• tsbridge

  • Referenced in 171 articles [sw12354]
  • functions that can be used to estimate normalising constants using the bridge sampler of Meng ... variety of time series Bayesian models, where parameters are estimated using BUGS, and models themselves...
  • bnlearn

  • Referenced in 77 articles [sw08265]
  • learning, parameter learning and inference. Bayesian network structure learning, parameter learning and inference. This package ... well as support for parameter estimation (maximum likelihood and Bayesian) and inference, conditional probability queries...
  • IBAL

  • Referenced in 27 articles [sw08945]
  • observations. IBAL also integrates Bayesian parameter estimation and decisiontheoretic utility maximization thoroughly into the framework...
  • BioBayes

  • Referenced in 26 articles [sw08082]
  • BioBayes, which provides a framework for Bayesian parameter estimation and evidential model ranking over models...
  • Amos

  • Referenced in 60 articles [sw06515]
  • refine models. Uses Bayesian analysis—to improve estimates of model parameters. Offers various data imputation...
  • MrBayes

  • Referenced in 60 articles [sw07715]
  • Phylogeny. MrBayes is a program for Bayesian inference and model choice across a wide range ... Carlo (MCMC) methods to estimate the posterior distribution of model parameters...
  • HDDM

  • Referenced in 11 articles [sw16420]
  • HDDM: Hierarchical Bayesian estimation of the Drift-Diffusion Model in Python. The diffusion model ... current estimation methods require an abundance of response time measurements to recover meaningful parameters ... each parameter. In contrast, hierarchical Bayesian parameter estimation methods are useful for enhancing statistical power ... estimation of how trial-by-trial measurements (e.g., fMRI) influence decision-making parameters. This paper...
  • abc

  • Referenced in 51 articles [sw14871]
  • Approximate Bayesian Computation (ABC). Implements several ABC algorithms for performing parameter estimation, model selection...
  • JASP

  • Referenced in 7 articles [sw27700]
  • developments in Bayesian hypothesis testing and Bayesian parameter estimation. The ease with which these relatively...
  • dlm

  • Referenced in 30 articles [sw04503]
  • Maximum likelihood, Kalman filtering and smoothing, and Bayesian analysis of Normal linear State Space models ... dynamic linear models with known parameters, and maximum likelihood estimation. It also presents many specific ... gives an introduction, presenting basic notions in Bayesian inference. The basic elements of Bayesian analysis ... models with unknown parameters. It presents a discussion of maximum likelihood estimation and a much...
  • GSM

  • Referenced in 19 articles [sw10497]
  • Mixture: This package implements a Bayesian approach for estimation of a mixture of gamma distributions ... which the mixing occurs over the shape parameter. This family provides a flexible and novel...
  • LAMARC

  • Referenced in 7 articles [sw11443]
  • Lamarc 2.0: maximum likelihood and Bayesian estimation of population parameters. LAMARC is a program which...
  • Data2Dynamics

  • Referenced in 12 articles [sw25272]
  • variety of parameter estimation algorithms as well as frequentist and Bayesian methods for uncertainty analysis...
  • Filzbach

  • Referenced in 2 articles [sw13096]
  • Bayesian and likelihood analysis made easy: Filzbach is a flexible, fast, robust, parameter estimation engine ... heterogeneous data sets. Filzbach allows for Bayesian parameter estimation, maximum likelihood analysis, priors, latents, hierarchies...
  • DPpackage

  • Referenced in 70 articles [sw10495]
  • programs for the implementation of some Bayesian nonparametric and semiparametric models in R, DPpackage. Currently ... includes models for marginal and conditional density estimation, receiver operating characteristic curve analysis, interval-censored ... model comparison and for eliciting the precision parameter of the Dirichlet process prior...
  • BILBY

  • Referenced in 2 articles [sw35188]
  • Inference Library for Gravitational-wave Astronomy. Bayesian parameter estimation is fast becoming the language ... Bayesian inference library for gravitational-wave astronomy, Bilby. This Python code provides expert-level parameter ... estimation infrastructure with straightforward syntax and tools that facilitate use by beginners. It allows users ... perform accurate and reliable gravitational-wave parameter estimation on both real, freely available data from...
  • DIAMONDS

  • Referenced in 2 articles [sw36440]
  • code, termed Diamonds, for Bayesian parameter estimation and model comparison by means of the nested ... provide a criterion based on the Bayesian evidence for assessing the peak significance...
  • SamIam

  • Referenced in 17 articles [sw29886]
  • engine. The graphical interface lets users develop Bayesian network models and save them ... supports many tasks including: classical inference; parameter estimation; time-space tradeoffs; sensitivity analysis; and explanation...
  • bamlss

  • Referenced in 11 articles [sw24276]
  • estimating probabilistic distributional regression models in a Bayesian framework. The distribution parameters may capture location...
  • lalinference

  • Referenced in 1 article [sw11174]
  • Robust parameter estimation for compact binaries with ground-based gravitational-wave observations using LALInference ... compact objects. Recovering the physical parameters of the sources from the GW observations ... describes the LALInference software library for Bayesian parameter estimation of compact binary coalescence (CBC) signals...