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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
residual_plots(
x,
var = 1,
conf = 0.95,
labels = FALSE,
plot_theme = theme_metan(),
band.alpha = 0.2,
point.alpha = 0.8,
fill.hist = "gray",
col.hist = "black",
col.point = "black",
col.line = "red",
col.lab.out = "red",
size.lab.out = 2.5,
size.tex.lab = 10,
size.shape = 1.5,
bins = 30,
which = c(1:4),
ncol = NULL,
nrow = NULL,
...
)
An object of class performs_ammi
, waas
,
anova_joint
, or gafem
The variable to plot. Defaults to var = 1
the first
variable of x
.
Level of confidence interval to use in the Q-Q plot (0.95 by default).
Logical argument. If TRUE
labels the points outside
confidence interval limits.
The graphical theme of the plot. Default is
plot_theme = theme_metan()
. For more details, see
ggplot2::theme()
.
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).
The color to fill the histogram. Default is 'gray'.
The color of the border of the the histogram. Default is 'black'.
The color of the points in the graphic. Default is 'black'.
The color of the lines in the graphic. Default is 'red'.
The color of the labels for the 'outlying' points.
The size of the labels for the 'outlying' points.
The size of the text in axis text and labels.
The size of the shape in the plots.
The number of bins to use in the histogram. Default is 30.
Which graphics should be plotted. Default is which = c(1:4)
that means that the first four graphics will be plotted.
The number of columns and rows of the plot pannel. Defaults
to NULL
Additional arguments passed on to the function
patchwork::wrap_plots()
.
Tiago Olivoto tiagoolivoto@gmail.com
# \donttest{
library(metan)
model <- performs_ammi(data_ge, ENV, GEN, REP, GY)
# Default plot
plot(model)
# Normal Q-Q plot
# Label possible outliers
plot(model,
which = 2,
labels = TRUE)
# Residual vs fitted,
# Normal Q-Q plot
# Histogram of raw residuals
# All in one row
plot(model,
which = c(1, 2, 5),
nrow = 1)
# }
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