get_gam_predictions: Get predictions from a GAM model.

In tidymv: Tidy Model Visualisation for Generalised Additive Models

Get predictions from a GAM model.

Description

This function is from the superseded package tidymv. Please, use the tidygam package instead.

It returns a tibble with the predictions from a gam or bam object.

Usage

get_gam_predictions(
  model,
  series,
  series_length = 25,
  conditions = NULL,
  exclude_random = TRUE,
  exclude_terms = NULL,
  split = NULL,
  sep = "\\.",
  time_series,
  transform = NULL,
  ci_z = 1.96,
  .comparison = NULL
)

Arguments

model	A gam or bam model object.
series	An unquoted expression indicating the model term that defines the series on which smoothing is applied. This is the term that is displayed on the x-axis when plotting.
series_length	An integer indicating how many values along the time series to use for predicting the outcome term.
conditions	A list of quosures with quos specifying the levels to plot from the model terms.
exclude_random	Whether to exclude random smooths (the default is TRUE).
exclude_terms	Terms to be excluded from the prediction. Term names should be given as they appear in the model summary (for example, "s(x0,x1)").
split	Columns to separate as a named list.
sep	Separator between columns (default is "\\.", which is the default with ). If character, it is interpreted as a regular expression.
time_series	Deprecated, use series instead.
transform	Function used to transform the fitted values (useful for getting plots on the response scale).
ci_z	The z-value for calculating the CIs (the default is 1.96 for 95 percent CI).
.comparison	Internal parameter, passed from plot_smooths().

Value

A tibble with predictions from a gam or bam model.

Examples

library(mgcv)
set.seed(10)
data <- gamSim(4)
model <- gam(y ~ fac + s(x2) + s(x2, by = fac) + s(x0), data = data)

pred <- get_gam_predictions(model, x2)

tidymv documentation built on May 31, 2023, 8:14 p.m.