Sorry if it is a silly question, I haven't found documentation on this and I
don't know if it is possible.
library(MASS) ## for fitdistr
library(msm) ## for dtnorm
#prepare truncated normal distribution
dtnorm0 <- function(x, mean, sd , log = FALSE) {
dtnorm(x, mean, sd, 105, 135, log)
}
set.seed(1)
#Generate normal distribution with the TRUE population mean (day 106 of the
year) that I don't know a priori
x <- rnorm(100, mean=106, sd=40)
#truncated sample simulating those records that I was able to observe
x<-x[x>105 & x<=135]
#fit truncated normal distribution to the data
fitdistr(x, dtnorm0, start = list(mean = mean(x), sd = sd(x)))
The result of the estimated true mean=132.8, sd=25.9, far from the true
values.
Can I, on biological grounds, suggest to fitdistr that the mean must be a
value, for example, between 90 and 110?
Thanks
David
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