Trouble is, they require that I provide a posterior log-likelihood function, which is a simple enough requirement that seems to be giving me problems for some reason.<BR><BR>I know it should be ...

That is, the variance of Y is , where >1. With overdispersion, methods based on quasi-likelihood can be used to estimate the parameters and .A quasi-likelihood function is specified by its associated ...

There are three SAS procedures that enable you to do maximum likelihood estimation of parameters in an arbitrary model with a likelihood function that you define: PROC MODEL, PROC NLP, and PROC IML.

In this part you do not have to sketch the graph and you may even be given the sketch of the graph to start with. For a quadratic equation of the form \(y = k{(x - a)^2} + b\), the following ...