best_models: Table with the best models according to one of the posterior...

In bdsm: Bayesian Dynamic Systems Modeling

Table with the best models according to one of the posterior criteria

Description

This function creates a ranking of best models according to one of the possible criterion (PMP under binomial model prior, PMP under binomial-beta model prior, R^2 under binomial model prior, R^2 under binomial-beta model prior). The function gives two types of tables in three different formats: inclusion table (where 1 indicates presence of the regressor in the model and 0 indicates that the variable is excluded from the model) and estimation results table (it displays the best models and estimation output for those models: point estimates, standard errors, significance level, and R^2).

Usage

best_models(
  bma_list,
  criterion = 1,
  best = 5,
  app = 3,
  estimate = TRUE,
  robust = TRUE
)

Arguments

bma_list	bma object (the result of the bma function)
criterion	The criterion that will be used for a basis of the model ranking: 1 - binomial model prior 2 - binomial-beta model prior
best	The number of the best models to be considered
app	Parameter indicating the decimal place to which number in the tables should be rounded (default app = 3)
estimate	A parameter with values TRUE or FALSE indicating which table should be displayed when the function finishes calculations. Works well when best is small. TRUE - table with estimation to the results FALSE - table with the inclusion of regressors in the best models
robust	A parameter with values TRUE or FALSE indicating which type of stanrdard errors should be displayed when the function finishes calculations. Works only if estimate = TRUE. Works well when best is small. TRUE - robust standard errors FALSE - regular standard errors

Value

A list with best_models objects:

1. matrix with inclusion of the regressors in the best models
   

2. matrix with estimation output in the best models with regular standard errors
   

3. matrix with estimation output in the best models with robust standard errors
   

4. knitr_kable table with inclusion of the regressors in the best models (the best for the display on the console - up to 11 models)
   

5. knitr_kable table with estimation output in the best models with regular standard errors (the best for the display on the console - up to 6 models)
   

6. knitr_kable table with estimation output in the best models with robust standard errors (the best for the display on the console - up to 6 models)
   

7. gTree table with inclusion of the regressors in the best models (displayed as a plot). Use grid::grid.draw() to display.
   

8. gTree table with estimation output in the best models with regular standard errors (displayed as a plot). Use grid::grid.draw() to display.

9. gTree table with estimation output in the best models with robust standard errors (displayed as a plot). Use grid::grid.draw() to display.

Examples

library(magrittr)

data_prepared <- economic_growth[,1:7] %>%
   feature_standardization(timestamp_col = year, entity_col = country) %>%
   feature_standardization(timestamp_col = year, entity_col = country,
                           time_effects = TRUE, scale = FALSE)

model_space <- optimal_model_space(df = data_prepared, dep_var_col = gdp,
                                   timestamp_col = year, entity_col = country,
                                   init_value = 0.5)

bma_results <- bma(df = data_prepared, dep_var_col = gdp, timestamp_col = year,
entity_col = country, model_space = model_space, run_parallel = FALSE, dilution = 0)

best_5_models <- best_models(bma_results, criterion = 1, best = 5, estimate = TRUE, robust = TRUE)

bdsm documentation built on April 4, 2025, 1:06 a.m.