The estimation functions rely on the SPARSE matrix facilities in MATLAB to solve large problems quickly. A separate manual exists along with a unix tar file containing spatial datasets and examples from the manual (see below for downloading).
There are also spatial econometrics learning materials developed under the auspices of the Regional Research Institute at West Virginia Univeristy for the Web Book of Regional Science.
| Download manual | Acrobat PDF file (updated 9/99) |
| Download manual | Postscript file (updated 9/99) |
| For documentation on semip_g.m function see: "A Bayesian probit model with spatial dependencies", Tony E. Smith and James P. LeSage, in Advances in Econometrics: Volume 18: Spatial and Spatiotemporal Econometrics, (Oxford: Elsevier Ltd), James P. LeSage and R. Kelley Pace (eds.), 2004, pp. 127-160. | |
| For documentation on bgwr.m function see: "A Family of Geographically Weighted Regression models", James P. LeSage in Econometrics for Spatial Models, Recent Advances, Springer-Verlag Luc Anselin and J.G.M. Florax and S. Rey (eds.), 2004, pp. 241-264. | |
| Download "Using matrix exponentials to explore spatial structure in regression relationships", James P. LeSage and R. Kelley Pace | Acrobat PDF file (updated 10/2000) |
| Download PDF file (200 pages) | (updated 12/98) |
| view datasets | (updated 4/2001) |