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## Estimate of model fit based on neill.test
## The code is an adapatation of drc::neill.test but has been
## changed in some sections because some errors occurs in the original
## function with 'nls' class models. The drc::neill.test, version 2.3-96
get_neilltest <- function(object, x, method, grouping){
noCluster <- floor(length(x)/2)
if(is.null(grouping)){
if (method == "finest") {
lenx <- length(x)
grouping <- floor((1 + 1:lenx)/2)
grouping[lenx] <- grouping[lenx - 1]
}
if (method == "c-finest") {
for (i in noCluster:(length(coef(object)) + 1)) {
grouping <- cutree(hclust(dist(x)), k = i)
if (all(tapply(x, grouping, length) > 1)) {
break
}
}
}
if (method == "percentiles") {
cutVar <- c(-Inf, quantile(x, c(0.2, 0.4, 0.6, 0.8)),
Inf)
grouping <- cut(x, cutVar)
}
}
M <- length(unique(grouping))
lhs <- as.character(object$m$formula()[[2]])
parameters <- names(object$m$getPars())
allobj <- ls(object$m$getEnv())
rhs <- allobj[-match(c(parameters,lhs),allobj)]
ndf <- data.frame(get(lhs, object$m$getEnv()), get(rhs, object$m$getEnv()))
names(ndf) <- c(lhs, rhs)
norder <- order(ndf[,rhs], decreasing=TRUE)
ndf <- ndf[norder,]
N <- nrow(ndf)
denDF <- N - M
## Checking the number of groups
mes <- NULL
if (denDF <= 0) # (N <= M)
{
# "error1.Too many groups in 'grouping'"
mes <- "error1"
}
p <- N - df.residual(object)
numDF <- M - p
if (numDF <= 0) # (M <= p)
{
# "error2. Too few groups in 'grouping'"
mes <- "error2"
}
if(is.null(mes)){
## Calculating the test statistic
resVec <- residuals(object)
resVec <- resVec[norder]
resAver0 <- tapply(resVec, grouping, mean)
resAver <- rep(resAver0, tapply(grouping, grouping, length))
resDiff <- resVec - resAver
FF <- (denDF/numDF)*(sum(resAver*resAver)/(sum(resDiff*resDiff)))
p <- pf(FF ,numDF, denDF, lower.tail = FALSE)
ans <- matrix(c(FF, p), 1, 2)
colnames(ans) <- c("F","p")
} else {
ans <- mes
}
return(ans)
}
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