plot.mat | R Documentation |
Five plots (selectable by which
) are currently available: a
plot of estimated against observed values, a plot of residuals against
estimated values, and screeplots of the apparent RMSE, average bias
and maximum bias for MAT models of size k
, where k = 1,
\dots, n
. By default, the first three and ‘5’ are provided.
## S3 method for class 'mat'
plot(x,
which = c(1:3, 5),
weighted = FALSE,
k,
caption = c("Inferred vs Observed", "Residuals vs Fitted",
"Leave-one-out errors", "Average bias",
"Maximum bias"),
max.bias = TRUE,
n.bias = 10,
restrict = 20,
sub.caption = NULL,
main = "",
ask = prod(par("mfcol")) < length(which) &&
dev.interactive(),
...,
panel = if (add.smooth) panel.smooth else points,
add.smooth = getOption("add.smooth"))
x |
an object of class |
which |
which aspects of the |
weighted |
logical; should the analysis use weighted mean of env data of analogues as fitted/estimated values? |
k |
numeric; the number of analogues to use. If missing |
caption |
captions to appear above the plots. |
max.bias |
logical, should max bias lines be added to residuals. |
n.bias |
numeric, number of sections to calculate maximum bias for. |
restrict |
logical; restrict comparison of k-closest model to
|
sub.caption |
common title-above figures if there are multiple;
used as ‘sub’ (s.‘title’) otherwise. If |
main |
title to each plot-in addition to the above
|
ask |
logical; if |
... |
graphical arguments passed to other graphics functions. |
panel |
panel function. The useful alternative to
|
add.smooth |
logical indicating if a smoother should be added to
fitted & residuals plots; see also |
This plotting function is modelled closely on plot.lm
and many of the conventions and defaults for that function are
replicated here.
sub.caption
- by default the function call - is shown as a
subtitle (under the x-axis title) on each plot when plots are on
separate pages, or as a subtitle in the outer margin (if any) when
there are multiple plots per page.
One or more plots, drawn on the current device.
Gavin L. Simpson. Code borrows heavily from plot.lm
.
mat
## Imbrie and Kipp example
## load the example data
data(ImbrieKipp)
data(SumSST)
data(V12.122)
## merge training and test set on columns
dat <- join(ImbrieKipp, V12.122, verbose = TRUE)
## extract the merged data sets and convert to proportions
ImbrieKipp <- dat[[1]] / 100
V12.122 <- dat[[2]] / 100
## MAT
ik.mat <- mat(ImbrieKipp, SumSST, method = "chord")
## summary plot of MAT model
layout(matrix(1:4, ncol = 2, byrow = TRUE))
plot(ik.mat)
layout(1)
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