Alternatives and similar repositories for BDA_m_demos

Users that are interested in BDA_m_demos are comparing it to the libraries listed below

• brian-lau / MatlabStan
  Matlab interface to Stan, a package for Bayesian inference
  ☆83Updated 2 years ago
• gpstuff-dev / gpstuff
  GPstuff - Gaussian process models for Bayesian analysis
  ☆175Updated 2 years ago
• msalibian / RobStatTM
  Companion package to the 2nd edition of the book "Robust Statistics: Theory and Methods"
  ☆18Updated 4 months ago
• sinhrks / stan-statespace
  Stan models for state space time series
  ☆145Updated 8 years ago
• compops / pmh-tutorial
  Source code and data for the tutorial: "Getting started with particle Metropolis-Hastings for inference in nonlinear models"
  ☆28Updated 6 years ago
• fonnesbeck / stan_workshop_2016
  Bayesian Modeling using Stan in R (May/June 2016)
  ☆54Updated 9 years ago
• glmgen / glmgen
  Generalized lasso implementations
  ☆46Updated 9 months ago
• jasonge27 / picasso
  Penalized Sparse Learning Solver - Unleash the Power of Nonconvex Penalty
  ☆76Updated 3 years ago
• boboppie / kruschke-doing_bayesian_data_analysis
  John K. Kruschke's Doing Bayesian Data Analysis: A Tutorial with R and BUGS
  ☆117Updated 8 years ago
• avehtari / modelselection
  Case studies on model assessment, model selection and inference after model selection
  ☆170Updated last year
• ryantibs / best-subset
  Comparisons between best subset selection and other popular sparse regression estimators
  ☆86Updated last year
• VBayesLab / deepGLM
  Train deepGLM with Matlab, R and Python
  ☆27Updated 2 years ago
• stablemarkets / BayesianTutorials
  Implementing MCMC sampling from scratch in R for various Bayesian models
  ☆109Updated last year
• avehtari / PSIS
  Pareto smoothed importance sampling (PSIS) and PSIS leave-one-out cross-validation for Python and Matlab/Octave
  ☆77Updated last year
• milkha / Splines_in_Stan
  Implementation of B-Splines in Stan
  ☆51Updated 7 years ago
• functionaldata / PACE_matlab
  ☆15Updated 2 years ago
• erichson / spca
  Sparse Principal Component Analysis (SPCA) using Variable Projection
  ☆68Updated 7 years ago
• junpenglao / GLMM-in-Python
  Generalized linear mixed-effect model in Python
  ☆180Updated 6 years ago
• betanalpha / stan_intro
  Draft introduction to probability and inference aimed at the Stan manual.
  ☆86Updated 9 years ago
• kingaa / pomp
  R package for statistical inference using partially observed Markov processes
  ☆116Updated last month
• stochasticresearch / copulastatistic
  All code related to the paper: "A Copula Statistic for Measuring Nonlinear Multivariate Dependence"
  ☆12Updated 3 years ago
• airoldilab / sgd
  An R package for large scale estimation with stochastic gradient descent
  ☆62Updated last year
• helske / seqHMM
  Multivariate and Multichannel Discrete Hidden Markov Models for Categorical Sequences
  ☆100Updated 2 weeks ago
• jhoupt / DBDA2Estan
  Stan implementations of models in Doing Bayesian Data Analysis, 2nd Edition
  ☆68Updated 7 years ago
• betanalpha / knitr_case_studies
  Inference case studies in knitr
  ☆167Updated 2 years ago
• junpenglao / All-that-likelihood-with-PyMC3
  ☆73Updated 6 years ago
• yc-ning / Bayesian-multivariate-time-series-causal-inference
  R code for ''Bayesian method for causal inference in spatially-correlated multivariate time series''
  ☆46Updated 4 years ago
• jrnold / ssmodels-in-stan
  State space models (dynamic linear models, hidden Markov models) implemented in Stan.
  ☆47Updated 7 years ago
• florianhartig / LearningBayes
  An introduction to Bayesian statistics
  ☆73Updated last year
• ayakubovich / EM
  Getting started with the Expectation Maximization algorithm, Mixture Models and Hidden Markov Models
  ☆18Updated 10 years ago