Nothing
# detection of response curves that are concave (non-unimodal)
detect_concave <- function(glm_coefficents) {
if (missing(glm_coefficents)) {
stop("Argumet 'glm_coefficents' must be defined.")
}
coef <- glm_coefficents
varname <- names(coef)
ccoef <- grep("\\^2", varname, value = TRUE)
if (length(ccoef) == 0) {
return("")
} else {
cccoef <- ccoef[coef[ccoef] >= 0]
return(paste(cccoef, collapse = ", "))
}
}
# contribution_formulas <- function(data, dependent, independent, weights = NULL,
# type = "lqp", range = c(0.0001, 0.2),
# by = 0.0001) {
#
# f <- get_formulas(dependent = dependent, independent = independent,
# type = type, all_combinations = FALSE)
#
# allfit <- glm(as.formula(f), data = data, family = binomial(link = "logit"),
# weights = weights)
#
# av <- anova(allfit, test = "Chisq")
# preds <- rownames(av)
# devs <- av$Deviance[-1]
#
# sequ <- seq(range[1], range[2], by = by)
#
# norm_dev <- seq(0, max(devs), length.out = 100)
#
# forms <- lapply(sequ, function(x) {
# thres <- quantile(norm_dev, x)
#
# pick <- devs > thres
#
# pred <- preds[-1][pick]
#
# paste(dependent, "~", paste(pred, collapse = " + "))
# })
#
# forms <- unique(unlist(forms))
# forms <- forms[length(forms):1]
#
# return(forms)
# }
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