M
MissAussie
Member
Hi,
I have 2 quick questions on the table shown on p. 24 of Chapter 2 (ie. the one that contains 15 posteriors for different combinations of priors/likelihoods)
1) When attempting to derive number 7 (ie. the one where the likelihood is Geo(p), I used the fact that the geometric distribution is a special case of the negative binomial distribution. However I didn't know whether to use the Type 1 or Type 2 negative binomial distribution. When I used the Type 1 negative binomial, I got the wrong expression for the posterior, while the Type 2 yielded the right expression. This leads to 2 sub-questions:
a) Can a geometric distribution be a Type 1 negative binomial one with k = 1?
b) If so, surely one should specify whether to use Type 1 or Type 2 in these derivations or statements?
2nd question is, after deriving number 8 (where prior and likelihood are both normal), I think there is an "n" missing in the formula. I think there should be an "n" attached to the (sigma x) term...?
Thanks in advance!
I have 2 quick questions on the table shown on p. 24 of Chapter 2 (ie. the one that contains 15 posteriors for different combinations of priors/likelihoods)
1) When attempting to derive number 7 (ie. the one where the likelihood is Geo(p), I used the fact that the geometric distribution is a special case of the negative binomial distribution. However I didn't know whether to use the Type 1 or Type 2 negative binomial distribution. When I used the Type 1 negative binomial, I got the wrong expression for the posterior, while the Type 2 yielded the right expression. This leads to 2 sub-questions:
a) Can a geometric distribution be a Type 1 negative binomial one with k = 1?
b) If so, surely one should specify whether to use Type 1 or Type 2 in these derivations or statements?
2nd question is, after deriving number 8 (where prior and likelihood are both normal), I think there is an "n" missing in the formula. I think there should be an "n" attached to the (sigma x) term...?
Thanks in advance!