Model diagnostic plots

Model diagnostic plots

Usage

appraise(model, ...)

# S3 method for class 'gam'
appraise(
  model,
  method = NULL,
  use_worm = FALSE,
  n_uniform = 10,
  n_simulate = 50,
  seed = NULL,
  type = c("deviance", "pearson", "response"),
  n_bins = c("sturges", "scott", "fd"),
  ncol = NULL,
  nrow = NULL,
  guides = "keep",
  level = 0.9,
  ci_col = "black",
  ci_alpha = 0.2,
  point_col = "grey20",
  point_alpha = 1,
  line_col = "red",
  ...
)

# S3 method for class 'lm'
appraise(model, ...)

Arguments

model

a fitted model. Currently models inheriting from class "gam", as well as classes "glm" and "lm" from calls to stats::glm or stats::lm are supported.

...

arguments passed to patchwork::wrap_plots().

method

character or NULL; method used to generate theoretical quantiles. The default, NULL, selects "simulate" for models fitted with mgcv::tw() or mgcv::Tweedie() and "uniform" otherwise. Explicitly supplying a method overrides this selection, subject to availability of the required family functions. "uniform" generates reference quantiles using random draws from a uniform distribution and the inverse cumulative distribution function (CDF) of the fitted values. The reference quantiles are averaged over n_uniform draws. "simulate" generates reference quantiles by simulating new response data from the model at the observed values of the covariates, which are then residualised to generate reference quantiles, using n_simulate simulated data sets. "normal" generates reference quantiles using the standard normal distribution. "uniform" is often more computationally efficient, but Tweedie quantiles are expensive to compute. "simulate" allows reference bands to be drawn on the QQ-plot. "normal" should be avoided but is used as a fall back if a random number generator ("simulate") or the inverse of the CDF ("uniform") are not available from the family used during model fitting.

Note that method = "direct" is deprecated in favour of method = "uniform".

use_worm

logical; should a worm plot be drawn in place of the QQ plot?

n_uniform

numeric; number of times to randomize uniform quantiles in the direct computation method (method = "direct") for QQ plots.

n_simulate

numeric; number of data sets to simulate from the estimated model when using the simulation method (method = "simulate") for QQ plots.

seed

numeric; the random number seed to use for method = "simulate" and method = "uniform".

type

character; type of residuals to use. Only "deviance", "response", and "pearson" residuals are allowed.

n_bins

character or numeric; either the number of bins or a string indicating how to calculate the number of bins.

ncol, nrow

numeric; the numbers of rows and columns over which to spread the plots.

guides

character; one of "keep" (the default), "collect", or "auto". Passed to patchwork::plot_layout()

level

numeric; the coverage level for QQ plot reference intervals. Must be strictly 0 < level < 1. Only used with method = "simulate".

ci_alpha, ci_col

colour and transparency used to draw the QQ plot reference interval when method = "simulate".

point_col, point_alpha

colour and transparency used to draw points in the plots. See graphics::par() section Color Specification. This is passed to the individual plotting functions, and therefore affects the points of all plots.

line_col

colour specification for the 1:1 line in the QQ plot and the reference line in the residuals vs linear predictor plot.

Note

The wording used in mgcv::qq.gam() uses direct in reference to the simulated residuals method (method = "simulated"). To avoid confusion, method = "direct" is deprecated in favour of method = "uniform".

See also

The plots are produced by functions qq_plot(), residuals_linpred_plot(), residuals_hist_plot(), and observed_fitted_plot().

Examples

load_mgcv()
## simulate some data...
dat <- data_sim("eg1", n = 400, dist = "normal", scale = 2, seed = 2)
mod <- gam(y ~ s(x0) + s(x1) + s(x2) + s(x3), data = dat)
## run some basic model checks
appraise(mod, point_col = "steelblue", point_alpha = 0.4)


## To change the theme for all panels use the & operator, for example to
## change the ggplot theme for all panels
library("ggplot2")
if (packageVersion("ggplot2") <= "3.5.2") {
  # Throws warning with ggplot rc 4.0.0 and patchwork 1.3.1 - will be fixed
  # in patchwork 1.3.2 - so temporarily skipping during ggplot release
  # process
  appraise(mod, seed = 42,
    point_col = "steelblue", point_alpha = 0.4,
    line_col = "black"
  ) & theme_minimal()
}