Tidy summarizes information about the components of a model.
A model component might be a single term in a regression, a single
hypothesis, a cluster, or a class. Exactly what tidy considers to be a
model component varies cross models but is usually self-evident.
If a model has several distinct types of components, you will need to
specify which components to return.
Usage
# S3 method for gamlss
tidy(x, quick = FALSE, ...)
Logical indiciating if the only the term and estimate
columns should be returned. Often useful to avoid time consuming
covariance and standard error calculations. Defaults to FALSE.
...
Additional arguments. Not used. Needed to match generic
signature only. Cautionary note: Misspelled arguments will be
absorbed in ..., where they will be ignored. If the misspelled
argument has a default value, the default value will be used.
For example, if you pass conf.lvel = 0.9, all computation will
proceed using conf.level = 0.95. Additionally, if you pass
newdata = my_tibble to an augment() method that does not
accept a newdata argument, it will use the default value for
the data argument.
Value
A tibble::tibble with one row for each coefficient, containing columns
parameter
Type of coefficient being estimated: mu, sigma,
nu, or tau.
term
Name of term in the model.
estimate
Estimate coefficient of given term.
std.error
Standard error of given term.
statistic
T-statistic used to test hypothesis that coefficien
equals zero.
p.value
Two sided p-value based on null hypothesis of coefficient
equaling zero.