plot.probsup {ProbBreed} | R Documentation |
probsup
objectBuild plots using the outputs stored in the probsup
object.
## S3 method for class 'probsup'
plot(x, ..., category = "perfo", level = "across")
x |
An object of class |
... |
currently not used |
category |
A string indicating which plot to build. See options in the Details section. |
level |
A string indicating the information level to be used for building
the plots. Options are |
The available options are:
hpd
: a caterpillar plot representing the marginal genotypic value of
each genotype, and their respective highest posterior density interval (95% represented by the
thick line, and 97.5% represented by the thin line). Available only if level = "across"
.
perfo
: if level = "across"
, a lollipop plot illustrating the probabilities of superior performance.
If level = "within"
, a heatmap with the probabilities of superior performance within
environments. If a model with reg
and/or year
is fitted, multiple plots are produced.
stabi
: a lollipop plot with the probabilities of superior stability.
If a model with reg
and/or year
is fitted, multiple plots are produced.
Available only if level = "across"
.
pair_perfo
: if level = "across"
, a heatmap representing the pairwise probability of superior
performance (the probability of genotypes at the x-axis being superior
to those on the y-axis). If level = "within"
, a list of heatmaps representing the pairwise probability of superior
performance within environments. If a model with reg
and/or year
is fitted, multiple plots (and multiple lists) are produced.
Should this option is set, it is mandatory to store the outputs in an object
(e.g., pl <- plot(obj, category = "pair_perfo", level = "within")
) so they can be visualized one at a time.
pair_stabi
: a heatmap with the pairwise probabilities of superior stability
(the probability of genotypes at the x-axis being more stable than those on the y-axis).
If a model with reg
and/or year
is fitted, multiple plots are produced. Available only if level = "across"
.
joint
: a lollipop plot with the joint probabilities of superior performance and stability.
mod = bayes_met(data = soy,
gen = "Gen",
loc = "Loc",
repl = NULL,
year = NULL,
reg = NULL,
res.het = FALSE,
trait = 'Y',
iter = 6000, cores = 4, chains = 4)
outs = extr_outs(model = mod,
probs = c(0.05, 0.95),
verbose = TRUE)
results = prob_sup(extr = outs,
int = .2,
increase = TRUE,
save.df = FALSE,
verbose = FALSE)
plot(results, category = "hpd")
plot(results, category = "perfo", level = "across")
plot(results, category = "perfo", level = "within")
plot(results, category = "stabi")
plot(results, category = "pair_perfo", level = "across")
plwithin = plot(results, category = "pair_perfo", level = "within")
plot(results, category = "pair_stabi")
plot(results, category = "joint")