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bayestestR (version 0.8.0)

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, ...)

# S3 method for default p_rope(x, ...)

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

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

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

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

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

# S3 method for stanreg p_rope( x, range = "default", effects = c("fixed", "random", "all"), parameters = NULL, ... )

# S3 method for 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 a vector of length two (e.g., c(-0.1, 0.1)) or "default". If "default", the range is set to c(-0.1, 0.1) if input is a vector, and based on rope_range() if a Bayesian model is provided.

effects

Should results for fixed effects, random effects or both be returned? Only applies to mixed models. May be abbreviated.

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.

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.

Examples

Run this code
# NOT RUN {
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))
# }

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