read_bma_all: Read and consolidate BMA weight tables

In bivarhr: Bivariate Hurdle Regression with Bayesian Model Averaging

Read and consolidate BMA weight tables

Description

Searches for BMA weight CSV files produced by the Hurdle-NB model, reads them using automatic delimiter detection, and returns a single stacked data frame with normalized column names and a combo identifier.

Usage

read_bma_all(dir_csv, dir_out, stop_if_empty = TRUE, verbose = TRUE)

Arguments

dir_csv	Character scalar; directory where BMA CSV files are expected (for example "bma_weights_specC_ctrl*.csv").
dir_out	Character scalar; output directory used during the experiment, which may contain BMA files or a fallback RDS object.
stop_if_empty	Logical; if TRUE, an informative error is thrown when no valid BMA tables are found. If FALSE, a warning is issued and an empty tibble is returned.
verbose	Logical; if TRUE, prints diagnostic messages about the search paths, files found, and detected ELPD column.

Details

The function:

• Looks for CSV files matching the pattern "bma_weights_specC_ctrl*.csv" in dir_csv, and if none are found, searches recursively in dir_out.

• Reads each candidate file via rc_auto() and keeps only non-empty data frames.

• If no CSV files are usable, optionally falls back to an RDS file "experimento_mejorado_all.rds" under dir_out and tries to extract BMA tables from allobj$bma.

• Normalizes column names with normalize_names(), ensures a combo column exists, detects the ELPD column, and sorts rows by decreasing ELPD.

Value

A data frame with all BMA tables stacked and an added combo_id column (source identifier) and a combo column (control combo). If nothing is found and stop_if_empty = FALSE, an empty tibble is returned.

bivarhr documentation built on July 7, 2026, 1:06 a.m.