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Inspect residuals of regression models.
check_resid(model, AR_start = NULL, split_pred = NULL, ask = TRUE,
select = 1:4)
Defaults to NULL.
Only use this when the model was run in an old versions of package
mgcv
and the function cannot retrieve the used AR.start values from
the model
. When an error is shown with newer versions of
mgcv
, please check the column provided as values of AR.start.
when using old versions of package mgcv
.
Function will give error when it cannot find AR.start.
A names list indicating time series in the data.
Logical: whether or not to show the plots one by one.
Defaults to TRUE. When set to FALSE, make sure to have specified
sufficient rows and columns to show the X plots. Alternatively,
use select
to plot only specific plots.
Vector or numeric value indicating which plots to return (see Notes). Defaults to 1:4 (all).
Other Model evaluation: diagnostics
,
plot_modelfit
# NOT RUN {
data(simdat)
# }
# NOT RUN {
# Add start event column:
simdat <- start_event(simdat, event=c("Subject", "Trial"))
head(simdat)
# bam model with AR1 model (toy example, not serious model):
m1 <- bam(Y ~ Group + te(Time, Trial, by=Group),
data=simdat, rho=.5, AR.start=simdat$start.event)
# Warning, no time series specified:
check_resid(m1)
# Time series specified, results in a "standard" ACF plot,
# treating all residuals as single time seriesand,
# and an ACF plot with the average ACF over time series:
check_resid(m1, split_pred=list(Subject=simdat$Subject, Trial=simdat$Trial))
# Note: residuals do not look very good.
# Alternative (results in the same, see help(acf_resid) ):
check_resid(m1, split_pred="AR.start")
# Define larger plot window (choose which line you need):
dev.new(width=8, height=8) # on windows or mac
quartz(,8,8) # on mac
x11(width=8, height=8) # on linux or mac
par(mfrow=c(2,2), cex=1.1)
check_resid(m1, split_pred="AR.start", ask=FALSE)
# }
# NOT RUN {
# }
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