#
jags
Here are 58 public repositories matching this topic...
Code that might be useful to others for learning/demonstration purposes, specifically along the lines of modeling and various algorithms.
python
r
julia
zip
matlab
irt
pca
survival-analysis
bayesian
stan
em
mixture-model
factor-analysis
gaussian-processes
jags
mixed-models
additive-models
lasso-regression
ordinal-regression
probit
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Apr 19, 2020 - R
Bayesian estimation of the finishing skill of football players
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Jan 12, 2018 - R
農研機構統計研修「ベイズ統計モデリングとMCMC」
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Nov 21, 2018 - TeX
An introduction to hierarchical Bayesian modelling with R, JAGS and STAN
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Mar 5, 2018 - R
trashbirdecology
commented
Apr 4, 2020
Although you clarify in readme that run_model() "takes a long time", the status message could use some more information. The first message I see for at least a few minutes after running this function is:
Processing function input.......
Done.
... and although the function is still processing, I see the word "Done" for some time.
I suggest improving the information in the me
Framework for conducting Bayesian analyses
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Nov 25, 2019 - R
Joint Analysis and Imputation of generalized linear models and linear mixed models with missing values
rstats
imputation
bayesian
missing-data
glm
survival
linear-mixed-models
glmm
linear-regression-models
jags
generalized-linear-models
missing-values
joint-analysis
imputations
mcmc-sample
mcmc-sampling
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Updated
Jul 7, 2020 - R
Fit multievent capture-recapture models in R (maximum-likelihood), Nimble and JAGS (Bayesian)
rstats
bayesian-inference
jags
nimble
maximum-likelihood-estimation
multistate
capture-recapture-models
multievent-models
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Updated
Dec 20, 2019 - R
Illustrate how to fit dynamic occupancy model in TMB. Benchmarking vs. ADMB, Unmarked and JAGS.
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Updated
Aug 24, 2017 - HTML
C++ libraries for Bayesian inference with interacting particle systems
c-plus-plus
particle-filter
graphical-models
bayesian-inference
smc
jags
inference-engine
bugs-language
biips
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Updated
Mar 21, 2018 - C++
R package for Bayesian inference with interacting particle systems
r
particle-filter
graphical-models
bayesian-inference
jags
mcmc-sampler
sequential-monte-carlo
inference-engine
bugs-language
biips
particle-mcmc
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Apr 16, 2018 - R
Probabilistic Matrix Factorization with JAGS in R
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Sep 13, 2017 - R
Applies Bayesian techniques for analysing various factors that can influence a UK university's graduate prospects rating from the HESA SFR247 and Complete University Guide table.
reproducible-research
linear-regression
fuzzy-matching
bayesian-methods
bayesian-inference
webscraping
bayesian-data-analysis
jags
linear-models
bayesian-statistics
markov-chain-monte-carlo
gibbs-sampling
gibbs-sampler
bayesian-analysis
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Jun 10, 2018 - R
Markov Chain Monte Carlo binary network optimization
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Mar 22, 2020 - Python
Health economic evaluations from individual level data with missing values using a set of pre-defined Bayesian models written in BUGS. A series of parametric models are available to jointly model partially-observed effectiveness and cost outcomes under both ignorable and nonignroable missing data mechanism assumptions
missing-data
health-economic-evaluation
sensitivity-analysis
jags
parametric-modelling
cost-effectiveness-analysis
individual-level-data
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Jun 25, 2020 - R
Bayesian implementation of capture-recapture models with robust design
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Apr 5, 2020 - HTML
Comparison of different implementations of the same stochastic volatility model (stochvol, JAGS, Stan)
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Mar 28, 2019 - R
Hierarchical Bayesian Models to assess Learning and Guessing Strategies in Reinforcement Learning
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Sep 24, 2018 - R
Bayesian Statistics with R [Gibbs Sampling, Metrapolis Hastings, Regression, Logistic Regression, Poisson Regression, Multi Factor Anova, Hierarchical Modelling, Mixture Models]
regression
logistic-regression
mixture-model
anova
jags
bayesian-statistics
gibbs-sampling
hierarchical-models
poisson-regression
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Updated
Oct 1, 2019 - Jupyter Notebook
Illustrate how to fit dynamic occupancy model in ADMB. Benchmarking with Unmarked and JAGS.
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Updated
Aug 21, 2017 - HTML
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It is not clear from the documentation what the intended usage is for outputs from
stan_lmorstan_lmwhere you do not have hierarchies to pass togather_draws()orspread_draws().For example, fitting a very simple model with
stan_lm():