diagnose | R Documentation |
Diagnose and examine combined fields, MVR, and CCA results. applies some tests to check for consistency.
diagnose(x, ...)
x |
data object |
... |
additional arguments |
it |
teporal selection - see |
plot |
if TRUE, plot results |
plot.type |
type of plot |
verbose |
Logical value defaulting to FALSE. If FALSE, do not display comments (silent mode). If TRUE, displays extra information on progress. |
new |
if TRUE plot in new window |
xlim |
range of y-axis |
alpha |
factor modifying the opacity alpha; typically in [0,1] |
map.show |
if TRUE show map |
xrange |
longitude range to display in map |
yrange |
latitude range to display in map |
main |
main label in plot |
sub |
smaller label (subtitle) in plot |
xlab |
label of x-axis |
ylab |
label of y-axis |
probs |
quantile to display in plot, e.g., probs=0.95 gives a diagnosis of the 95th percentile of the data. |
The method diagnose.comb.eof
which estimates the difference in the
mean for the PCs of the calibration data and GCMs over a common period in
addition to the ratio of standard deviations and lag-one autocorrelation.
The x-axis shows the difference in the mean of the segments in the PCs
representing the different data souces, the y-axis shows difference in
standard deviation and the size of the symbols the difference in the
autocorrelation (open symbols if the autocorrelation have different signs).
climvar
estimates the climatological variance, e.g. how the
inter-annual variance varies with seasons.
A 'diag' object containing test results
R.E. Benestad
t2m <- t2m.DNMI(lon=c(-40,40),lat=c(30,70))
T2m <- t2m.NorESM.M(lon=c(-40,40),lat=c(30,70))
# Combine in time to compute common EOFs:
X <- combine(t2m,T2m)
diagnose(X)
ceof <- EOF(X,it="jan")
plot(diagnose(ceof))
slp <- slp.NCEP(lat=c(-40,40),anomaly=TRUE)
sst <- sst.NCEP(lat=c(-40,40),anomaly=TRUE)
eof.1 <- EOF(slp,it="jan")
eof.2 <- EOF(sst,it="jan")
cca <- CCA(eof.1,eof.2)
diagnose(cca)
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