Package: badp 0.4.0.1

Marcin Dubel

badp: Bayesian Averaging for Dynamic Panels

Implements Bayesian model averaging for dynamic panels with weakly exogenous regressors as described in the paper by Moral-Benito (2013, <doi:10.1080/07350015.2013.818003>). The package provides functions to estimate dynamic panel data models and analyze the results of the estimation.

Authors:Krzysztof Beck [aut], Piotr Cukier [aut], Marcin Dubel [aut, cre], Mariusz Szczepanczyk [aut], Mateusz Wyszynski [aut]

badp_0.4.0.1.tar.gz
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manual.pdf |manual.html✨
card.svg |card.png
badp/json (API)
NEWS

# Install 'badp' in R:
install.packages('badp', repos = c('https://badp-project.r-universe.dev', 'https://cloud.r-project.org'))

Bug tracker:https://github.com/badp-project/badp/issues

Uses libs:
  • openblas– Optimized BLAS
  • c++– GNU Standard C++ Library v3
Datasets:

On CRAN:

Conda:

openblascpp

4.60 score 4 scripts 609 downloads 30 exports 43 dependencies

Last updated from:9184f75354. Checks:13 OK. Indexed: yes.

TargetResultTimeFilesSyslog
linux-devel-arm64OK185
linux-devel-x86_64OK178
source / vignettesOK244
linux-release-arm64OK174
linux-release-x86_64OK182
macos-release-arm64OK200
macos-release-x86_64OK296
macos-oldrel-arm64OK237
macos-oldrel-x86_64OK232
windows-develOK155
windows-releaseOK181
windows-oldrelOK146
wasm-releaseOK144

Exports:best_modelsbmacoef_histcompute_model_space_statsexogenous_matrixextract_namesfeature_standardizationhessianinit_model_space_paramsjoin_lagged_coljointnessmatrices_from_dfmodel_pmpmodel_sizesnested_optimization_wrappernested_std_dev_from_paramsnon_nested_optimization_wrappernon_nested_std_dev_from_paramsoptim_model_spaceoptim_model_space_paramsposterior_densregressor_names_from_params_vectorresidual_maker_matrixsem_B_matrixsem_C_matrixsem_dep_var_matrixsem_likelihoodsem_psi_matrixsem_regressors_matrixsem_sigma_matrix

Dependencies:clicpp11dplyrevaluatefarvergenericsggplot2gluegridExtragtablehighrisobandknitrlabelinglatticelifecyclemagrittrMatrixoptimbasepbapplypillarpkgconfigpurrrR6RColorBrewerRcppRcppArmadillorjerlangrootSolveS7scalesstringistringrtibbletidyrtidyselectutf8vctrsviridisLitewithrxfunyaml

badp: Bayesian model averaging for dynamic panels with weakly exogenous regressors

Krzysztof Beck^1,2^, Piotr Cukier^2^, Marcin Dubel^2^, Mariusz Szczepańczyk^2^, Mateusz Wyszyński^3^

Rendered frombadp_vignette.Rmdusingknitr::rmarkdownon Jun 01 2026.

Last update: 2026-03-30
Started: 2026-03-30

Readme and manuals

Help Manual

Help pageTopics
Table with the best models according to one of the posterior criteriabest_models
Calculation of the bma objectbma
Graphs of the distribution of the coefficients over the model spacecoef_hist
Approximate standard deviations for the modelscompute_model_space_stats
Economic Growth Dataeconomic_growth
Matrix with exogenous variables for SEM representationexogenous_matrix
Extraction of names of the variablesextract_names
Perform feature standardizationfeature_standardization
Example output of the bma functionfull_bma_results
Example output of 'optim_model_space'full_model_space
Hessian matrixhessian
Initialize model space matrixinit_model_space_params
Dataframe with no lagged columnjoin_lagged_col
Calculation of of the jointness measuresjointness
List of matrices for SEM modelmatrices_from_df
Graphs of the prior and posterior model probabilities for the best individual modelsmodel_pmp
Graphs of the prior and posterior model probabilities of the model sizesmodel_sizes
Example output of 'optim_model_space' for non-nested modelsmodel_space_nonnested
Helper-function - finds parameters minimizing log-likelihood function for the nested version of the SEM setup, using BFGS methodnested_optimization_wrapper
Helper function - wraps single execution of the log-likelihood & deviation parameters calculations. Used for non nested version of SEM likelihood.nested_std_dev_from_params
Helper-function - finds parameters minimizing log-likelihood function for the non-nested version of the SEM setup, using BFGS methodnon_nested_optimization_wrapper
Helper function - wraps single execution of the log-likelihood & deviation parameters calculations. Used for non nested version of SEM likelihood.non_nested_std_dev_from_params
Calculation of the model_space objectoptim_model_space
Finds MLE parameters for each model in the given model spaceoptim_model_space_params
Economic Growth Data in the original formatoriginal_economic_growth
Graphs of the posterior densities of the coefficientsposterior_dens
Helper function to extract names from a vector defining a modelregressor_names_from_params_vector
Residual Maker Matrixresidual_maker_matrix
Coefficients matrix for SEM representationsem_B_matrix
Coefficients matrix for initial conditionssem_C_matrix
Matrix with dependent variable data for SEM representationsem_dep_var_matrix
Likelihood for the SEM modelsem_likelihood
Matrix with psi parameters for SEM representationsem_psi_matrix
Matrix with regressors data for SEM representationsem_regressors_matrix
Covariance matrix for SEM representationsem_sigma_matrix
Example output of 'optim_model_space' (small version)small_model_space