In statistics, the generalized linear array model (GLAM) is used for analyzing data sets with array structures. It based on the generalized linear model with the design matrix written as a Kronecker product.
Contents
Overview
The generalized linear array model or GLAM was introduced in 2006. Such models provide a structure and a computational procedure for fitting generalized linear models or GLMs whose model matrix can be written as a Kronecker product and whose data can be written as an array. In a large GLM, the GLAM approach gives very substantial savings in both storage and computational time over the usual GLM algorithm.
Suppose that the data
The standard analysis of a GLM with data vector
where
and
is the working variable.
Computationally, GLAM provides array algorithms to calculate the linear predictor,
and the weighted inner product
without evaluation of the model matrix
Example
In 2 dimensions, let
where
These low storage high speed formulae extend to
Applications
GLAM is designed to be used in