plot_mvgam_resids: Residual diagnostics for a fitted mvgam object
In mvgam: Multivariate (Dynamic) Generalized Additive Models

plot_mvgam_resids

R Documentation

Residual diagnostics for a fitted mvgam object

Description

This function takes a fitted mvgam object and returns various residual diagnostic plots

Usage

plot_mvgam_resids(object, series = 1, newdata, data_test)

Arguments

`object`	`list` object returned from `mvgam`. See `mvgam()`
`series`	`integer` specifying which series in the set is to be plotted
`newdata`	Optional `dataframe` or `list` of test data containing at least 'series', 'y', and 'time' in addition to any other variables included in the linear predictor of `formula`. If included, the covariate information in `newdata` will be used to generate forecasts from the fitted model equations. If this same `newdata` was originally included in the call to `mvgam`, then forecasts have already been produced by the generative model and these will simply be extracted and used to calculate residuals. However if no `newdata` was supplied to the original model call, an assumption is made that the `newdata` supplied here comes sequentially after the data supplied as `data` in the original model (i.e. we assume there is no time gap between the last observation of series 1 in `data_train` and the first observation for series 1 in `newdata`).
`data_test`	Deprecated. Still works in place of `newdata` but users are recommended to use `newdata` instead for more seamless integration into `R` workflows

Details

A total of four base R plots are generated to examine Dunn-Smyth residuals for the specified series. Plots include a residuals vs fitted values plot, a Q-Q plot, and two plots to check for any remaining temporal autocorrelation in the residuals. Note, all plots use posterior medians of fitted values / residuals, so uncertainty is not represented.