coldis

knn10columbus

Object of class distance for Columbus dataset 
10-nearest neighbors matrix for columbus dataset

Functions for fitting Cliff-Ord-type spatial autoregressive models with and without heteroskedastic innovations using Generalized Method of Moments estimation are provided. Some support is available for fitting spatial HAC models, and for fitting with non-spatial endogeneous variables using instrumental variables.

Gianfranco Piras

sphet

Estimation of Spatial Autoregressive Models with and without
Heteroskedastic Innovations

Roger Bivand

coldis function

A list of neighbors and distances for the columbus neighborhoods

Format

Gianfranco Piras <a href="/link/gpiras%40mac.com?package=sphet&version=2.0" data-mini-rdoc="sphet::gpiras@mac.com">gpiras@mac.com</a>

Author

Object of class distance for Columbus dataset 
10-nearest neighbors matrix for columbus dataset — coldis

Gianfranco Piras <a href='mailto:gpiras@mac.com'>gpiras@mac.com</a>

coldis: Object of class distance for Columbus dataset 10-nearest neighbors matrix for columbus dataset

Description

Arguments

Format

Author