bayestestR: p_rope – R documentation

Become an expert in R — Interactive courses, Cheat Sheets, certificates and more!

p_rope

Probability of being in the ROPE

Description

Compute the proportion of the whole posterior distribution that doesn't lie within a region of practical equivalence (ROPE). It is equivalent to running rope(..., ci = 1).

Usage

p_rope(x, ...)

## Default S3 method:
p_rope(x, ...)

## S3 method for class 'numeric'
p_rope(x, range = "default", ...)

## S3 method for class 'data.frame'
p_rope(x, range = "default", ...)

## S3 method for class 'emmGrid'
p_rope(x, range = "default", ...)

## S3 method for class 'BFBayesFactor'
p_rope(x, range = "default", ...)

## S3 method for class 'MCMCglmm'
p_rope(x, range = "default", ...)

## S3 method for class 'stanreg'
p_rope(
  x,
  range = "default",
  effects = c("fixed", "random", "all"),
  component = c("location", "all", "conditional", "smooth_terms", "sigma",
    "distributional", "auxiliary"),
  parameters = NULL,
  ...
)

## S3 method for class 'brmsfit'
p_rope(
  x,
  range = "default",
  effects = c("fixed", "random", "all"),
  component = c("conditional", "zi", "zero_inflated", "all"),
  parameters = NULL,
  ...
)

Arguments

`x`	Vector representing a posterior distribution. Can also be a `stanreg` or `brmsfit` model.
`...`	Currently not used.
`range`	ROPE's lower and higher bounds. Should be `"default"` or depending on the number of outcome variables a vector or a list. In models with one response, 'range' should be a vector of length two (e.g., `c(-0.1, 0.1)`). In multivariate models, 'range' should be a list with a numeric vectors for each response variable. Vector names should correspond to the name of the response variables. If `"default"` and input is a vector, the range is set to `c(-0.1, 0.1)`. If `"default"` and input is a Bayesian model, `rope_range()` is used.
`effects`	Should results for fixed effects, random effects or both be returned? Only applies to mixed models. May be abbreviated.
`component`	Should results for all parameters, parameters for the conditional model or the zero-inflated part of the model be returned? May be abbreviated. Only applies to brms-models.
`parameters`	Regular expression pattern that describes the parameters that should be returned. Meta-parameters (like `lp__` or `prior_`) are filtered by default, so only parameters that typically appear in the `summary()` are returned. Use `parameters` to select specific parameters for the output.

Examples

library(bayestestR)

p_rope(x = rnorm(1000, 0, 0.01), range = c(-0.1, 0.1))
p_rope(x = mtcars, range = c(-0.1, 0.1))

bayestestR

Understand and Describe Bayesian Models and Posterior Distributions

v0.10.0

GPL-3

Authors

Dominique Makowski [aut, cre] (<https://orcid.org/0000-0001-5375-9967>, @Dom_Makowski), Daniel Lüdecke [aut] (<https://orcid.org/0000-0002-8895-3206>, @strengejacke), Mattan S. Ben-Shachar [aut] (<https://orcid.org/0000-0002-4287-4801>, @mattansb), Indrajeet Patil [aut] (<https://orcid.org/0000-0003-1995-6531>, @patilindrajeets), Michael D. Wilson [aut] (<https://orcid.org/0000-0003-4143-7308>), Paul-Christian Bürkner [rev], Tristan Mahr [rev] (<https://orcid.org/0000-0002-8890-5116>), Henrik Singmann [ctb] (<https://orcid.org/0000-0002-4842-3657>), Quentin F. Gronau [ctb] (<https://orcid.org/0000-0001-5510-6943>), Sam Crawley [ctb] (<https://orcid.org/0000-0002-7847-0411>)

Initial release