p_rope {bayestestR} R Documentation

## 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))
```

[Package bayestestR version 0.10.0 Index]