R: Precision for the k Best-Performing Models

best_models {MCMCprecision} | R Documentation

## Precision for the k Best-Performing Models

### Description

Assesses the precision in estimating the ranking of the k best-performing models.

### Usage

    best_models(samples, k, ties.method = "min")

### Arguments

`samples` | a matrix with posterior samples (one per row) for the model posterior probabilities (one model per column). Can be estimated using `stationary` with the argument `summary = FALSE`.
`k` | number of best-performing models to be considered
`ties.method` | a character string specifying how ties are treated, see `rank`

### Examples

    # a sequence of uncorrelated model indices
    mult <- rmultinom(1000, 1, c(.05, .6, .15, .12, .08))
    idx <- apply(mult, 2, which.max)
    z <- letters[idx]
    stat <- stationary(z, summary = FALSE)
    best_models(stat, 3)

[Package MCMCprecision version 0.3.9 Index]