Abstract:
Data collected from neighbouring districts are often spatially correlated. I will present the conditional autoregressive (CAR) spatial model whereby these correlations can be fitted. The method has recently been implemented in the R package hglm and is described in an article to appear in the R Journal.
The hglm package fits linear mixed models by iterating between generalized linear models. This algorithm will be presented and how it can be used to fit a CAR model in a computationally efficient manner.
The package can also be used to make predictions for districts with no observations and an example using 4th grade school results from Ohio will be presented.
Seminar: Lars Rönnegård, Dalarna University
EVENT
Date:
30 September 2015, 1.00 PM
-
30 September 2015, 2.00 PM
Venue: B705
Venue: B705
Title: A Generalized Linear Model Approach to Spatial Modelling.
Last updated:
April 12, 2016
Source: Department of Statistics