View source: R/plotConfidence.R
plotCCVal | R Documentation |
Plot confidence curve for (uE,E) set. New version with improved validation.
plotCCVal(
E,
uE,
stat = ErrViewLib::rmse,
probref = FALSE,
rep_probref = 1000,
showUk = FALSE,
plot = TRUE,
score = FALSE,
nBoot = 5000,
parallel = FALSE,
cl = NULL,
col = 5,
type = c("l", "p"),
add = FALSE,
xlab = "k% discarded",
xlim = NULL,
ylab = "RMSE",
ylim = NULL,
title = NULL,
label = 0,
showLegend = TRUE,
legend = NULL,
legLoc = "bottomleft",
gPars = ErrViewLib::setgPars()
)
E |
(vector) prediction uncertainty, uE, or predicted value, V |
uE |
(vector) error or z-score |
probref |
(logical) plot probabilistic reference (probref) curve (default: FALSE) |
rep_probref |
(integer) sampling repetitions for normal curve (default = 1000) |
showUk |
(logical) plot secondary axis with u_k values; supersedes 'title' |
plot |
(function) produce plot ? |
score |
(logical) estimate confidence score ? This requires a bootstrapped CI on the CC and might take some time. |
nBoot |
(integer) nb of bootstrap repeats to estimate CI on confidence curve (default = 5000) |
parallel |
(logical) use parallelized bootstrap ? (default = FALSE) |
cl |
(object) cluster for parallel computing, which is used when parallel = TRUE. If parallel = TRUE and cl = NULL, then the cluster is defined as cl = makeCluster(detectCores()). (default = NULL) |
col |
(integer) color index for the curve (default: 6) |
add |
(logical) add confidence curve to previous plot (default: FALSE) |
xlab |
(string) x axis label (default: 'k % discarded) |
xlim |
(vector) limits of the x axis (default: NULL) |
ylim |
(vector) limits of the y axis (default: NULL) |
title |
(string) a title to display above the plot (default: ”) |
label |
(integer) index of letter for subplot tag (default: 0) |
showLegend |
(logical) display legend (default: TRUE) |
legend |
(string) legend for the dataset (default: NULL) |
legLoc |
(string) location of legend (see xy.coord) (default: 'bottomleft') |
gPars |
(list) graphical parameters (default: ErrViewLib::setgPars()) |
unit |
(string) unit string to add to ylab |
Plot confidence curve for (E,uE) set
uE = sqrt(rchisq(1000, df = 4)) # Re-scale uncertainty
E = rnorm(uE, mean=0, sd=uE) # Generate errors
plotCCVal(E, uE)
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