Nothing
`MOStest` <-
function(x, y, interval, ...)
{
if (!missing(interval))
interval <- sort(interval)
x <- eval(x)
m0 <- glm(y ~ x + I(x^2), ...)
k <- coef(m0)
isHump <- unname(k[3] < 0)
hn <- if(isHump) "hump" else "pit"
hump <- unname(-k[2]/2/k[3])
if (missing(interval))
p1 <- min(x)
else
p1 <- interval[1]
if (missing(interval))
p2 <- max(x)
else
p2 <- interval[2]
test <- if (m0$family$family %in% c("binomial", "poisson")) "Chisq" else "F"
tmp <- glm(y ~ I(x^2 - 2*x*p1), ...)
## Chisq test has one column less than F test: extract statistic
## and its P value
statmin <- anova(tmp, m0, test = test)[2, (5:6) - (test == "Chisq")]
tmp <- glm(y ~ I(x^2 - 2*x*p2), ...)
statmax <- anova(tmp, m0, test = test)[2, (5:6) - (test == "Chisq")]
comb <- 1 - (1-statmin[2])*(1-statmax[2])
comb <- unlist(comb)
stats <- rbind(statmin, statmax)
rownames(stats) <- paste(hn, c("at min", "at max"))
stats <- cbind("min/max" = c(p1,p2), stats)
stats <- rbind(stats, "Combined" = c(NA, NA, comb))
vec <- c(p1, p2, hump)
names(vec) <- c("min", "max", hn)
vec <- sort(vec)
isBracketed <- names(vec)[2] == hn
out <- list(isHump = isHump, isBracketed = isBracketed,
hump = vec, family = family(m0), coefficients = stats,
mod = m0)
class(out) <- "MOStest"
out
}
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