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sphet (version 2.0)

Estimation of Spatial Autoregressive Models with and without Heteroskedastic Innovations

Description

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.

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Install

install.packages('sphet')

Monthly Downloads

709

Version

2.0

License

GPL-2

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Repository

https://github.com/gpiras/sphet

Maintainer

Gianfranco Piras

Last Published

January 6th, 2022

Functions in sphet (2.0)

Generate circular weigthing matrices

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

impacts.stsls_sphet

Generate impacts for objects of class lag_gmm created in sphet

impacts.ols_sphet

Generate impacts for objects of class ols_sphet created in sphet

Generate impacts for objects of class sarar_gmm created in sphet

print method for class sphet

print.summary.sphet

print method for class sphet

Distance measures available in distance

listw2dgCMatrix

Interface between Matrix class objects and weights list

Estimation of spatial models with heteroskedastic innovations

print method for class sphet

Spatial two stages least square with HAC standard errors

GM estimation of a Cliff-Ord type model with Heteroskedastic Innovations

Functions used by gstslshet.

GM estimation of a Cliff-Ord type model with Heteroskedastic Innovations

Read distance ojbects

Generate impacts for spreg lag and sarar models

impacts.error_sphet

Generate impacts for objects of class error_sphet created in sphet

Kelejian and Piras J-test