Suppose that we have a sample of n observations y1, y2, . . . , yn which can be treated as a Poisson distribution, with:
The following variance function:
Furthermore, suppose that we want to let the mean µi (and therefore the variance) depend on a vector of explanatory variables xi. We can adopt a simple linear model of the form:
The linear predictor on the right-hand side of the previous equation can assume any real ...
Get Regression Analysis with R now with the O’Reilly learning platform.
O’Reilly members experience books, live events, courses curated by job role, and more from O’Reilly and nearly 200 top publishers.
Get Mark Richards’s Software Architecture Patterns ebook to better understand how to design components—and how they should interact.
Dive in for free with a 10-day trial of the O’Reilly learning platform—then explore all the other resources our members count on to build skills and solve problems every day.
Start your free trial Become a member now