Hello, is there a package which allows to fit a spatial regression model for any k-dimensional data? The spatial regression model is composed of three components: y=mu+Z+epsilon, where mu is a low order polynomial, Z is a realization of a second-order stochastic process with covariance matrix Sigma and epsilon is a realization of a white-noise process. The covariance function belongs to the class of either isotropic or anisotropic functions. Mean and covariance parameters are estimated simultaneously by ML or REML. I hope somebody can answer my question. Thank you! Nadine Henkenjohann
Spatial regression model
2 messages · Nadine Henkenjohann, Roger Bivand
On Wed, 7 Jan 2004, Nadine Henkenjohann wrote:
Hello, is there a package which allows to fit a spatial regression model for any k-dimensional data?
This site: http://sal.agecon.uiuc.edu/csiss/Rgeo/index.html tries to provide some guidance about the availability of packages for analysis of spatial data. The Geostatistics section of that site lists a number of packages perhaps relevant to your problem, but there are other possibilities too. Roger
The spatial regression model is composed of three components: y=mu+Z+epsilon, where mu is a low order polynomial, Z is a realization of a second-order stochastic process with covariance matrix Sigma and epsilon is a realization of a white-noise process. The covariance function belongs to the class of either isotropic or anisotropic functions. Mean and covariance parameters are estimated simultaneously by ML or REML. I hope somebody can answer my question. Thank you! Nadine Henkenjohann
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Roger Bivand Economic Geography Section, Department of Economics, Norwegian School of Economics and Business Administration, Breiviksveien 40, N-5045 Bergen, Norway. voice: +47 55 95 93 55; fax +47 55 95 93 93 e-mail: Roger.Bivand at nhh.no