qqnorm.predCVSTmodel {SpatioTemporal} | R Documentation |
STdata
/STmodel
/predCVSTmodel
objectsqqnorm
method for classes
STdata
/STmodel
/predCVSTmodel
.
Used for data and residual analysis of the cross validation.
## S3 method for class 'predCVSTmodel' qqnorm(y, ID = "all", main = "Q-Q plot for CV residuals", group = NULL, col = 1, norm = FALSE, line = 0, org.scale = TRUE, ...) ## S3 method for class 'STdata' qqnorm(y, ID = "all", main = "Q-Q plot for observations", group = NULL, col = 1, line = 0, ...) ## S3 method for class 'STmodel' qqnorm(y, ID = "all", main = "Q-Q plot for observations", group = NULL, col = 1, line = 0, ...)
y |
|
ID |
The location for which we want to norm-plot observations/residuals
or |
main |
Title of the plot |
group |
Do the norm-plot both for all data and then for each subset defined by the factor/levels in group variable. |
col |
Colour of points in the plot, either a scalar or a vector with length matching the number of observations/residuals. |
norm |
|
line |
If non-zero add a |
org.scale |
|
... |
Arguments passed on to the plotting function,
|
Nothing
Johan Lindstrom
Other predCVSTmodel methods: estimateCV.STmodel
,
plot.predCVSTmodel
,
print.predCVSTmodel
,
print.summary.predCVSTmodel
,
scatterPlot.predCVSTmodel
,
summary.predCVSTmodel
Other STdata methods: createSTdata
,
plot.STdata
, print.STdata
,
print.summary.STdata
,
scatterPlot.predCVSTmodel
,
summary.STdata
Other STmodel methods: MCMC.STmodel
,
c.STmodel
, createSTmodel
,
estimate.STmodel
,
estimateCV.STmodel
,
plot.STdata
, predict.STmodel
,
print.STmodel
,
print.summary.STmodel
,
scatterPlot.predCVSTmodel
,
simulate.STmodel
,
summary.STmodel
################################ ## Example for STdata/STmodel ## ################################ ##load data data(mesa.model) ##standard plot qqnorm(mesa.model) ##add a line, and group (and colour) by AQS/FIXED par(mfrow=c(2,2)) obs.type <- mesa.model$locations$type[match(mesa.model$obs$ID, mesa.model$locations$ID)] qqnorm(mesa.model, line=1, group=obs.type, col=obs.type) ##colour code by season and split by type ##First create a vector dividing data into four seasons I.season <- as.factor(as.POSIXlt(mesa.model$obs$date)$mon+1) levels(I.season) <- c(rep("Winter",2), rep("Spring",3), rep("Summer",3), rep("Fall",3), "Winter") par(mfrow=c(2,2)) qqnorm(mesa.model, line=1, col=I.season, group=obs.type) legend("bottomright", legend=as.character(levels(I.season)), pch=1, col=1:nlevels(I.season)) ############################### ## Example for predCVSTmodel ## ############################### ##load data data(pred.cv.mesa) ##standard plot par(mfrow=c(1,1)) qqnorm(pred.cv.mesa, line=3) ##or for the normalised residuals qqnorm(pred.cv.mesa, line=3, norm=TRUE) ##add a line, and group by AQS/FIXED par(mfrow=c(2,2)) qqnorm(pred.cv.mesa, line=1, group=obs.type) ##and for normalised residuals, colour-coded by season par(mfrow=c(2,2)) qqnorm(pred.cv.mesa, line=2, norm=TRUE, group=obs.type, col=I.season) legend("bottomright", legend=as.character(levels(I.season)), pch=1, col=1:nlevels(I.season))