Comments (2)
Thanks for this question. I read "Chapter 8.2 The gamma distribution" in the book "Generzlized Linear Models", and find the authors say "we are concerned mostly with models for which the shape parameter is assumed constant for all observations". So I think it is make sense that a data set share the same shape parameter.
Actually, the simulation setting adopts that in R:
# add noise
sigma <- sqrt((t(beta) %*% Sigma %*% beta) / snr)
eta <- x %*% beta + stats::rnorm(n, 0, sigma)
# set coef_0 as + abs(min(eta)) + 1
eta <- eta + abs(min(eta)) + 10
# set the shape parameter of gamma uniformly in [0.1, 100.1]
shape_para <- 100 * runif(n) + 0.1
y <- stats::rgamma(n, shape = shape_para, rate = shape_para * eta)
This is written by @bbayukari , is there has any special consideration?
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I completely agree with you that a data set should share the same shape parameter.
It has been fixed in d039462.
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