Broom-style table methods for fitted longitudinal GAMLSS models — gamlss_longitudinal_table

These methods expose fitted gamlss.longitudinal objects in the table shapes expected by reporting packages. tidy() returns fixed-coefficient summaries, glance() returns one-row model-fit summaries, and augment() returns row-level fitted values and residuals.

Usage

# S3 method for class 'gamlss.longitudinal'
tidy(
  x,
  conf.int = TRUE,
  conf.level = 0.95,
  parameter = NULL,
  include_vcov = TRUE,
  vcov_method = "analytical",
  ...
)

# S3 method for class 'gamlss.longitudinal'
glance(x, include_vcov = FALSE, vcov_method = "analytical", ...)

# S3 method for class 'gamlss.longitudinal'
augment(
  x,
  data = NULL,
  newdata = NULL,
  type = c("mean", "mu", "median"),
  residual_type = c("response", "pearson", "quantile"),
  se.fit = FALSE,
  interval = c("none", "confidence"),
  level = 0.95,
  vcov_method = "analytical",
  ...
)

Arguments

x: A fitted gamlss.longitudinal object.
conf.int: Logical; include Wald confidence intervals for coefficients.
conf.level: Confidence level for intervals.
parameter: Optional distributional parameter(s) to retain.
include_vcov: Logical; compute or reuse variance-covariance output.
vcov_method: Variance-covariance method passed to summary.gamlss.longitudinal().
...: Additional arguments passed to downstream methods.
data: Optional data frame to augment. Defaults to the fitted expanded model frame.
newdata: Optional new data to augment. When supplied, residuals are only added if a response column is present.
type: Prediction type passed to predict.gamlss.longitudinal().
residual_type: Residual type used when augmenting fitted rows.
se.fit: Logical; include prediction standard errors when supported.
interval: Interval type passed to predict.gamlss.longitudinal().
level: Confidence level for prediction intervals.

Value

A data frame.