Bayesian Dynamic Systems Modeling

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Documentation for package ‘bdsm’ version 0.1.0

• DESCRIPTION file.
• Package NEWS.

Help Pages

bma_summary	Summary of a model space
economic_growth	Economic Growth Data
economic_growth_bma_params	Example Approximate Summary of Parameters of Interest Based on Model Space
economic_growth_liks	Example Approximate Likelihoods Summary based on Model Space
economic_growth_ms	Example Model Space
economic_growth_ms_full_proj_const	Full Model Space with Constant Projection Matrix
economic_growth_ms_full_proj_var	Full Model Space with Varying Projection Matrix
exogenous_matrix	Matrix with exogenous variables for SEM representation
feature_standardization	Perform feature standarization
hessian	Hessian matrix
initialize_model_space	Initialize model space matrix
join_lagged_col	Dataframe with no lagged column
likelihoods_summary	Approximate standard deviations for the models
matrices_from_df	List of matrices for SEM model
optimal_model_space	Finds MLE parameters for each model in the given model space
parameters_summary	BMA summary for parameters of interest
regressor_names_from_params_vector	Helper function to extract names from a vector defining a model
residual_maker_matrix	Residual Maker Matrix
SEM_B_matrix	Coefficients matrix for SEM representation
SEM_C_matrix	Coefficients matrix for initial conditions
SEM_dep_var_matrix	Matrix with dependent variable data for SEM representation
SEM_likelihood	Likelihood for the SEM model
SEM_psi_matrix	Matrix with psi parameters for SEM representation
SEM_regressors_matrix	Matrix with regressors data for SEM representation
SEM_sigma_matrix	Covariance matrix for SEM representation