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70 results for “bayesian approach”
Relativistic description of dense matter equation of state and compatibility with neutron star observables: a Bayesian approach
<p>The general behavior of the nuclear equation of state (EOS), relevant for the description of neutron stars (NS), is studied within a Bayesian approach applied to a set of models based on a density-dependent relativistic mean-field description of nuclear matter <a href="https://arxiv.org/abs/2201.12552">Malik et al 2022</a>. The EOS is subjected to a minimal number of constraints based on nuclear saturation properties and the low-density pure neutron matter EOS obtained from a precise next-to-next-to-next-to-leading order (N$^{3}$LO) calculation in chiral effective field theory ($\chi$EFT). The number of final sample parameters corresponding to the posterior sets is around fourteen thousand. We present five EOSs among them, namely DDBl, DDBm, DDBu1, DDBu2, and DDBx. The DDBl, DDBm, DDBu2 were chosen so that the radius of the 1.4$M_\odot$ star has the lower limit, a medium value, and the upper limit of the 90% CI for the conditional probabilities $P(R|M)$. We have also included DDBu1 that has a slightly lower $R_{1.4}$ than the upper limit but lies completely inside the 90% CI for the conditional probabilities $P(R|M)$. The DDBx is the one that predicts a maximum mass of 2.5$M_\odot$ and has the following nuclear matter properties, $K_0=300$ MeV, $J_{sym,0}=30$ MeV and $L_{sym,0}=39$ MeV.</p> <p>We also release our entire sets of ~14K NS matter EOS. All the EOSs are for NS core and starting baryon density is 0.04 fm$^{-3}$. One needs to add their own choice of crust EOS for the star properties calculation. The uncertainty in star properties for the choice of the different crust has been discussed in Section 2.1 of the manuscript (arxiv: 2201.12552). </p> <pre> To extract the entire sets of ~14K NS matter EOS files, one needs to follow the steps, 1) unzip DDB_EOS_14K.zip ----------------------------Note------------------------------------- All the eos files have three columns baryon density (fm-3), energy density (MeV.fm-3), and pressure (MeV.fm-3). The starting density is 0.04 fm-3, as it is NS core eos. One needs to add their own choice of crust eos in order to calculate NS properties. ---------------------------------------------------------------</pre> <p> </p> <p> </p>
A Bayesian Approach to Detect Pedestrian Destination-Sequences from WiFi Signatures: Data (Transp. Res. Part C, 2014)
<p>This dataset contains and describes the data used in</p> <p>Danalet, A., Farooq, B., & Bierlaire, M. (2014). A Bayesian approach to detect pedestrian destination-sequences from WiFi signatures. <em>Transportation Research Part C: Emerging Technologies</em>, <strong>44</strong>, 146-170. doi:10.1016/j.trc.2014.03.015</p> <p>Specifically it contains WiFi traces, pedestrian Semantically-Enriched Routing Graph (SERG), and Potential Attractivity measure (PAM).</p>
Data and codes for 'A Bayesian Approach to Blood Rheological Uncertainties in Aortic Hemodynamics'
<p>This submission is supplementary material in the form of data and codes used in and for the manuscript 'A Bayesian Approach to Blood Rheological Uncertainties in Aortic Hemodynamics' submitted to the International Journal of Numerical Methods in Biomedical Engineering (currently under review).</p>
Figure 1. Bayesian phylogenetic tree inferred from the 640 in Two new Geoplaninae species (Platyhelminthes: Continenticola) from Southern Brazil based on an integrative taxonomic approach
Figure 1. Bayesian phylogenetic tree inferred from the 640-bp of cytochrome c oxidase subunit I gene under GTR + I + G model of sequence evolution. The two new species are highlighted in light grey (Cratera ochra sp. nov.) and dark grey (Obama maculipunctata sp. nov.). Values indicate support for each node according to the maximum posterior probabilities>70% and bootstrap support values> 70%, respectively.
Fig. 2. The Bayesian consensus tree basedon 988 in Integrative approach to resolve the Calotes mystaceus Duméril & Bibron, 1837 species complex (Squamata: Agamidae)
Fig. 2. The Bayesian consensus tree basedon 988 bp of mitochondrial DNA (12S rRNA and COI) shows six distinctlineages within Calotes mystaceus. Node support in terms of Bayesian posterior probabilities is indicated by circles at nodes (nodes with a BPP ≥ 0.90 are white, BPP ≥ 0.95 are grey, BPP ≥ 0.99 are black, values <0.90 arenot marked). Outgroup (Calotes versicolor) notshown for clarity. Numbers in parentheses behind taxa refer to localities mapped in Fig. 1.
Figure 42. Bayesian 50 in A species complex within the isopod genus Haploniscus (Crustacea: Malacostraca: Peracarida) from the Southern Ocean deep sea: a morphological and molecular approach
Figure 42. Bayesian 50% majority rule consensus tree of the 16S rDNA data set. Model choice based on AIC: TVM model with gamma distributed rates (alpha = 0.3755) and no invariant positions (see text for more details). Values above the branches are posterior proabilities of the 16S rDNA data set, values below of the 18S rDNA data set (if applicable).
Molecular dating for phylogenies containing a mix of populations and species by using Bayesian and RelTime approaches
<p><span><span><span><span><span><span><span><span><span><span><span>Simultaneous molecular dating of population and species divergences is essential in many biological investigations, including phylogeography, phylodynamics, and species delimitation studies. In these investigations, multiple sequence alignments consist of both intra- and inter-species samples (mixed samples). As a result, the phylogenetic trees contain inter-species, inter-population, and within-population divergences. Bayesian relaxed clock methods are often employed in these analyses, but they assume the same tree prior for both inter- and intra-species branching processes and require specification of a clock model for branch rates (independent vs. autocorrelated rates models). We evaluated the impact of a single tree prior onBayesian divergence time estimates by analyzing computer-simulated datasets. We also examined the effectof the assumption of independence of evolutionary rate variation among branches when the branch rates are autocorrelated. Bayesian approach with coalescent tree priors generally produced excellent molecular dates and highest posterior densities with high coverage probabilities. We also evaluated the performance of a non-Bayesian method, RelTime, which does not require the specification of a tree prior or a clock model. RelTime's performance was similar to that of the Bayesian approach, suggesting that it is also suitable to analyze datasets containing both populations and species variation when its computational-efficiency is needed.</span></span></span></span></span></span></span></span></span></span></span></p>
Data from: A Bayesian approach for inferring the impact of a discrete character on rates of continuous-character evolution in the presence of background-rate variation
Understanding how and why rates of character evolution vary across the Tree of Life is central to many evolutionary questions; e.g., does the trophic apparatus (a set of continuous characters) evolve at a higher rate in fish lineages that dwell in reef versus non-reef habitats (a discrete character)? Existing approaches for inferring the relationship between a discrete character and rates of continuous-character evolution rely on comparing a null model (in which rates of continuous-character evolution are constant across lineages) to an alternative model (in which rates of continuous-character evolution depend on the state of the discrete character under consideration). However, these approaches are susceptible to a "straw-man" effect: the influence of the discrete character is inflated because the null model is extremely unrealistic. Here, we describe MuSSCRat, a Bayesian approach for inferring the impact of a discrete trait on rates of continuous-character evolution in the presence of alternative sources of rate variation ("background-rate variation"). We demonstrate by simulation that our method is able to reliably infer the degree of state-dependent rate variation, and show that ignoring background-rate variation leads to biased inferences regarding the degree of state-dependent rate variation in grunts (the fish group Haemulidae).
A Bayesian Approach to Detect Pedestrian Destination-Sequences from WiFi Signatures: Data (tech. report 2013)
<p>This dataset contains the data used in:</p> <p>Danalet, A., Farooq, B. and Bierlaire, M. (2013). A Bayesian Approach to Detect Pedestrian Destination-Sequences from WiFi Signatures, Technical report, Transport and Mobility Laboratory, ENAC, Ecole Polytechnique Fédérale de Lausanne, Lausanne. URL: http://infoscience.epfl.ch/record/189759 (full text available)</p> <p>It contains data and a technical report describing</p> <ul> <li>WiFi traces</li> <li>Pedestrian Semantically-Enriched Routing Graph (SERG), and</li> <li>Potential Attractivity measure (PAM).</li> </ul>
A Clustering Approach to Improve IntraVoxel Incoherent Motion Maps from DW-MRI using Conditional Auto-Regressive Bayesian Model
<p>Simulated data generated and used in the paper "A Clustering Approach to Improve IntraVoxel Incoherent Motion Maps from DW-MRI using Conditional Auto-Regressive Bayesian Model" are here available.</p> <p>Results generated from both simulated and clinical datasets are also available on the excel tables.</p>
Rare and widespread: Integrating Bayesian MCMC approaches, Sanger sequencing and Hyb-Seq phylogenomics to reconstruct the origin of the enigmatic Rand Flora genus Camptoloma
<p class="MsoCommentText">Premise</p> <p class="MsoCommentText">Genera that are widespread but have a geographically discontinuous distribution and are represented by few species are intriguing. Did they achieve their disjunct distribution recently, or is it ancient in origin? Why are they species-poor? The Rand Flora is a continental-scale floristic pattern in which closely related species appear co-distributed in isolated regions over the edges of Africa and nearby archipelagos. Genus <i>Camptoloma</i> (Scrophulariaceae) is the most notable example, comprising three species isolated from each other at the ends of the African continent: <i>C. canariense </i>in the west, endemic to the Canary Islands; <i>C. lyperiiflorum </i>in the east, endemic to the Horn of Africa - Southern Arabia; and <i>C. rotundifolia</i>, restricted to Southern Africa.</p> <p class="MsoCommentText">Methods</p> <p class="MsoCommentText">Here, we employed Sanger sequencing of nuclear and plastid markers, together with genomic target sequencing of 2190 low-copy nuclear genes, to infer interspecies relationships and the position of <i>Camptoloma</i> within Scrophulariaceae, using supermatrix and multispecies-coalescent approaches. Lineage divergence times and ancestral ranges were inferred with Bayesian MCMC approaches. Population history was estimated with phylogeographic structured coalescent methods.</p> <p class="MsoCommentText">Key Results</p> <p class="MsoCommentText">Our results support <i>C. rotundifolia</i> as sister to the disjunct clade formed by <i>C. canariense</i> and <i>C. lyperiiflorum.</i> Stem divergence was dated in the Late Miocene, while the origin of extant diversification within the genus was inferred as Early Pliocene.</p> <p class="MsoCommentText">Conclusions</p> <p>We show that the current disjunct distribution of <i>Camptoloma </i>across Africa was likely the result of fragmentation and extinction/population bottlenecking events associated to historical aridification cycles, consistent with the "climatic refugia" hypothesis.</p>
Unified EoS within Nambu–Jona-Lasinio description of hadronic matter from a Bayesian approach
<p># Introduction to the Unified Equations of State Dataset for Neutron Star Properties</p> <p>This dataset comprises three unified equations of state (EOS) for neutron star properties, denoted as eNJL1, eNJL2, and eNJL3, developed based on a microscopic nuclear matter formalism with explicit chiral symmetry. This formalism is grounded in the Nambu Jona-Lasinio (NJL) model and has been specifically designed to accurately describe nuclear matter by introducing four-point and eight-point interactions. These interactions are crucial for reproducing nuclear matter properties at saturation density.</p> <p>### Background and Methodology</p> <p>To ensure the robustness and accuracy of the model parameters, a Bayesian inference approach was utilized. This method involved imposing constraints from experimental and {\it ab-initio} nuclear matter calculations, as well as observational data from neutron stars. Key properties such as the effective nucleon mass, radius, and maximum mass of neutron stars were meticulously matched against these constraints. The resulting model parameters provide a comprehensive and reliable description of nuclear matter and neutron star properties.</p> <p>### Key Findings</p> <p>- **Effective Nucleon Mass:** The model predicts an effective nucleon mass range between 0.75 and 0.8 times the nucleon mass.<br>- **Neutron Star Radius:** At a 90% confidence level, the radius of a 1.4 $M_\odot$ neutron star varies between 11.48 km and 13.20 km.<br>- **Maximum Mass and Radius:** The model predicts neutron stars with masses up to approximately 2.2 $M_\odot$, with the radius of a 2 $M_\odot$ star being above 10.5 km.<br>- **Speed of Sound:** The speed of sound in the center of massive stars increases monotonically with density, reaching values between $\sqrt{0.7}c$ and $\sqrt{0.8}c$.</p> <p>### High-Density Constraints and Observational Alignment</p> <p>The high-density perturbative QCD (pQCD) results impose significant constraints on the EOS, invalidating those predicting larger maximum masses and radii. Interestingly, the EOS that satisfy pQCD constraints also align closely with recent mass-radius measurements, particularly those of PSR J0437-4715. This alignment provides an additional layer of validation against other relativistic mean field model results.</p> <p>### Dataset Overview</p> <p>This dataset includes three distinct EOS models (eNJL1, eNJL2, and eNJL3), each offering a unified approach for calculating neutron star properties. These models are detailed in the associated article, where the implications of the findings and the methodology are thoroughly discussed.</p> <p>Researchers and astrophysicists can utilize this dataset to further explore and model the properties of neutron stars, contributing to a deeper understanding of these fascinating celestial objects. The provided EOS models are essential tools for simulations and theoretical studies aimed at deciphering the complex nature of neutron stars and nuclear matter under extreme conditions.</p>
CLDF dataset derived from Oskolskaya et al.'s "A Bayesian approach to the classification of Tungusic languages" from 2021
<p>Cite the source of the dataset as:</p> <blockquote> <p>Oskolskaya, S., Koile, E., & Robbeets, M. (2021). A Bayesian approach to the classification of Tungusic languages. Diachronica, 39(1), 128–158. https://doi.org/10.1075/dia.20010.osk</p> </blockquote>
Characterizing the spatial correlation of coseismic slip distributions: A data driven Bayesian approach
<p>Slip models for the simulated case and the Illapel earthquake are provided. The zip file contains processed data, predictions, and uncertainty estimates for the Illapel event.</p>
Inferring predator-prey interactions from camera traps: A Bayesian co-abundance modelling approach
<p><span>Predator-prey dynamics are a fundamental part of ecology, but directly studying interactions has proven difficult. The proliferation of camera trapping has enabled the collection of large datasets on wildlife, but researchers face hurdles inferring interactions from observational data. </span><span>Recent advances in </span><span>hierarchical c</span><span>o-abundance models infer species interactions while </span><span>accounting for two species' detection probabilities, shared responses to environmental covariates, and propagate uncertainty throughout the</span> <span>entire modelling process. However, current approaches remain </span><span>unsuitable for interacting species </span><span>whose natural densities differ by an order of magnitude and have contrasting detection probabilities, such as predator-prey interactions, which introduce zero-inflation and overdispersion in count histories. </span><span>Here we developed </span><span>a Bayesian hierarchical N-mixture co-abundance model that is </span><span>suitable for </span><span>inferring </span><span>predator-prey </span><span>interactions. We accounted for excessive zeros in count histories using an informed zero-inflated Poisson distribution in the abundance formula and accounted for overdispersion in count histories by including a random effect per sampling unit and sampling occasion in the detection probability formula. We demonstrate that models with these modifications outperform alternative approaches, improve model goodness-of-fit, and overcome parameter convergence failures. We highlight its utility using 20 camera trapping datasets </span><span>from 10 tropical forest landscapes in Southeast Asia and estimate four predator-prey relationships between tigers, clouded leopards, and muntjac and sambar deer. Tigers had a negative effect on muntjac abundance, providing support for top-down regulation, while clouded leopards had a positive effect on muntjac and sambar deer, likely driven by shared responses to unmodelled covariates like hunting. </span><span>This Bayesian co-abundance modelling approach to quantify predator-prey relationships </span><span>is widely applicable across species, ecosystems, and sampling approaches, and may be useful in forecasting cascading impacts following widespread predator declines. Taken together, this approach facilitates a nuanced and mechanistic understanding of food-web ecology.</span></p>
The optimal time to approach an unfamiliar object: A Bayesian model
<p>Many organisms take time before approaching unfamiliar objects. This caution forms the basis of some well-known assays in the fields of behavioral ecology, comparative psychology and animal welfare, including quantifying the personality traits of individuals and evaluating the extent of their neophobia. In this paper we present a mathematical model which identifies the optimal time an observer should wait before approaching an unfamiliar object. The model is Bayesian, and simply assumes that the longer the observer goes without being attacked by an unfamiliar object, the lower will be the observer's estimated probability that the object is dangerous. Given the information gained, a time is reached at which the expected benefits from approaching the object begin to exceed the costs. The model not only explains why latency to approach may be repeatable among individuals and vary with the object's appearance, but also why individuals habituate to the stimulus, approaching it more rapidly over repeated trials. We demonstrate the applicability of our model by fitting it to published data on the time taken by chicks to attack artificial caterpillars which share no, one, or two signaling traits with snakes (eyespots and posture). We use this example to show that while the optimal time to attack an unfamiliar object reflects the observer's expectation that the object is dangerous, the rate at which habituation arises is also a function of the observer's certainty in their belief. In so doing, we explain why observers become more rapidly habituated to "weaker" stimuli than "stronger" ones. </p>
Combining formal methods and Bayesian approach for inferring discrete-state stochastic models from steady-state data
<p>Model, data, and a script to a paper of respective name</p>
Data from: A Bayesian approach for inferring the impact of a discrete character on rates of continuous-character evolution in the presence of background-rate variation
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Inferring predator-prey interactions from camera traps: A Bayesian co-abundance modelling approach
Open the record for dataset details and reuse information.
Rare and widespread: Integrating Bayesian MCMC approaches, Sanger sequencing and Hyb-Seq phylogenomics to reconstruct the origin of the enigmatic Rand Flora genus Camptoloma
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Allen Brain Atlas
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
Annotated Behaviour and Observability Dataset (ABODe)
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DANDI Archive for NWB datasets
DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.
International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.