overview {gratia}

Provides an overview of a model and the terms in that model

Description

Provides an overview of a model and the terms in that model

Usage

overview(model, ...)

## S3 method for class 'gam'
overview(
  model,
  parametric = TRUE,
  random_effects = TRUE,
  dispersion = NULL,
  frequentist = FALSE,
  accuracy = 0.001,
  stars = FALSE,
  ...
)

Arguments

model

a fitted model object to overview.

...

arguments passed to other methods.

parametric

logical; include the model parametric terms in the overview?

random_effects

tests of fully penalized smooth terms (those with a zero-dimensional null space, e.g. random effects) are computationally expensive and for large data sets producing these p values can take a very long time. If random_effects = FALSE, the tests of the expensive terms will be skipped.

dispersion

numeric; a known value for the dispersion parameter. The default NULL implies that the estimated value or the default value (1 for the Poisson distribution for example) where this is specified is used instead.

frequentist

logical; by default the Bayesian estimated covariance matrix of the parameter estimates is used to calculate p values for parametric terms. If frequentist = FALSE, the frequentist covariance matrix of the parameter estimates is used.

accuracy

numeric; accuracy with which to report p values, with p values below this value displayed as "< accuracy".

stars

logical; should significance stars be added to the output?

Examples

load_mgcv()

df <- data_sim(n = 400, seed = 2)
m <- gam(y ~ x3 + s(x0) + s(x1, bs = "bs") + s(x2, bs = "ts"),
  data = df, method = "REML"
)
overview(m)