• SUN

  • Referenced in 13 articles [sw28156]
  • Bayesian framework for saliency using natural statistics. We propose a definition of saliency by considering ... directing attention. The resulting model is a Bayesian framework from which bottom-up saliency emerges ... existing saliency measures, which depend on the statistics of the particular image being viewed...
  • BayesTree

  • Referenced in 59 articles [sw07995]
  • posterior. Effectively, BART is a nonparametric Bayesian regression approach which uses dimensionally adaptive random basis ... particular, BART is defined by a statistical model: a prior and a likelihood. This approach...
  • PRISM

  • Referenced in 34 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...
  • bayes4psy

  • Referenced in 2 articles [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...
  • GPS-ABC

  • Referenced in 15 articles [sw16117]
  • challenging. The Approximate Bayesian Computation (ABC) framework is the standard statistical tool to handle these...
  • 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...
  • pomp

  • Referenced in 41 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...
  • SAVE

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

  • Referenced in 7 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...
  • 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...
  • Amos

  • Referenced in 60 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...
  • Nestle

  • Referenced in 2 articles [sw32995]
  • order to compare models in Bayesian statistics. It is similar to Markov Chain Monte Carlo...
  • BraMBLe

  • Referenced in 27 articles [sw36453]
  • BraMBLe: A Bayesian multiple blob tracker. Blob trackers have become increasingly powerful in recent years ... largely due to the adoption of statistical appearance models which allow effective background subtraction ... adapted from the theory of Bayesian correlation, but uses the assumption of a static camera...
  • abcrf

  • Referenced in 11 articles [sw21308]
  • grown into a standard methodology that manages Bayesian inference for models associated with intractable likelihood ... preliminary selection of a vector of informative statistics summarizing raw data. Furthermore, in almost ... calibrated. We propose to conduct likelihood-free Bayesian inferences about parameters with no prior selection ... relevant components of the summary statistics and bypassing the derivation of the associated tolerance level...
  • dlm

  • Referenced in 28 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...
  • rNPBST

  • Referenced in 1 article [sw38275]
  • Package Covering Non-parametric and Bayesian Statistical Tests. Statistical tests has arisen as a reliable ... statistical comparison applied to the field of algorithms’ performance comparison indicate that Bayesian tests, which ... contribution rNPBST (R Non-Parametric and Bayesian Statistical tests), an R package that contains...
  • 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...
  • RELION

  • Referenced in 10 articles [sw22792]
  • RELION uses a Bayesian approach to infer parameters of a statistical model from the data...