Hi, I'm doing a generalized linear mixed model, and I currently use an R function called "glmm". However, in this function they use a standard normal distribution for the random effect, which doesn't satisfy my case, i.e. my random effect also follows a normal distribution, but observations over time are somehow correlated, so the covariance matrix would be different the identity matrix. Besides, it's also different from the commonly used AR(1), AR(2) structures, so actually I need a way to write down the covariance matrix for the random effect in GLMM by myself. Does anyone know how to do this in R? Thank you in advance for any help. -- Best, Vicky [[alternative HTML version deleted]]
Hi, I'm doing a generalized linear mixed model, and I currently use an R function called "glmm". However, in this function they use a standard normal distribution for the random effect, which doesn't satisfy my case, i.e. my random effect also follows a normal distribution, but observations over time are somehow correlated, so the covariance matrix would be different the identity matrix. Besides, it's also different from the commonly used AR(1), AR(2) structures, so actually I need a way to write down the covariance matrix for the random effect in GLMM by myself. Does anyone know how to do this in R? Thank you in advance for any help. -- Best, Vicky [[alternative HTML version deleted]]