I thought I was finished, having gotten everything to work as intended. This is a model of risk, and the short term forecasts look very good, given the data collected after the estimates are produced (this model is intended to be executed daily, to give a continuing picture of our risk). But now there is a new requirement.
I have weekly samples from a non-autonomous process (i.e. although well modelled as a decay process, with an exponential distribution fitting the decay times well, the rate estimates and their sd vary considerably from one week to the next). The total number of events to be expected from a given sample over the next week can be easily estimated from a simple integral. And the total number of these events from all samples, is just the sum of these estimates over all samples. So far, so good (imagine you have a sample of a variety of species of radionuclides all emitting alpha particles with the same energy - so you can't tell from the decay event which species produced the alpha particles). I guess there are two parts of my question. I get a fit of the exponential distribution to each sample using fitdistr(x,"exponential"). I am finding the expected values vary by as much as a factor of 4, and the corresponding estimates of sd vary by as much as a factor of 100 (some samples are MUCH larger than others). How do I go from the sd it gives to a 99% confidence interval for the integral for that function from now through a week from now (or to the end of time, or through the next month/quarter)? And how do I move from these estimates to get the expected value and confidence intervals for the totals over all the samples? I am a bit rusty on figuring out how error propagates through model calculations (an online reference for this would be handy, if you know of one). Thanks Ted -- View this message in context: http://www.nabble.com/How-to-get-estimate-of-confidence-interval--tp20073921p20073921.html Sent from the R help mailing list archive at Nabble.com. ______________________________________________ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.