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, align = "hv", ... )
x | An object of class |
---|---|
var | The variable to plot. Defaults to |
conf | Level of confidence interval to use in the Q-Q plot (0.95 by default). |
labels | Logical argument. If |
plot_theme | The graphical theme of the plot. Default is
|
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 |
ncol, nrow | The number of columns and rows of the plot pannel. Defaults
to |
align | Specifies whether graphs in the grid should be horizontally
( |
... | Additional arguments passed on to the function
|
Tiago Olivoto tiagoolivoto@gmail.com
#> variable GY #> --------------------------------------------------------------------------- #> AMMI analysis table #> --------------------------------------------------------------------------- #> Source Df Sum Sq Mean Sq F value Pr(>F) Proportion Accumulated #> ENV 13 279.574 21.5057 62.33 0.00e+00 . . #> REP(ENV) 28 9.662 0.3451 3.57 3.59e-08 . . #> GEN 9 12.995 1.4439 14.93 2.19e-19 . . #> GEN:ENV 117 31.220 0.2668 2.76 1.01e-11 . . #> PC1 21 10.749 0.5119 5.29 0.00e+00 34.4 34.4 #> PC2 19 9.924 0.5223 5.40 0.00e+00 31.8 66.2 #> PC3 17 4.039 0.2376 2.46 1.40e-03 12.9 79.2 #> PC4 15 3.074 0.2049 2.12 9.60e-03 9.8 89 #> PC5 13 1.446 0.1113 1.15 3.18e-01 4.6 93.6 #> PC6 11 0.932 0.0848 0.88 5.61e-01 3 96.6 #> PC7 9 0.567 0.0630 0.65 7.53e-01 1.8 98.4 #> PC8 7 0.362 0.0518 0.54 8.04e-01 1.2 99.6 #> PC9 5 0.126 0.0252 0.26 9.34e-01 0.4 100 #> Residuals 252 24.367 0.0967 NA NA . . #> Total 536 389.036 0.7258 NA NA <NA> <NA> #> --------------------------------------------------------------------------- #> #> All variables with significant (p < 0.05) genotype-vs-environment interaction #> Done!# Residual vs fitted, # Normal Q-Q plot # Histogram of raw residuals # All in one row plot(model, which = c(1, 2, 5), nrow = 1)# }