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mkinerrmin <- function(errdata, n.parms, alpha = 0.05)
{
means.mean <- mean(errdata$value_mean, na.rm=TRUE)
df = length(errdata$value_mean) - n.parms
f <- function(err)
{
(sum((errdata$value_mean - errdata$value_pred)^2/((err * means.mean)^2)) -
qchisq(1 - alpha,df))^2
}
err.min <- optimize(f, c(0.01,0.9))$minimum
return(list(err.min = err.min, n.optim = n.parms, df = df))
}
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