Get a named variance-covariance matrix from a model object
Description
Mostly for internal use, but can be useful because the output is consistent across model classes.
Usage
get_vcov(model, ...)
## Default S3 method:
get_vcov(model, vcov = NULL, ...)
## S3 method for class 'MCMCglmm'
get_vcov(model, vcov = NULL, ...)
## S3 method for class 'afex_aov'
get_vcov(model, vcov = NULL, ...)
## S3 method for class 'glimML'
get_vcov(model, vcov = NULL, ...)
## S3 method for class 'biglm'
get_vcov(model, vcov = NULL, ...)
## S3 method for class 'brmsfit'
get_vcov(model, vcov = NULL, ...)
## S3 method for class 'bart'
get_vcov(model, vcov = NULL, ...)
## S3 method for class 'gamlss'
get_vcov(model, ...)
## S3 method for class 'glmmTMB'
get_vcov(model, ...)
## S3 method for class 'mhurdle'
get_vcov(model, vcov = NULL, ...)
## S3 method for class 'Learner'
get_vcov(model, ...)
## S3 method for class 'orm'
get_vcov(model, vcov = NULL, ...)
## S3 method for class 'stpm2'
get_vcov(model, ...)
## S3 method for class 'pstpm2'
get_vcov(model, ...)
## S3 method for class 'gsm'
get_vcov(model, ...)
## S3 method for class 'aft'
get_vcov(model, ...)
## S3 method for class 'scam'
get_vcov(model, vcov = NULL, ...)
## S3 method for class 'systemfit'
get_vcov(model, ...)
## S3 method for class 'model_fit'
get_vcov(model, type = NULL, ...)
## S3 method for class 'workflow'
get_vcov(model, type = NULL, ...)
Arguments
model
|
Model object |
…
|
Additional arguments are passed to the predict() method supplied by the modeling package.These arguments are particularly useful for mixed-effects or bayesian models (see the online vignettes on the marginaleffects website). Available arguments can vary from model to model, depending on the range of supported arguments by each modeling package. See the "Model-Specific Arguments" section of the ?slopes documentation for a non-exhaustive list of available arguments.
|
vcov
|
Type of uncertainty estimates to report (e.g., for robust standard errors). Acceptable values:
|
type
|
string indicates the type (scale) of the predictions used to compute contrasts or slopes. This can differ based on the model type, but will typically be a string such as: "response", "link", "probs", or "zero". When an unsupported string is entered, the model-specific list of acceptable values is returned in an error message. When type is NULL , the first entry in the error message is used by default.
|
Value
A named square matrix of variance and covariances. The names must match the coefficient names.