• # dlm

• Referenced in 27 articles [sw04503]
• Maximum likelihood, Kalman filtering and smoothing, and Bayesian analysis of Normal linear State Space models ... state space models, the Kalman filter for estimation and forecasting in dynamic linear models with ... known parameters, and maximum likelihood estimation. It also presents many specific dynamic linear models particularly ... maximum likelihood estimation and a much more elaborated one on Bayesian inference. The last chapter...
• # abc

• Referenced in 34 articles [sw14871]
• Approximate Bayesian Computation (ABC). Implements several ABC algorithms for performing parameter estimation, model selection...
• # pacbpred

• Referenced in 4 articles [sw07805]
• package pacbpred: PAC-Bayesian Estimation and Prediction in Sparse Additive Models. This package is intended ... perform estimation and prediction in high-dimensional additive models, using a sparse PAC-Bayesian point ... Guedj and Alquier (2013), ’PAC-Bayesian Estimation and Prediction in Sparse Additive Models’, Electronic Journal...
• # spatcounts

• Referenced in 6 articles [sw13743]
• implement MCMC algorithms in $R$ for Bayesian estimation. The corresponding R library `spatcounts’ is available ... they can be used in a Bayesian context...
• # DPpackage

• Referenced in 59 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...
• # RSGHB

• Referenced in 3 articles [sw23112]
• package RSGHB: Functions for Hierarchical Bayesian Estimation: A Flexible Approach. Functions for estimating models using ... Hierarchical Bayesian (HB) framework. The flexibility comes in allowing the user to specify the likelihood ... structures. Types of models that can be estimated with this code include the family ... Gauss code for doing Hierarchical Bayesian estimation has served as the basis...
• # dynesty

• Referenced in 3 articles [sw28387]
• Dynamic Nested Sampling Package for Estimating Bayesian Posteriors and Evidences. We present dynesty, a public ... open-source, Python package to estimate Bayesian posteriors and evidences (marginal likelihoods) using Dynamic Nested ... Carlo algorithms that focus exclusively on posterior estimation while retaining Nested Sampling’s ability...
• # BaySTDetect

• Referenced in 4 articles [sw20750]
• temporal patterns in small area data via bayesian model choice. Space-time modeling of small ... government statistical agencies for producing local estimates of, for example, unemployment or crime rates. Although ... time series of small area data using Bayesian model choice between two competing space-time ... detection method, we provide a Bayesian estimate of the false discovery rate (FDR). A comprehensive...
• # Arlequin

• Referenced in 4 articles [sw11442]
• departure from selective neutrality and demographic equilibrium, estimation or parameters from past population expansions ... files, and two new methods: a Bayesian estimation of gametic phase from multi-locus genotypes...
• # MTS

• Referenced in 4 articles [sw15485]
• series analysis, the package performs model specification, estimation, model checking, and prediction for many widely ... using diffusion index, transfer function analysis, Bayesian estimation of VAR models, and multivariate time series...
• # BITE

• Referenced in 6 articles [sw13222]
• BITE: A Bayesian Intensity Estimator. BITE is a software package designed for the analysis ... history data using flexible hierarchical models and Bayesian inference, with a particular emphasis ... parameter values stored during simulations, (ii) estimated expectations of functionals of parameters, or (iii) graphs...
• # UQLab

• Referenced in 17 articles [sw19740]
• tensor approximations), rare event estimation (structural reliability), global sensitivity analysis, Bayesian techniques for inverse problems...
• # phytools

• Referenced in 13 articles [sw10003]
• package includes functions for Bayesian and ML ancestral state estimation; visual simulation of trait evolution ... including across multiple trees (such as a Bayesian posterior sample); conducting an analysis called stochastic ... nodes and one character state per edge; estimating a phylogeny using the least squares method...