• PRISM

  • Referenced in 33 articles [sw23359]
  • describe various types of symbolic-statistical modeling formalism known but unrelated ... modeling formalisms, the hidden Markov model and Bayesian networks, are described by PRISM programs...
  • PROC MCMC

  • Referenced in 2 articles [sw12072]
  • designed to fit Bayesian models. Bayesian statistics is different from traditional statistical methods such ... varying degrees of difficulty. In essence, Bayesian statistics treats parameters as unknown random variables ... several advantages associated with this approach to statistical inference. Some of the advantages include ... relative advantages and disadvantages of Bayesian analysis, see the section Bayesian Analysis: Advantages and Disadvantages...
  • LearnBayes

  • Referenced in 3 articles [sw04495]
  • learning the basic tenets of Bayesian statistical inference. It contains functions for summarizing basic ... contains functions for regression models, hierarchical models, Bayesian tests, and illustrations of Gibbs sampling...
  • SAVE

  • Referenced in 3 articles [sw24205]
  • Validation of Computer Models. Implements Bayesian statistical methodology for the analysis of complex computer models...
  • GPS-ABC

  • Referenced in 12 articles [sw16117]
  • challenging. The Approximate Bayesian Computation (ABC) framework is the standard statistical tool to handle these...
  • RSS

  • Referenced in 2 articles [sw23316]
  • Regression with Summary Statistics: Bayesian large-scale multiple regression with summary statistics from genome-wide ... association studies. Bayesian methods for large-scale multiple regression provide attractive approaches to the analysis ... Specifically, we introduce a “Regression with Summary Statistics” (RSS) likelihood, which relates the multiple regression ... obtained from public databases. We perform Bayesian multiple regression analysis by combining the RSS likelihood...
  • BCM

  • Referenced in 2 articles [sw22361]
  • predictions of computational models using Bayesian statistics...
  • pomp

  • Referenced in 34 articles [sw10664]
  • package pomp: Statistical Inference for Partially Observed Markov Processes. Tools for working with partially observed ... data by a variety of frequentist and Bayesian methods. It is also a platform...
  • Amos

  • Referenced in 57 articles [sw06515]
  • models more accurately than with standard multivariate statistics techniques. Users can choose either the graphical ... easily compare, confirm and refine models. Uses Bayesian analysis—to improve estimates of model parameters...
  • WebBUGS

  • Referenced in 2 articles [sw24311]
  • WebBUGS: Conducting Bayesian Statistical Analysis Online. A web interface, named WebBUGS, is developed to conduct...
  • abctools

  • Referenced in 6 articles [sw14870]
  • Analyses. Tools for approximate Bayesian computation including summary statistic selection and assessing coverage...
  • bayes4psy

  • Referenced in 1 article [sw29388]
  • Open Source R Package for Bayesian Statistics in Psychology. Research in psychology generates interesting data ... appropriate statistical models and methods cannot be found in accessible Bayesian tools. As a result ... Bayesian methods is limited to those that have the technical and statistical fundamentals that ... teaching tool for Bayesian statistics in psychology. The package contains Bayesian t-test and bootstrapping...
  • BaySICS

  • Referenced in 1 article [sw32670]
  • BaySICS: A User-Friendly Program for Bayesian Statistical Inference from Coalescent Simulations. Inference of population ... including the use of ancient DNA. Approximate Bayesian computation (ABC) stands among the most promising ... Here we present the software BaySICS: Bayesian Statistical Inference of Coalescent Simulations. BaySICS provides...
  • dlm

  • Referenced in 27 articles [sw04503]
  • Maximum likelihood, Kalman filtering and smoothing, and Bayesian analysis of Normal linear State Space models ... Models. This book gives an introduction to statistical time series analysis by dynamic linear models ... gives an introduction, presenting basic notions in Bayesian inference. The basic elements of Bayesian analysis...
  • BAT

  • Referenced in 5 articles [sw00067]
  • free parameters of a model. The Bayesian Analysis Toolkit, BAT, is a software package which ... designed to help solve statistical problems encountered in Bayesian inference. BAT is based on Bayes...
  • ABC-SysBio

  • Referenced in 6 articles [sw24739]
  • SysBio: Approximate Bayesian Computation in Python with GPU support. MOTIVATION: The growing field of systems ... parameters. A number of statistical approaches, both frequentist and Bayesian, have been proposed to answer...
  • moloc

  • Referenced in 1 article [sw31660]
  • Bayesian Framework for Multiple Trait Colocalization from Summary Association Statistics. In this work ... propose multiple-trait-coloc (moloc), a Bayesian statistical framework that integrates GWAS summary data with...
  • YADAS

  • Referenced in 1 article [sw28131]
  • applying Bayesian methods is the need to develop new software to analyze novel statistical models ... YADAS, that facilitates the development of Bayesian statistical analyses. It includes classes that help analysts...
  • AMORPH

  • Referenced in 1 article [sw25890]
  • diffraction. AMORPH utilizes a new Bayesian statistical approach to interpreting X-ray diffraction results...
  • IRTm2noHA

  • Referenced in 2 articles [sw25347]
  • MCMC chain, and obtain Bayesian fit statistics. Illustrative examples are provided to demonstrate and validate...