bdsm (version 0.3.0)

bma: Calculation of the bma object

Description

This function calculates BMA statistics based on the provided model space. Other objects for furhter analysis are also returned.

Usage

bma(model_space, df, round = 4, EMS = NULL, dilution = 0, dil.Par = 0.5)

Value

A list with 16 elements.

uniform_table

A table containing the results based on the binomialmodel prior.

random_table

A table containing the results based on the binomial-beta model prior.

reg_names

A vector containing the names of the regressors, used by the functions.

R

The total number of regressors.

num_of_models

The number of models present in the model space.

forJointnes

A table containing model IDs and posterior model probabilities (PMPs) for the jointness function.

forBestModels

A table containing model IDs, PMPs, coefficients, standard deviations,and standardized regression coefficients (stdRs) for the best_models function.

EMS

The expected model size for the binomial and binomial-beta model priors, as specified by the user (default is EMS = R/2).

sizePriors

A table of uniform and random model priors distributed over model sizes for the model_sizes function.

PMPs

A table containing the posterior model probabilities for use in the model_sizes function.

modelPriors

A table containing the model priors, used by the model_pmp function.

dilution

A parameter indicating whether the priors were diluted, used in the model_sizes function.

alphas

A vector of coefficients for the lagged dependent variable in the coef_hist function.

betas_nonzero

A vector of nonzero coefficients for the regressors in the coef_hist function.

d_free

A table containing the degrees of freedom for the estimated models in the best_models function.

PMStable

A table containing the prior and posterior expected model sizes for the binomial and binomial-beta model priors.

Arguments

model_space

List with params and stats from the model space

df

Data frame with data for the SEM analysis.

round

Parameter indicating the decimal place to which number in the BMA tables and prior and posterior model sizes should be rounded (default round = 4)

EMS

Expected model size for model binomial and binomial-beta model prior

dilution

Binary parameter: 0 - NO application of a dilution prior; 1 - application of a dilution prior (George 2010).

dil.Par

Parameter associated with dilution prior - the exponent of the determinant (George 2010). Used only if parameter dilution = 1.

Examples

# \donttest{
library(magrittr)

data_prepared <- bdsm::economic_growth[, 1:6] %>%
  bdsm::feature_standardization(
    excluded_cols = c(country, year, gdp)
  ) %>%
  bdsm::feature_standardization(
    group_by_col  = year,
    excluded_cols = country,
    scale         = FALSE
  )

bma_results <- bma(
  model_space = bdsm::small_model_space,
  df          = data_prepared,
  round       = 3,
  dilution    = 0
)
# }