Nothing
##
## auc.R
##
## Calculate ROC curve or area under it
##
## $Revision: 1.17 $ $Date: 2023/08/15 07:44:11 $
roc <- function(X, ...) { UseMethod("roc") }
roc.ppp <- function(X, covariate, ..., high=TRUE) {
nullmodel <- exactppm(X)
result <- rocData(covariate, nullmodel, ..., high=high)
return(result)
}
rocData <- function(covariate, nullmodel, ...,
high=TRUE,
p=seq(0, 1, length=1024)) {
d <- spatialCDFframe(nullmodel, covariate, ...)
U <- d$values$U
ec <- if(high) ecdf(1-U) else ecdf(U)
if(!missing(p)) {
check.nvector(p)
stopifnot(min(p) >= 0)
stopifnot(max(p) <= 1)
if(prod(range(diff(p))) < 0) stop("p should be a monotone sequence")
}
df <- data.frame(p=p, fobs=ec(p), fnull=p)
result <- fv(df,
argu="p",
ylab=quote(roc(p)),
valu="fobs",
fmla= . ~ p,
desc=c("fraction of area",
"observed fraction of points",
"expected fraction if no effect"),
fname="roc")
fvnames(result, ".") <- c("fobs", "fnull")
return(result)
}
rocModel <- function(lambda, nullmodel, ..., high,
p=seq(0, 1, length=1024)) {
if(!missing(high))
warning("Argument 'high' is ignored when computing ROC for a fitted model")
d<- spatialCDFframe(nullmodel, lambda, ...)
U <- d$values$U
ec <- ecdf(1-U)
if(!missing(p)) {
check.nvector(p)
stopifnot(min(p) >= 0)
stopifnot(max(p) <= 1)
if(prod(range(diff(p))) < 0) stop("p should be a monotone sequence")
}
fobs <- ec(p)
FZ <- d$values$FZ
FZinverse <- quantilefun.ewcdf(FZ)
lambdavalues <- if(is.im(lambda)) lambda[] else unlist(lapply(lambda, "["))
F1Z <- ewcdf(lambdavalues, lambdavalues/sum(lambdavalues))
ftheo <- 1 - F1Z(FZinverse(1-p))
df <- data.frame(p=p, fobs=fobs, ftheo=ftheo, fnull=p)
result <- fv(df,
argu="p",
ylab=quote(roc(p)),
valu="fobs",
fmla = . ~ p,
desc=c("fraction of area",
"observed fraction of points",
"expected fraction of points",
"expected fraction if no effect"),
fname="roc")
fvnames(result, ".") <- c("fobs", "ftheo", "fnull")
return(result)
}
## Code for roc.ppm, roc.slrm, roc.kppm is moved to spatstat.model
# ......................................................
auc <- function(X, ...) { UseMethod("auc") }
auc.ppp <- function(X, covariate, ..., high=TRUE) {
d <- spatialCDFframe(exactppm(X), covariate, ...)
U <- d$values$U
EU <- mean(U)
result <- if(high) EU else (1 - EU)
return(result)
}
## Code for auc.ppm, auc.slrm, auc.kppm is moved to spatstat.model
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