# Conjugate prior for a Gamma distribution

I need to update the failure rate (given as deterministic) based on new rate of failure about the same system (it is a deterministic one too). I read about conjugate priors and Gamma distribution as a conjugate for the Poisson process.

Also, I can equate the mean value of Gamma dist. ($\beta/\alpha$) to the new rate (as a mean value) but I do not have any other information such as standard deviation, Coefficient of Variation, 90th percentile value,...etc. Is there a magic way to manipulate that and find parameters for the prior Gamma hence I get the posterior which Gamma too?

• Your question is not clear. Could you please edit the text and add a bit more context?
– user28
Sep 15 '10 at 3:25
• ... and maybe a better topic?
– user88
Oct 5 '10 at 10:52
• I attempted to make it a better title; feel free to change it to something more appropriate Nov 4 '10 at 6:25
• What parameterization are you using for your Gamma? Aug 2 '13 at 5:12