qq_plot | R Documentation |
Quantile-quantile plot of model residuals
qq_plot(model, ...) ## Default S3 method: qq_plot(model, ...) ## S3 method for class 'gam' qq_plot( model, method = c("uniform", "simulate", "normal", "direct"), type = c("deviance", "response", "pearson"), n_uniform = 10, n_simulate = 50, level = 0.9, ylab = NULL, xlab = NULL, title = NULL, subtitle = NULL, caption = NULL, ci_col = "black", ci_alpha = 0.2, point_col = "black", point_alpha = 1, line_col = "red", ... ) ## S3 method for class 'glm' qq_plot(model, ...) ## S3 method for class 'lm' qq_plot(model, ...)
model |
a fitted model. Currently only class |
... |
arguments passed ot other methods. |
method |
character; method used to generate theoretical quantiles. Note
that |
type |
character; type of residuals to use. Only |
n_uniform |
numeric; number of times to randomize uniform quantiles
in the direct computation method ( |
n_simulate |
numeric; number of data sets to simulate from the estimated
model when using the simulation method ( |
level |
numeric; the coverage level for reference intervals. Must be
strictly |
ylab |
character or expression; the label for the y axis. If not supplied, a suitable label will be generated. |
xlab |
character or expression; the label for the y axis. If not supplied, a suitable label will be generated. |
title |
character or expression; the title for the plot. See
|
subtitle |
character or expression; the subtitle for the plot. See
|
caption |
character or expression; the plot caption. See
|
ci_col, ci_alpha |
fill colour and alpha transparency for the reference
interval when |
point_col, point_alpha |
colour and alpha transparency for points on the QQ plot. |
line_col |
colour used to draw the reference line. |
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"
.
load_mgcv() ## simulate binomial data... dat <- data_sim("eg1", n = 200, dist = "binary", scale = .33, seed = 0) p <- binomial()$linkinv(dat$f) # binomial p n <- sample(c(1, 3), 200, replace = TRUE) # binomial n dat <- transform(dat, y = rbinom(n, n, p), n = n) m <- gam( y / n ~ s(x0) + s(x1) + s(x2) + s(x3), family = binomial, data = dat, weights = n, method = "REML") ## Q-Q plot; default using direct randomization of uniform quantiles qq_plot(m) ## Alternatively use simulate new data from the model, which ## allows construction of reference intervals for the Q-Q plot qq_plot(m, method = "simulate", point_col = "steelblue", point_alpha = 0.4) ## ... or use the usual normality assumption qq_plot(m, method = "normal")
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