Residual plots for a output model of class performs_ammi, waas, anova_ind, and anova_joint. Seven types of plots are produced: (1) Residuals vs fitted, (2) normal Q-Q plot for the residuals, (3) scale-location plot (standardized residuals vs Fitted Values), (4) standardized residuals vs Factor-levels, (5) Histogram of raw residuals and (6) standardized residuals vs observation order, and (7) 1:1 line plot
x: An object of class performs_ammi, waas, anova_joint, or gafem
var: The variable to plot. Defaults to var = 1 the first variable of x.
conf: Level of confidence interval to use in the Q-Q plot (0.95 by default).
labels: Logical argument. If TRUE labels the points outside confidence interval limits.
plot_theme: The graphical theme of the plot. Default is plot_theme = theme_metan(). For more details, see ggplot2::theme().
band.alpha, point.alpha: The transparency of confidence band in the Q-Q plot and the points, respectively. Must be a number between 0 (opaque) and 1 (full transparency).
fill.hist: The color to fill the histogram. Default is 'gray'.
col.hist: The color of the border of the the histogram. Default is 'black'.
col.point: The color of the points in the graphic. Default is 'black'.
col.line: The color of the lines in the graphic. Default is 'red'.
col.lab.out: The color of the labels for the 'outlying' points.
size.lab.out: The size of the labels for the 'outlying' points.
size.tex.lab: The size of the text in axis text and labels.
size.shape: The size of the shape in the plots.
bins: The number of bins to use in the histogram. Default is 30.
which: Which graphics should be plotted. Default is which = c(1:4) that means that the first four graphics will be plotted.
ncol, nrow: The number of columns and rows of the plot pannel. Defaults to NULL
...: Additional arguments passed on to the function patchwork::wrap_plots().
Examples
library(metan)model <- performs_ammi(data_ge, ENV, GEN, REP, GY)# Default plotplot(model)# Normal Q-Q plot# Label possible outliersplot(model, which =2, labels =TRUE)# Residual vs fitted,# Normal Q-Q plot# Histogram of raw residuals# All in one rowplot(model, which = c(1,2,5), nrow =1)