-show the approach can significantly improve observational efficiency in settings that have well-defined nonlinear models. I conclude with a list of open issues that must be addressed to make Bayesian adaptive exploration a practical and reliable tool for optimizing scientific exploration.
Bayesian logistic regression analysis
Van Erp, H.R.N.; Van Gelder, P.H.A.J.M.
2012-01-01
In this paper we present a Bayesian logistic regression analysis. It is found that if one wishes to derive the posterior distribution of the probability of some event, then, together with the traditional Bayes Theorem and the integrating out of nuissance parameters, the Jacobian transformation is an
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
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.
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
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...
Li, Geng
Gnomon shadow measurement was one of the most fundamental astronomical observations in ancient China. It was crucial for calendar making, which constituted an important aspect of imperial governance. A painted stick discovered from a prehistoric (2300 BC) astronomical site of Taosi (see Chap. 201, "Taosi Observatory", 10.1007/978-1-4614-6141-8_215") is the oldest gnomon known of China. From second century BC onward, gnomon shadow measurements have been essential part of calendrical practice. Various historical measurements are discussed in this chapter.
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
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...
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...
Campbell, Murray
2002-11-01
There is considerable evidence from iconographic and documentary sources that musical lip-reed instruments were important in the early celtic communities of Scotland and Ireland. In recent years several studies have been undertaken with the aim of gaining a better understanding of the musical nature of these ancient horns, and of their place in the life and culture of the time. A valuable source of tangible evidence is to be found in the archaeological remains deposited across Scotland and the whole of Ireland. A project is now under way, under the auspices of the Kilmartin House Trust and the general direction of John Purser, which has brought together an international team of musicians, craftsmen, archaeologists, musicologists and physicists with the aim of analyzing ancient musical artifacts, reconstructing some of the original instruments, and analyzing the sounds they produce. This paper describes acoustical studies carried out on a number of recent reconstructions of wooden and bronze instruments, and discusses the role of acoustics in this type of investigation. [Work supported by Sciart and EPSRC.
Bayesian Nonparametric Graph Clustering
Banerjee, Sayantan; Akbani, Rehan; Baladandayuthapani, Veerabhadran
2015-01-01
We present clustering methods for multivariate data exploiting the underlying geometry of the graphical structure between variables. As opposed to standard approaches that assume known graph structures, we first estimate the edge structure of the unknown graph using Bayesian neighborhood selection approaches, wherein we account for the uncertainty of graphical structure learning through model-averaged estimates of the suitable parameters. Subsequently, we develop a nonparametric graph cluster...
Approximate Bayesian recursive estimation
Kárný, Miroslav
2014-01-01
Roč. 285, č. 1 (2014), s. 100-111. ISSN 0020-0255 R&D Projects: GA ČR GA13-13502S Institutional support: RVO:67985556 Keywords : Approximate parameter estimation * Bayesian recursive estimation * Kullback–Leibler divergence * Forgetting Subject RIV: BB - Applied Statistics, Operational Research Impact factor: 4.038, year: 2014 http://library.utia.cas.cz/separaty/2014/AS/karny-0425539.pdf
Bayesian Benchmark Dose Analysis
Fang, Qijun; Piegorsch, Walter W.; Barnes, Katherine Y.
2014-01-01
An important objective in environmental risk assessment is estimation of minimum exposure levels, called Benchmark Doses (BMDs) that induce a pre-specified Benchmark Response (BMR) in a target population. Established inferential approaches for BMD analysis typically involve one-sided, frequentist confidence limits, leading in practice to what are called Benchmark Dose Lower Limits (BMDLs). Appeal to Bayesian modeling and credible limits for building BMDLs is far less developed, however. Indee...
Bayesian Generalized Rating Curves
Helgi Sigurðarson 1985
2014-01-01
A rating curve is a curve or a model that describes the relationship between water elevation, or stage, and discharge in an observation site in a river. The rating curve is fit from paired observations of stage and discharge. The rating curve then predicts discharge given observations of stage and this methodology is applied as stage is substantially easier to directly observe than discharge. In this thesis a statistical rating curve model is proposed working within the framework of Bayesian...
Heteroscedastic Treed Bayesian Optimisation
Assael, John-Alexander M.; Wang, Ziyu; Shahriari, Bobak; De Freitas, Nando
2014-01-01
Optimising black-box functions is important in many disciplines, such as tuning machine learning models, robotics, finance and mining exploration. Bayesian optimisation is a state-of-the-art technique for the global optimisation of black-box functions which are expensive to evaluate. At the core of this approach is a Gaussian process prior that captures our belief about the distribution over functions. However, in many cases a single Gaussian process is not flexible enough to capture non-stat...
Efficient Bayesian Phase Estimation
Wiebe, Nathan; Granade, Chris
2016-07-01
We introduce a new method called rejection filtering that we use to perform adaptive Bayesian phase estimation. Our approach has several advantages: it is classically efficient, easy to implement, achieves Heisenberg limited scaling, resists depolarizing noise, tracks time-dependent eigenstates, recovers from failures, and can be run on a field programmable gate array. It also outperforms existing iterative phase estimation algorithms such as Kitaev's method.
Brody, Samuel; Lapata, Mirella
2009-01-01
Sense induction seeks to automatically identify word senses directly from a corpus. A key assumption underlying previous work is that the context surrounding an ambiguous word is indicative of its meaning. Sense induction is thus typically viewed as an unsupervised clustering problem where the aim is to partition a word’s contexts into different classes, each representing a word sense. Our work places sense induction in a Bayesian context by modeling the contexts of the ambiguous word as samp...
Bayesian Neural Word Embedding
Barkan, Oren
2016-01-01
Recently, several works in the domain of natural language processing presented successful methods for word embedding. Among them, the Skip-gram (SG) with negative sampling, known also as Word2Vec, advanced the state-of-the-art of various linguistics tasks. In this paper, we propose a scalable Bayesian neural word embedding algorithm that can be beneficial to general item similarity tasks as well. The algorithm relies on a Variational Bayes solution for the SG objective and a detailed step by ...
Wiegerinck, Wim; Schoenaker, Christiaan; Duane, Gregory
2016-04-01
Recently, methods for model fusion by dynamically combining model components in an interactive ensemble have been proposed. In these proposals, fusion parameters have to be learned from data. One can view these systems as parametrized dynamical systems. We address the question of learnability of dynamical systems with respect to both short term (vector field) and long term (attractor) behavior. In particular we are interested in learning in the imperfect model class setting, in which the ground truth has a higher complexity than the models, e.g. due to unresolved scales. We take a Bayesian point of view and we define a joint log-likelihood that consists of two terms, one is the vector field error and the other is the attractor error, for which we take the L1 distance between the stationary distributions of the model and the assumed ground truth. In the context of linear models (like so-called weighted supermodels), and assuming a Gaussian error model in the vector fields, vector field learning leads to a tractable Gaussian solution. This solution can then be used as a prior for the next step, Bayesian attractor learning, in which the attractor error is used as a log-likelihood term. Bayesian attractor learning is implemented by elliptical slice sampling, a sampling method for systems with a Gaussian prior and a non Gaussian likelihood. Simulations with a partially observed driven Lorenz 63 system illustrate the approach.
Bayesian theory and applications
Dellaportas, Petros; Polson, Nicholas G; Stephens, David A
2013-01-01
The development of hierarchical models and Markov chain Monte Carlo (MCMC) techniques forms one of the most profound advances in Bayesian analysis since the 1970s and provides the basis for advances in virtually all areas of applied and theoretical Bayesian statistics. This volume guides the reader along a statistical journey that begins with the basic structure of Bayesian theory, and then provides details on most of the past and present advances in this field. The book has a unique format. There is an explanatory chapter devoted to each conceptual advance followed by journal-style chapters that provide applications or further advances on the concept. Thus, the volume is both a textbook and a compendium of papers covering a vast range of topics. It is appropriate for a well-informed novice interested in understanding the basic approach, methods and recent applications. Because of its advanced chapters and recent work, it is also appropriate for a more mature reader interested in recent applications and devel...
Authenticity in ancient DNA studies
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 ...
Unbounded Bayesian Optimization via Regularization
Shahriari, Bobak; Bouchard-Côté, Alexandre; De Freitas, Nando
2015-01-01
Bayesian optimization has recently emerged as a popular and efficient tool for global optimization and hyperparameter tuning. Currently, the established Bayesian optimization practice requires a user-defined bounding box which is assumed to contain the optimizer. However, when little is known about the probed objective function, it can be difficult to prescribe such bounds. In this work we modify the standard Bayesian optimization framework in a principled way to allow automatic resizing of t...
Bayesian optimization for materials design
Frazier, Peter I.; Wang, Jialei
2015-01-01
We introduce Bayesian optimization, a technique developed for optimizing time-consuming engineering simulations and for fitting machine learning models on large datasets. Bayesian optimization guides the choice of experiments during materials design and discovery to find good material designs in as few experiments as possible. We focus on the case when materials designs are parameterized by a low-dimensional vector. Bayesian optimization is built on a statistical technique called Gaussian pro...
Tamil merchant in ancient Mesopotamia.
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
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.
Characterization of Ancient Tripitaka
Gong, Y. X.; Geng, L.; Gong, D. C.
2015-08-01
Tripitaka is the world's most comprehensive version of Buddhist sutra. There are limited numbers of Tripitaka currently preserved, most of them present various patterns of degradation. As little is known about the materials and crafts used in Tripitaka, it appeared necessary to identify them, and to further define adapted conservation treatment. In this work, a study concerning the paper source and dyestuff of the Tripitaka from approximate 16th century was carried out using fiber analysis and thin-layer chromatography (TLC). The results proved that the papers were mainly made from hemp or bark of mulberry tree, and indigo was used for colorizing the paper. At the end, we provide with suggestions for protecting and restoring the ancient Tripitaka.
Bayesian nonparametric data analysis
Müller, Peter; Jara, Alejandro; Hanson, Tim
2015-01-01
This book reviews nonparametric Bayesian methods and models that have proven useful in the context of data analysis. Rather than providing an encyclopedic review of probability models, the book’s structure follows a data analysis perspective. As such, the chapters are organized by traditional data analysis problems. In selecting specific nonparametric models, simpler and more traditional models are favored over specialized ones. The discussed methods are illustrated with a wealth of examples, including applications ranging from stylized examples to case studies from recent literature. The book also includes an extensive discussion of computational methods and details on their implementation. R code for many examples is included in on-line software pages.
Decentralized Distributed Bayesian Estimation
Dedecius, Kamil; Sečkárová, Vladimíra
Praha: ÚTIA AVČR, v.v.i, 2011 - (Janžura, M.; Ivánek, J.). s. 16-16 [7th International Workshop on Data–Algorithms–Decision Making. 27.11.2011-29.11.2011, Mariánská] R&D Projects: GA ČR 102/08/0567; GA ČR GA102/08/0567 Institutional research plan: CEZ:AV0Z10750506 Keywords : estimation * distributed estimation * model Subject RIV: BB - Applied Statistics, Operational Research http://library.utia.cas.cz/separaty/2011/AS/dedecius-decentralized distributed bayesian estimation.pdf
Congdon, Peter
2014-01-01
This book provides an accessible approach to Bayesian computing and data analysis, with an emphasis on the interpretation of real data sets. Following in the tradition of the successful first edition, this book aims to make a wide range of statistical modeling applications accessible using tested code that can be readily adapted to the reader's own applications. The second edition has been thoroughly reworked and updated to take account of advances in the field. A new set of worked examples is included. The novel aspect of the first edition was the coverage of statistical modeling using WinBU
Computationally efficient Bayesian tracking
Aughenbaugh, Jason; La Cour, Brian
2012-06-01
In this paper, we describe the progress we have achieved in developing a computationally efficient, grid-based Bayesian fusion tracking system. In our approach, the probability surface is represented by a collection of multidimensional polynomials, each computed adaptively on a grid of cells representing state space. Time evolution is performed using a hybrid particle/grid approach and knowledge of the grid structure, while sensor updates use a measurement-based sampling method with a Delaunay triangulation. We present an application of this system to the problem of tracking a submarine target using a field of active and passive sonar buoys.
Improved iterative Bayesian unfolding
D'Agostini, G
2010-01-01
This paper reviews the basic ideas behind a Bayesian unfolding published some years ago and improves their implementation. In particular, uncertainties are now treated at all levels by probability density functions and their propagation is performed by Monte Carlo integration. Thus, small numbers are better handled and the final uncertainty does not rely on the assumption of normality. Theoretical and practical issues concerning the iterative use of the algorithm are also discussed. The new program, implemented in the R language, is freely available, together with sample scripts to play with toy models.
Astronomy in the Ancient Caucasus
Simonia, Irakli; Jijelava, Badri
This chapter discusses the role of recurrent heavenly phenomena in the formation of ancient cultural traditions. Artifacts bearing witness to astronomical and calendrical practices in the ancient Caucasus are described and we analyze the significance of the "boats of the sun" petroglyphs at Gobustan in Azerbaijan, the solar station at Abuli in Georgia, and the "sky dial" at Carahunge in Armenia. Similarities and differences between the ancient cultures of the region are discussed. Finally, we present the results of the latest field research and new facts and hypotheses.
The Ancient Egyptian Demonology Project
Weber, Felicitas
2016-01-01
“The Ancient Egyptian Demonology Project: Second Millennium BCE” was intended and funded as a three-year project (2013-2016) to explore the world of Ancient Egyptian demons in the 2nd millennium BC. It intends to create a classification and ontology of benevolent and malevolent demons. Whereas ancient Egyptians did not use a specific term denoting “demons”, liminal beings known from various other cultures such as δαίμονες, ghosts, angels, Mischwesen, genies, etc., were nevertheless described ...
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...
Bayesian Inference on Gravitational Waves
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.
[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
Adaptive Dynamic Bayesian Networks
Ng, B M
2007-10-26
A discrete-time Markov process can be compactly modeled as a dynamic Bayesian network (DBN)--a graphical model with nodes representing random variables and directed edges indicating causality between variables. Each node has a probability distribution, conditional on the variables represented by the parent nodes. A DBN's graphical structure encodes fixed conditional dependencies between variables. But in real-world systems, conditional dependencies between variables may be unknown a priori or may vary over time. Model errors can result if the DBN fails to capture all possible interactions between variables. Thus, we explore the representational framework of adaptive DBNs, whose structure and parameters can change from one time step to the next: a distribution's parameters and its set of conditional variables are dynamic. This work builds on recent work in nonparametric Bayesian modeling, such as hierarchical Dirichlet processes, infinite-state hidden Markov networks and structured priors for Bayes net learning. In this paper, we will explain the motivation for our interest in adaptive DBNs, show how popular nonparametric methods are combined to formulate the foundations for adaptive DBNs, and present preliminary results.
Bayesian analysis toolkit - BAT
Statistical treatment of data is an essential part of any data analysis and interpretation. Different statistical methods and approaches can be used, however the implementation of these approaches is complicated and at times inefficient. The Bayesian analysis toolkit (BAT) is a software package developed in C++ framework that facilitates the statistical analysis of the data using Bayesian theorem. The tool evaluates the posterior probability distributions for models and their parameters using Markov Chain Monte Carlo which in turn provide straightforward parameter estimation, limit setting and uncertainty propagation. Additional algorithms, such as simulated annealing, allow extraction of the global mode of the posterior. BAT sets a well-tested environment for flexible model definition and also includes a set of predefined models for standard statistical problems. The package is interfaced to other software packages commonly used in high energy physics, such as ROOT, Minuit, RooStats and CUBA. We present a general overview of BAT and its algorithms. A few physics examples are shown to introduce the spectrum of its applications. In addition, new developments and features are summarized.
Ancient and Current Chaos Theories
Güngör Gündüz
2006-07-01
Full Text Available Chaos theories developed in the last three decades have made very important contributions to our understanding of dynamical systems and natural phenomena. The meaning of chaos in the current theories and in the past is somewhat different from each other. In this work, the properties of dynamical systems and the evolution of chaotic systems were discussed in terms of the views of ancient philosophers. The meaning of chaos in Anaximenes’ philosophy and its role in the Ancient natural philosophy has been discussed in relation to other natural philosophers such as of Anaximander, Parmenides, Heraclitus, Empedocles, Leucippus (i.e. atomists and Aristotle. In addition, the fundamental concepts of statistical mechanics and the current chaos theories were discussed in relation to the views in Ancient natural philosophy. The roots of the scientific concepts such as randomness, autocatalysis, nonlinear growth, information, pattern, etc. in the Ancient natural philosophy were investigated.
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.
Reconstructing ancient genomes and epigenomes
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...
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)
Hartelius, Karsten; Carstensen, Jens Michael
2003-01-01
A method for locating distorted grid structures in images is presented. The method is based on the theories of template matching and Bayesian image restoration. The grid is modeled as a deformable template. Prior knowledge of the grid is described through a Markov random field (MRF) model which...... represents the spatial coordinates of the grid nodes. Knowledge of how grid nodes are depicted in the observed image is described through the observation model. The prior consists of a node prior and an arc (edge) prior, both modeled as Gaussian MRFs. The node prior models variations in the positions of grid...... nodes and the arc prior models variations in row and column spacing across the grid. Grid matching is done by placing an initial rough grid over the image and applying an ensemble annealing scheme to maximize the posterior distribution of the grid. The method can be applied to noisy images with missing...
Did the ancient Egyptians migrate to ancient Nigeria?
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.
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
Bayesian Methods and Universal Darwinism
Campbell, John
2010-01-01
Bayesian methods since the time of Laplace have been understood by their practitioners as closely aligned to the scientific method. Indeed a recent champion of Bayesian methods, E. T. Jaynes, titled his textbook on the subject Probability Theory: the Logic of Science. Many philosophers of science including Karl Popper and Donald Campbell have interpreted the evolution of Science as a Darwinian process consisting of a 'copy with selective retention' algorithm abstracted from Darwin's theory of...
Portfolio Allocation for Bayesian Optimization
Brochu, Eric; Hoffman, Matthew W.; De Freitas, Nando
2010-01-01
Bayesian optimization with Gaussian processes has become an increasingly popular tool in the machine learning community. It is efficient and can be used when very little is known about the objective function, making it popular in expensive black-box optimization scenarios. It uses Bayesian methods to sample the objective efficiently using an acquisition function which incorporates the model's estimate of the objective and the uncertainty at any given point. However, there are several differen...
Neuronanatomy, neurology and Bayesian networks
Bielza Lozoya, Maria Concepcion
2014-01-01
Bayesian networks are data mining models with clear semantics and a sound theoretical foundation. In this keynote talk we will pinpoint a number of neuroscience problems that can be addressed using Bayesian networks. In neuroanatomy, we will show computer simulation models of dendritic trees and classification of neuron types, both based on morphological features. In neurology, we will present the search for genetic biomarkers in Alzheimer's disease and the prediction of health-related qualit...
Bayesian Networks and Influence Diagrams
Kjærulff, Uffe Bro; Madsen, Anders Læsø
Probabilistic networks, also known as Bayesian networks and influence diagrams, have become one of the most promising technologies in the area of applied artificial intelligence, offering intuitive, efficient, and reliable methods for diagnosis, prediction, decision making, classification......, troubleshooting, and data mining under uncertainty. Bayesian Networks and Influence Diagrams: A Guide to Construction and Analysis provides a comprehensive guide for practitioners who wish to understand, construct, and analyze intelligent systems for decision support based on probabilistic networks. Intended...
Ancient DNA in Greece. Problems and prospects
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)
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.
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 ...... conservation of forests under existing decentralized management arrangements toward a push for extending the coverage of forests under decentralized management, making forest rights the hard currency of REDD+....
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
Night blindness and ancient remedy
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.
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
Nonparametric Bayesian Classification
Coram, M A
2002-01-01
A Bayesian approach to the classification problem is proposed in which random partitions play a central role. It is argued that the partitioning approach has the capacity to take advantage of a variety of large-scale spatial structures, if they are present in the unknown regression function $f_0$. An idealized one-dimensional problem is considered in detail. The proposed nonparametric prior uses random split points to partition the unit interval into a random number of pieces. This prior is found to provide a consistent estimate of the regression function in the $\\L^p$ topology, for any $1 \\leq p < \\infty$, and for arbitrary measurable $f_0:[0,1] \\rightarrow [0,1]$. A Markov chain Monte Carlo (MCMC) implementation is outlined and analyzed. Simulation experiments are conducted to show that the proposed estimate compares favorably with a variety of conventional estimators. A striking resemblance between the posterior mean estimate and the bagged CART estimate is noted and discussed. For higher dimensions, a ...
BAT - Bayesian Analysis Toolkit
One of the most vital steps in any data analysis is the statistical analysis and comparison with the prediction of a theoretical model. The many uncertainties associated with the theoretical model and the observed data require a robust statistical analysis tool. The Bayesian Analysis Toolkit (BAT) is a powerful statistical analysis software package based on Bayes' Theorem, developed to evaluate the posterior probability distribution for models and their parameters. It implements Markov Chain Monte Carlo to get the full posterior probability distribution that in turn provides a straightforward parameter estimation, limit setting and uncertainty propagation. Additional algorithms, such as Simulated Annealing, allow to evaluate the global mode of the posterior. BAT is developed in C++ and allows for a flexible definition of models. A set of predefined models covering standard statistical cases are also included in BAT. It has been interfaced to other commonly used software packages such as ROOT, Minuit, RooStats and CUBA. An overview of the software and its algorithms is provided along with several physics examples to cover a range of applications of this statistical tool. Future plans, new features and recent developments are briefly discussed.
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 ...
Acupuncture: From Ancient Practice to Modern Science
... Section CAM Acupuncture From Ancient Practice to Modern Science Past Issues / Winter 2009 Table of Contents For ... of Progress / Acupuncture From Ancient Practice to Modern Science / Low Back Pain and CAM / Time to Talk / ...
The eye and its diseases in Ancient Egypt
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 crimes as a threat to sustainable forest management
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
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
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
Discovering the Ancient Temperate Rainforest.
Lindsay, Anne
1997-01-01
Two activities for grades 3 through 8 explore species adaptation and forestry issues in the North American rainforests. In one activity, students create imaginary species of plants or animals that are adapted for life in an ancient temperate rainforest. In the second activity, students role play groups affected by plans to log an area of the…
Bayesian seismic AVO inversion
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
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 ...
Probability biases as Bayesian inference
Andre; C. R. Martins
2006-11-01
Full Text Available In this article, I will show how several observed biases in human probabilistic reasoning can be partially explained as good heuristics for making inferences in an environment where probabilities have uncertainties associated to them. Previous results show that the weight functions and the observed violations of coalescing and stochastic dominance can be understood from a Bayesian point of view. We will review those results and see that Bayesian methods should also be used as part of the explanation behind other known biases. That means that, although the observed errors are still errors under the be understood as adaptations to the solution of real life problems. Heuristics that allow fast evaluations and mimic a Bayesian inference would be an evolutionary advantage, since they would give us an efficient way of making decisions. %XX In that sense, it should be no surprise that humans reason with % probability as it has been observed.
Bayesian Methods and Universal Darwinism
Campbell, John
2010-01-01
Bayesian methods since the time of Laplace have been understood by their practitioners as closely aligned to the scientific method. Indeed a recent champion of Bayesian methods, E. T. Jaynes, titled his textbook on the subject Probability Theory: the Logic of Science. Many philosophers of science including Karl Popper and Donald Campbell have interpreted the evolution of Science as a Darwinian process consisting of a 'copy with selective retention' algorithm abstracted from Darwin's theory of Natural Selection. Arguments are presented for an isomorphism between Bayesian Methods and Darwinian processes. Universal Darwinism, as the term has been developed by Richard Dawkins, Daniel Dennett and Susan Blackmore, is the collection of scientific theories which explain the creation and evolution of their subject matter as due to the operation of Darwinian processes. These subject matters span the fields of atomic physics, chemistry, biology and the social sciences. The principle of Maximum Entropy states that system...
Bayesian methods for proteomic biomarker development
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.
New approach using Bayesian Network to improve content based image classification systems
jayech, Khlifia
2012-01-01
This paper proposes a new approach based on augmented naive Bayes for image classification. Initially, each image is cutting in a whole of blocks. For each block, we compute a vector of descriptors. Then, we propose to carry out a classification of the vectors of descriptors to build a vector of labels for each image. Finally, we propose three variants of Bayesian Networks such as Naive Bayesian Network (NB), Tree Augmented Naive Bayes (TAN) and Forest Augmented Naive Bayes (FAN) to classify the image using the vector of labels. The results showed a marked improvement over the FAN, NB and TAN.
Bayesian test and Kuhn's paradigm
Chen Xiaoping
2006-01-01
Kuhn's theory of paradigm reveals a pattern of scientific progress,in which normal science alternates with scientific revolution.But Kuhn underrated too much the function of scientific test in his pattern,because he focuses all his attention on the hypothetico-deductive schema instead of Bayesian schema.This paper employs Bayesian schema to re-examine Kuhn's theory of paradigm,to uncover its logical and rational components,and to illustrate the tensional structure of logic and belief,rationality and irrationality,in the process of scientific revolution.
3D Bayesian contextual classifiers
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 Model Averaging for Propensity Score Analysis
Kaplan, David; Chen, Jianshen
2013-01-01
The purpose of this study is to explore Bayesian model averaging in the propensity score context. Previous research on Bayesian propensity score analysis does not take into account model uncertainty. In this regard, an internally consistent Bayesian framework for model building and estimation must also account for model uncertainty. The…
Bayesian networks and food security - An introduction
Stein, A.
2004-01-01
This paper gives an introduction to Bayesian networks. Networks are defined and put into a Bayesian context. Directed acyclical graphs play a crucial role here. Two simple examples from food security are addressed. Possible uses of Bayesian networks for implementation and further use in decision sup
Bayesian variable order Markov models: Towards Bayesian predictive state representations
C. Dimitrakakis
2009-01-01
We present a Bayesian variable order Markov model that shares many similarities with predictive state representations. The resulting models are compact and much easier to specify and learn than classical predictive state representations. Moreover, we show that they significantly outperform a more st
Ancient DNA from marine mammals
Foote, Andrew David; Hofreiter, Michael; Morin, Philip A
2012-01-01
such as bone, tooth, baleen, skin, fur, whiskers and scrimshaw using ancient DNA (aDNA) approaches provide an oppor- tunity for investigating such changes over evolutionary and ecological timescales. Here, we review the application of aDNA techniques to the study of marine mammals. Most of the studies have...... focused on detecting changes in genetic diversity following periods of exploitation and environmental change. To date, these studies have shown that even small sample sizes can provide useful information on historical genetic diversity. Ancient DNA has also been used in investigations of changes...... in distribution and range of marine mammal species; we review these studies and discuss the limitations of such ‘presence only’ studies. Combining aDNA data with stable isotopes can provide further insights into changes in ecology and we review past studies and suggest future potential applications. We also...
Psychiatric Thoughts in Ancient India
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.
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...
Bayesian Analysis of Experimental Data
Lalmohan Bhar
2013-10-01
Full Text Available Analysis of experimental data from Bayesian point of view has been considered. Appropriate methodology has been developed for application into designed experiments. Normal-Gamma distribution has been considered for prior distribution. Developed methodology has been applied to real experimental data taken from long term fertilizer experiments.
Bayesian image restoration, using configurations
Thorarinsdottir, Thordis Linda
2006-01-01
configurations are expressed in terms of the mean normal measure of the random set. These probabilities are used as prior probabilities in a Bayesian image restoration approach. Estimation of the remaining parameters in the model is outlined for the salt and pepper noise. The inference in the model is discussed...
Bayesian image restoration, using configurations
Thorarinsdottir, Thordis
configurations are expressed in terms of the mean normal measure of the random set. These probabilities are used as prior probabilities in a Bayesian image restoration approach. Estimation of the remaining parameters in the model is outlined for salt and pepper noise. The inference in the model is discussed in...
ANALYSIS OF BAYESIAN CLASSIFIER ACCURACY
Felipe Schneider Costa
2013-01-01
Full Text Available The naÃ¯ve Bayes classifier is considered one of the most effective classification algorithms today, competing with more modern and sophisticated classifiers. Despite being based on unrealistic (naÃ¯ve assumption that all variables are independent, given the output class, the classifier provides proper results. However, depending on the scenario utilized (network structure, number of samples or training cases, number of variables, the network may not provide appropriate results. This study uses a process variable selection, using the chi-squared test to verify the existence of dependence between variables in the data model in order to identify the reasons which prevent a Bayesian network to provide good performance. A detailed analysis of the data is also proposed, unlike other existing work, as well as adjustments in case of limit values between two adjacent classes. Furthermore, variable weights are used in the calculation of a posteriori probabilities, calculated with mutual information function. Tests were applied in both a naÃ¯ve Bayesian network and a hierarchical Bayesian network. After testing, a significant reduction in error rate has been observed. The naÃ¯ve Bayesian network presented a drop in error rates from twenty five percent to five percent, considering the initial results of the classification process. In the hierarchical network, there was not only a drop in fifteen percent error rate, but also the final result came to zero.
Bayesian Agglomerative Clustering with Coalescents
Teh, Yee Whye; Daumé III, Hal; Roy, Daniel
2009-01-01
We introduce a new Bayesian model for hierarchical clustering based on a prior over trees called Kingman's coalescent. We develop novel greedy and sequential Monte Carlo inferences which operate in a bottom-up agglomerative fashion. We show experimentally the superiority of our algorithms over others, and demonstrate our approach in document clustering and phylolinguistics.
Bayesian Networks and Influence Diagrams
Kjærulff, Uffe Bro; Madsen, Anders Læsø
Bayesian Networks and Influence Diagrams: A Guide to Construction and Analysis, Second Edition, provides a comprehensive guide for practitioners who wish to understand, construct, and analyze intelligent systems for decision support based on probabilistic networks. This new edition contains six new...
Topics in Bayesian statistics and maximum entropy
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)
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. ...
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.
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
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
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...
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
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
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.
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
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.
Álvarez-Presas, M; Sánchez-Gracia, A; Carbayo, F; Rozas, J; Riutort, M
2014-01-01
The relative importance of the processes that generate and maintain biodiversity is a major and controversial topic in evolutionary biology with large implications for conservation management. The Atlantic Forest of Brazil, one of the world's richest biodiversity hot spots, is severely damaged by human activities. To formulate an efficient conservation policy, a good understanding of spatial and temporal biodiversity patterns and their underlying evolutionary mechanisms is required. With this aim, we performed a comprehensive phylogeographic study using a low-dispersal organism, the land planarian species Cephaloflexa bergi (Platyhelminthes, Tricladida). Analysing multi-locus DNA sequence variation under the Approximate Bayesian Computation framework, we evaluated two scenarios proposed to explain the diversity of Southern Atlantic Forest (SAF) region. We found that most sampled localities harbour high levels of genetic diversity, with lineages sharing common ancestors that predate the Pleistocene. Remarkably, we detected the molecular hallmark of the isolation-by-distance effect and little evidence of a recent colonization of SAF localities; nevertheless, some populations might result from very recent secondary contacts. We conclude that extant SAF biodiversity originated and has been shaped by complex interactions between ancient geological events and more recent evolutionary processes, whereas Pleistocene climate changes had a minor influence in generating present-day diversity. We also demonstrate that land planarians are an advantageous biological model for making phylogeographic and, particularly, fine-scale evolutionary inferences, and propose appropriate conservation policies. PMID:24549112
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...
Public Library Systems in Ancient South India
Raman Nair, R.
1991-01-01
The paper puts forward and substantiates the view that the concept of free public library service goes back to ancient times. Governments of those days were aware of their responsibility to provide to all citizens free information service. The study observes with reference to ancient Indian records that educational facilities and libraries were accessible to people of Ancient India without any discrimination based on economic status, caste, religion or geographical boundaries. Scholars handl...
The Ancient Greece's roots of Olimpism
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.
Aiding the Interpretation of Ancient Documents
Roued-Cunliffe, Henriette
tool it is important first to comprehend the interpretation process involved in reading ancient documents. This is not a linear process but rather a recursive process where the scholar moves between different levels of reading, such as ‘understanding the meaning of a character’ or ‘understanding......How can Decision Support System (DSS) software aid the interpretation process involved in the reading of ancient documents? This paper discusses the development of a DSS prototype for the reading of ancient texts. In this context the term ‘ancient documents’ is used to describe mainly Greek...
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
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...
Chinese Ancient Football with Romanticism
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
breedR: Statistical methods for forest genetic resources analysts
MUNOZ, Facundo
2015-01-01
This package provides frequentist and Bayesian statistical tools to build predictive models useful for the breeders, quantitative genetists and forest genetic resources analysts communities. It aims to assess the genetic value of individuals under a number of situations, including spatial autocorrelation, genetic/environment interaction and competition. It is under active development as part of the Trees4Future project, particularly developed having forest genetic trials in mind. But can be u...
Bayesian approach to rough set
Marwala, Tshilidzi
2007-01-01
This paper proposes an approach to training rough set models using Bayesian framework trained using Markov Chain Monte Carlo (MCMC) method. The prior probabilities are constructed from the prior knowledge that good rough set models have fewer rules. Markov Chain Monte Carlo sampling is conducted through sampling in the rough set granule space and Metropolis algorithm is used as an acceptance criteria. The proposed method is tested to estimate the risk of HIV given demographic data. The results obtained shows that the proposed approach is able to achieve an average accuracy of 58% with the accuracy varying up to 66%. In addition the Bayesian rough set give the probabilities of the estimated HIV status as well as the linguistic rules describing how the demographic parameters drive the risk of HIV.
Attention in a bayesian framework
Whiteley, Louise Emma; Sahani, Maneesh
2012-01-01
include both selective phenomena, where attention is invoked by cues that point to particular stimuli, and integrative phenomena, where attention is invoked dynamically by endogenous processing. However, most previous Bayesian accounts of attention have focused on describing relatively simple experimental...... settings, where cues shape expectations about a small number of upcoming stimuli and thus convey "prior" information about clearly defined objects. While operationally consistent with the experiments it seeks to describe, this view of attention as prior seems to miss many essential elements of both its......The behavioral phenomena of sensory attention are thought to reflect the allocation of a limited processing resource, but there is little consensus on the nature of the resource or why it should be limited. Here we argue that a fundamental bottleneck emerges naturally within Bayesian models of...
Bayesian Sampling using Condition Indicators
Faber, Michael H.; Sørensen, John Dalsgaard
2002-01-01
allows for a Bayesian formulation of the indicators whereby the experience and expertise of the inspection personnel may be fully utilized and consistently updated as frequentistic information is collected. The approach is illustrated on an example considering a concrete structure subject to corrosion......The problem of control quality of components is considered for the special case where the acceptable failure rate is low, the test costs are high and where it may be difficult or impossible to test the condition of interest directly. Based on the classical control theory and the concept of...... condition indicators introduced by Benjamin and Cornell (1970) a Bayesian approach to quality control is formulated. The formulation is then extended to the case where the quality control is based on sampling of indirect information about the condition of the components, i.e. condition indicators. This...
BAYESIAN IMAGE RESTORATION, USING CONFIGURATIONS
Thordis Linda Thorarinsdottir
2011-05-01
Full Text Available In this paper, we develop a Bayesian procedure for removing noise from images that can be viewed as noisy realisations of random sets in the plane. The procedure utilises recent advances in configuration theory for noise free random sets, where the probabilities of observing the different boundary configurations are expressed in terms of the mean normal measure of the random set. These probabilities are used as prior probabilities in a Bayesian image restoration approach. Estimation of the remaining parameters in the model is outlined for salt and pepper noise. The inference in the model is discussed in detail for 3 X 3 and 5 X 5 configurations and examples of the performance of the procedure are given.
Bayesian Seismology of the Sun
Gruberbauer, Michael
2013-01-01
We perform a Bayesian grid-based analysis of the solar l=0,1,2 and 3 p modes obtained via BiSON in order to deliver the first Bayesian asteroseismic analysis of the solar composition problem. We do not find decisive evidence to prefer either of the contending chemical compositions, although the revised solar abundances (AGSS09) are more probable in general. We do find indications for systematic problems in standard stellar evolution models, unrelated to the consequences of inadequate modelling of the outer layers on the higher-order modes. The seismic observables are best fit by solar models that are several hundred million years older than the meteoritic age of the Sun. Similarly, meteoritic age calibrated models do not adequately reproduce the observed seismic observables. Our results suggest that these problems will affect any asteroseismic inference that relies on a calibration to the Sun.
Bayesian priors for transiting planets
Kipping, David M
2016-01-01
As astronomers push towards discovering ever-smaller transiting planets, it is increasingly common to deal with low signal-to-noise ratio (SNR) events, where the choice of priors plays an influential role in Bayesian inference. In the analysis of exoplanet data, the selection of priors is often treated as a nuisance, with observers typically defaulting to uninformative distributions. Such treatments miss a key strength of the Bayesian framework, especially in the low SNR regime, where even weak a priori information is valuable. When estimating the parameters of a low-SNR transit, two key pieces of information are known: (i) the planet has the correct geometric alignment to transit and (ii) the transit event exhibits sufficient signal-to-noise to have been detected. These represent two forms of observational bias. Accordingly, when fitting transits, the model parameter priors should not follow the intrinsic distributions of said terms, but rather those of both the intrinsic distributions and the observational ...
Bayesian Inference for Radio Observations
Lochner, Michelle; Zwart, Jonathan T L; Smirnov, Oleg; Bassett, Bruce A; Oozeer, Nadeem; Kunz, Martin
2015-01-01
(Abridged) New telescopes like the Square Kilometre Array (SKA) will push into a new sensitivity regime and expose systematics, such as direction-dependent effects, that could previously be ignored. Current methods for handling such systematics rely on alternating best estimates of instrumental calibration and models of the underlying sky, which can lead to inaccurate uncertainty estimates and biased results because such methods ignore any correlations between parameters. These deconvolution algorithms produce a single image that is assumed to be a true representation of the sky, when in fact it is just one realisation of an infinite ensemble of images compatible with the noise in the data. In contrast, here we report a Bayesian formalism that simultaneously infers both systematics and science. Our technique, Bayesian Inference for Radio Observations (BIRO), determines all parameters directly from the raw data, bypassing image-making entirely, by sampling from the joint posterior probability distribution. Thi...
Bayesian inference on proportional elections.
Brunello, Gabriel Hideki Vatanabe; Nakano, Eduardo Yoshio
2015-01-01
Polls for majoritarian voting systems usually show estimates of the percentage of votes for each candidate. However, proportional vote systems do not necessarily guarantee the candidate with the most percentage of votes will be elected. Thus, traditional methods used in majoritarian elections cannot be applied on proportional elections. In this context, the purpose of this paper was to perform a Bayesian inference on proportional elections considering the Brazilian system of seats distribution. More specifically, a methodology to answer the probability that a given party will have representation on the chamber of deputies was developed. Inferences were made on a Bayesian scenario using the Monte Carlo simulation technique, and the developed methodology was applied on data from the Brazilian elections for Members of the Legislative Assembly and Federal Chamber of Deputies in 2010. A performance rate was also presented to evaluate the efficiency of the methodology. Calculations and simulations were carried out using the free R statistical software. PMID:25786259
A Bayesian Nonparametric IRT Model
Karabatsos, George
2015-01-01
This paper introduces a flexible Bayesian nonparametric Item Response Theory (IRT) model, which applies to dichotomous or polytomous item responses, and which can apply to either unidimensional or multidimensional scaling. This is an infinite-mixture IRT model, with person ability and item difficulty parameters, and with a random intercept parameter that is assigned a mixing distribution, with mixing weights a probit function of other person and item parameters. As a result of its flexibility...
Bayesian segmentation of hyperspectral images
Mohammadpour, Adel; Mohammad-Djafari, Ali
2007-01-01
In this paper we consider the problem of joint segmentation of hyperspectral images in the Bayesian framework. The proposed approach is based on a Hidden Markov Modeling (HMM) of the images with common segmentation, or equivalently with common hidden classification label variables which is modeled by a Potts Markov Random Field. We introduce an appropriate Markov Chain Monte Carlo (MCMC) algorithm to implement the method and show some simulation results.
Bayesian segmentation of hyperspectral images
Mohammadpour, Adel; Féron, Olivier; Mohammad-Djafari, Ali
2004-11-01
In this paper we consider the problem of joint segmentation of hyperspectral images in the Bayesian framework. The proposed approach is based on a Hidden Markov Modeling (HMM) of the images with common segmentation, or equivalently with common hidden classification label variables which is modeled by a Potts Markov Random Field. We introduce an appropriate Markov Chain Monte Carlo (MCMC) algorithm to implement the method and show some simulation results.
Bayesian Stable Isotope Mixing Models
Parnell, Andrew C.; Phillips, Donald L.; Bearhop, Stuart; Semmens, Brice X.; Ward, Eric J.; Moore, Jonathan W.; Andrew L Jackson; Inger, Richard
2012-01-01
In this paper we review recent advances in Stable Isotope Mixing Models (SIMMs) and place them into an over-arching Bayesian statistical framework which allows for several useful extensions. SIMMs are used to quantify the proportional contributions of various sources to a mixture. The most widely used application is quantifying the diet of organisms based on the food sources they have been observed to consume. At the centre of the multivariate statistical model we propose is a compositional m...
Bayesian Network--Response Regression
WANG, LU; Durante, Daniele; Dunson, David B.
2016-01-01
There is an increasing interest in learning how human brain networks vary with continuous traits (e.g., personality, cognitive abilities, neurological disorders), but flexible procedures to accomplish this goal are limited. We develop a Bayesian semiparametric model, which combines low-rank factorizations and Gaussian process priors to allow flexible shifts of the conditional expectation for a network-valued random variable across the feature space, while including subject-specific random eff...
Bayesian estimation of turbulent motion
Héas, P.; Herzet, C.; Mémin, E.; Heitz, D.; P. D. Mininni
2013-01-01
International audience Based on physical laws describing the multi-scale structure of turbulent flows, this article proposes a regularizer for fluid motion estimation from an image sequence. Regularization is achieved by imposing some scale invariance property between histograms of motion increments computed at different scales. By reformulating this problem from a Bayesian perspective, an algorithm is proposed to jointly estimate motion, regularization hyper-parameters, and to select the ...
Elements of Bayesian experimental design
Sivia, D.S. [Rutherford Appleton Lab., Oxon (United Kingdom)
1997-09-01
We consider some elements of the Bayesian approach that are important for optimal experimental design. While the underlying principles used are very general, and are explained in detail in a recent tutorial text, they are applied here to the specific case of characterising the inferential value of different resolution peakshapes. This particular issue was considered earlier by Silver, Sivia and Pynn (1989, 1990a, 1990b), and the following presentation confirms and extends the conclusions of their analysis.
Skill Rating by Bayesian Inference
Di Fatta, Giuseppe; Haworth, Guy McCrossan; Regan, Kenneth W.
2009-01-01
Systems Engineering often involves computer modelling the behaviour of proposed systems and their components. Where a component is human, fallibility must be modelled by a stochastic agent. The identification of a model of decision-making over quantifiable options is investigated using the game-domain of Chess. Bayesian methods are used to infer the distribution of players’ skill levels from the moves they play rather than from their competitive results. The approach is used on large sets of ...
Topics in Nonparametric Bayesian Statistics
2003-01-01
The intersection set of Bayesian and nonparametric statistics was almost empty until about 1973, but now seems to be growing at a healthy rate. This chapter gives an overview of various theoretical and applied research themes inside this field, partly complementing and extending recent reviews of Dey, Müller and Sinha (1998) and Walker, Damien, Laud and Smith (1999). The intention is not to be complete or exhaustive, but rather to touch on research areas of interest, partly by example.
Cover Tree Bayesian Reinforcement Learning
Tziortziotis, Nikolaos; Dimitrakakis, Christos; Blekas, Konstantinos
2013-01-01
This paper proposes an online tree-based Bayesian approach for reinforcement learning. For inference, we employ a generalised context tree model. This defines a distribution on multivariate Gaussian piecewise-linear models, which can be updated in closed form. The tree structure itself is constructed using the cover tree method, which remains efficient in high dimensional spaces. We combine the model with Thompson sampling and approximate dynamic programming to obtain effective exploration po...
Bayesian kinematic earthquake source models
Minson, S. E.; Simons, M.; Beck, J. L.; Genrich, J. F.; Galetzka, J. E.; Chowdhury, F.; Owen, S. E.; Webb, F.; Comte, D.; Glass, B.; Leiva, C.; Ortega, F. H.
2009-12-01
Most coseismic, postseismic, and interseismic slip models are based on highly regularized optimizations which yield one solution which satisfies the data given a particular set of regularizing constraints. This regularization hampers our ability to answer basic questions such as whether seismic and aseismic slip overlap or instead rupture separate portions of the fault zone. We present a Bayesian methodology for generating kinematic earthquake source models with a focus on large subduction zone earthquakes. Unlike classical optimization approaches, Bayesian techniques sample the ensemble of all acceptable models presented as an a posteriori probability density function (PDF), and thus we can explore the entire solution space to determine, for example, which model parameters are well determined and which are not, or what is the likelihood that two slip distributions overlap in space. Bayesian sampling also has the advantage that all a priori knowledge of the source process can be used to mold the a posteriori ensemble of models. Although very powerful, Bayesian methods have up to now been of limited use in geophysical modeling because they are only computationally feasible for problems with a small number of free parameters due to what is called the "curse of dimensionality." However, our methodology can successfully sample solution spaces of many hundreds of parameters, which is sufficient to produce finite fault kinematic earthquake models. Our algorithm is a modification of the tempered Markov chain Monte Carlo (tempered MCMC or TMCMC) method. In our algorithm, we sample a "tempered" a posteriori PDF using many MCMC simulations running in parallel and evolutionary computation in which models which fit the data poorly are preferentially eliminated in favor of models which better predict the data. We present results for both synthetic test problems as well as for the 2007 Mw 7.8 Tocopilla, Chile earthquake, the latter of which is constrained by InSAR, local high
Bayesian Kernel Mixtures for Counts
Canale, Antonio; David B Dunson
2011-01-01
Although Bayesian nonparametric mixture models for continuous data are well developed, there is a limited literature on related approaches for count data. A common strategy is to use a mixture of Poissons, which unfortunately is quite restrictive in not accounting for distributions having variance less than the mean. Other approaches include mixing multinomials, which requires finite support, and using a Dirichlet process prior with a Poisson base measure, which does not allow smooth deviatio...
Bayesian Optimization for Adaptive MCMC
Mahendran, Nimalan; Wang, Ziyu; Hamze, Firas; De Freitas, Nando
2011-01-01
This paper proposes a new randomized strategy for adaptive MCMC using Bayesian optimization. This approach applies to non-differentiable objective functions and trades off exploration and exploitation to reduce the number of potentially costly objective function evaluations. We demonstrate the strategy in the complex setting of sampling from constrained, discrete and densely connected probabilistic graphical models where, for each variation of the problem, one needs to adjust the parameters o...
Inference in hybrid Bayesian networks
Lanseth, Helge; Nielsen, Thomas Dyhre; Rumí, Rafael;
2009-01-01
and reliability block diagrams). However, limitations in the BNs' calculation engine have prevented BNs from becoming equally popular for domains containing mixtures of both discrete and continuous variables (so-called hybrid domains). In this paper we focus on these difficulties, and summarize some of the last...... decade's research on inference in hybrid Bayesian networks. The discussions are linked to an example model for estimating human reliability....
Quantile pyramids for Bayesian nonparametrics
2009-01-01
P\\'{o}lya trees fix partitions and use random probabilities in order to construct random probability measures. With quantile pyramids we instead fix probabilities and use random partitions. For nonparametric Bayesian inference we use a prior which supports piecewise linear quantile functions, based on the need to work with a finite set of partitions, yet we show that the limiting version of the prior exists. We also discuss and investigate an alternative model based on the so-called substitut...
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 analysis of contingency tables
Gómez Villegas, Miguel A.; González Pérez, Beatriz
2005-01-01
The display of the data by means of contingency tables is used in different approaches to statistical inference, for example, to broach the test of homogeneity of independent multinomial distributions. We develop a Bayesian procedure to test simple null hypotheses versus bilateral alternatives in contingency tables. Given independent samples of two binomial distributions and taking a mixed prior distribution, we calculate the posterior probability that the proportion of successes in the first...
Bayesian Credit Ratings (new version)
Paola Cerchiello; Paolo Giudici
2013-01-01
In this contribution we aim at improving ordinal variable selection in the context of causal models. In this regard, we propose an approach that provides a formal inferential tool to compare the explanatory power of each covariate, and, therefore, to select an effective model for classification purposes. Our proposed model is Bayesian nonparametric, and, thus, keeps the amount of model specification to a minimum. We consider the case in which information from the covariates is at the ordinal ...
Bayesian second law of thermodynamics
Bartolotta, Anthony; Carroll, Sean M.; Leichenauer, Stefan; Pollack, Jason
2016-08-01
We derive a generalization of the second law of thermodynamics that uses Bayesian updates to explicitly incorporate the effects of a measurement of a system at some point in its evolution. By allowing an experimenter's knowledge to be updated by the measurement process, this formulation resolves a tension between the fact that the entropy of a statistical system can sometimes fluctuate downward and the information-theoretic idea that knowledge of a stochastically evolving system degrades over time. The Bayesian second law can be written as Δ H (ρm,ρ ) + F |m≥0 , where Δ H (ρm,ρ ) is the change in the cross entropy between the original phase-space probability distribution ρ and the measurement-updated distribution ρm and F |m is the expectation value of a generalized heat flow out of the system. We also derive refined versions of the second law that bound the entropy increase from below by a non-negative number, as well as Bayesian versions of integral fluctuation theorems. We demonstrate the formalism using simple analytical and numerical examples.
Quantum Inference on Bayesian Networks
Yoder, Theodore; Low, Guang Hao; Chuang, Isaac
2014-03-01
Because quantum physics is naturally probabilistic, it seems reasonable to expect physical systems to describe probabilities and their evolution in a natural fashion. Here, we use quantum computation to speedup sampling from a graphical probability model, the Bayesian network. A specialization of this sampling problem is approximate Bayesian inference, where the distribution on query variables is sampled given the values e of evidence variables. Inference is a key part of modern machine learning and artificial intelligence tasks, but is known to be NP-hard. Classically, a single unbiased sample is obtained from a Bayesian network on n variables with at most m parents per node in time (nmP(e) - 1 / 2) , depending critically on P(e) , the probability the evidence might occur in the first place. However, by implementing a quantum version of rejection sampling, we obtain a square-root speedup, taking (n2m P(e) -1/2) time per sample. The speedup is the result of amplitude amplification, which is proving to be broadly applicable in sampling and machine learning tasks. In particular, we provide an explicit and efficient circuit construction that implements the algorithm without the need for oracle access.
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...
[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 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...
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...
Bayesian networks with applications in reliability analysis
Langseth, Helge
2002-01-01
A common goal of the papers in this thesis is to propose, formalize and exemplify the use of Bayesian networks as a modelling tool in reliability analysis. The papers span work in which Bayesian networks are merely used as a modelling tool (Paper I), work where models are specially designed to utilize the inference algorithms of Bayesian networks (Paper II and Paper III), and work where the focus has been on extending the applicability of Bayesian networks to very large domains (Paper IV and ...
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.…
The Idea of Ancient Greek Philosophy
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.
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…
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
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
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.
Archimedes: Accelerator Reveals Ancient Text
Archimedes (287-212 BC), who is famous for shouting 'Eureka' (I found it) is considered one of the most brilliant thinkers of all times. The 10th-century parchment document known as the 'Archimedes Palimpsest' is the unique source for two of the great Greek's treatises. Some of the writings, hidden under gold forgeries, have recently been revealed at the Stanford Synchrotron Radiation Laboratory at SLAC. An intense x-ray beam produced in a particle accelerator causes the iron in original ink, which has been partly erased and covered, to send out a fluorescence glow. A detector records the signal and a digital image showing the ancient writings is produced. Please join us in this fascinating journey of a 1,000-year-old parchment from its origin in the Mediterranean city of Constantinople to a particle accelerator in Menlo Park.
Ancient Acupuncture Literature on Apoplexy
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.
Bayesian phylogeography finds its roots.
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.
Bayesian Methods and Universal Darwinism
Campbell, John
2009-12-01
Bayesian methods since the time of Laplace have been understood by their practitioners as closely aligned to the scientific method. Indeed a recent Champion of Bayesian methods, E. T. Jaynes, titled his textbook on the subject Probability Theory: the Logic of Science. Many philosophers of science including Karl Popper and Donald Campbell have interpreted the evolution of Science as a Darwinian process consisting of a `copy with selective retention' algorithm abstracted from Darwin's theory of Natural Selection. Arguments are presented for an isomorphism between Bayesian Methods and Darwinian processes. Universal Darwinism, as the term has been developed by Richard Dawkins, Daniel Dennett and Susan Blackmore, is the collection of scientific theories which explain the creation and evolution of their subject matter as due to the Operation of Darwinian processes. These subject matters span the fields of atomic physics, chemistry, biology and the social sciences. The principle of Maximum Entropy states that Systems will evolve to states of highest entropy subject to the constraints of scientific law. This principle may be inverted to provide illumination as to the nature of scientific law. Our best cosmological theories suggest the universe contained much less complexity during the period shortly after the Big Bang than it does at present. The scientific subject matter of atomic physics, chemistry, biology and the social sciences has been created since that time. An explanation is proposed for the existence of this subject matter as due to the evolution of constraints in the form of adaptations imposed on Maximum Entropy. It is argued these adaptations were discovered and instantiated through the Operations of a succession of Darwinian processes.
Bayesian Query-Focused Summarization
Daumé, Hal
2009-01-01
We present BayeSum (for ``Bayesian summarization''), a model for sentence extraction in query-focused summarization. BayeSum leverages the common case in which multiple documents are relevant to a single query. Using these documents as reinforcement for query terms, BayeSum is not afflicted by the paucity of information in short queries. We show that approximate inference in BayeSum is possible on large data sets and results in a state-of-the-art summarization system. Furthermore, we show how BayeSum can be understood as a justified query expansion technique in the language modeling for IR framework.
Numeracy, frequency, and Bayesian reasoning
Gretchen B. Chapman
2009-02-01
Full Text Available Previous research has demonstrated that Bayesian reasoning performance is improved if uncertainty information is presented as natural frequencies rather than single-event probabilities. A questionnaire study of 342 college students replicated this effect but also found that the performance-boosting benefits of the natural frequency presentation occurred primarily for participants who scored high in numeracy. This finding suggests that even comprehension and manipulation of natural frequencies requires a certain threshold of numeracy abilities, and that the beneficial effects of natural frequency presentation may not be as general as previously believed.
Bayesian inference for Hawkes processes
Rasmussen, Jakob Gulddahl
The Hawkes process is a practically and theoretically important class of point processes, but parameter-estimation for such a process can pose various problems. In this paper we explore and compare two approaches to Bayesian inference. The first approach is based on the so-called conditional...... intensity function, while the second approach is based on an underlying clustering and branching structure in the Hawkes process. For practical use, MCMC (Markov chain Monte Carlo) methods are employed. The two approaches are compared numerically using three examples of the Hawkes process....
Bayesian inference for Hawkes processes
Rasmussen, Jakob Gulddahl
2013-01-01
The Hawkes process is a practically and theoretically important class of point processes, but parameter-estimation for such a process can pose various problems. In this paper we explore and compare two approaches to Bayesian inference. The first approach is based on the so-called conditional...... intensity function, while the second approach is based on an underlying clustering and branching structure in the Hawkes process. For practical use, MCMC (Markov chain Monte Carlo) methods are employed. The two approaches are compared numerically using three examples of the Hawkes process....
Collaborative Kalman Filtration: Bayesian Perspective
Dedecius, Kamil
Lisabon, Portugalsko: Institute for Systems and Technologies of Information, Control and Communication (INSTICC), 2014, s. 468-474. ISBN 978-989-758-039-0. [11th International Conference on Informatics in Control, Automation and Robotics - ICINCO 2014. Vien (AT), 01.09.2014-03.09.2014] R&D Projects: GA ČR(CZ) GP14-06678P Institutional support: RVO:67985556 Keywords : Bayesian analysis * Kalman filter * distributed estimation Subject RIV: BB - Applied Statistics, Operational Research http://library.utia.cas.cz/separaty/2014/AS/dedecius-0431324.pdf
Bayesian credible interval construction for Poisson statistics
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.