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An introduction to pspatreg: A new R package for semiparametric spatial autoregressive analysis
[Zeitschriftenartikel]
Abstract This article introduces a new R package (pspatreg) for the estimation of semiparametric spatial autoregressive models. pspatreg fits penalized spline semiparametric spatial autoregressive models via Restricted Maximum Likelihood or Maximum Likelihood. These models are very flexible since they make i... mehr
This article introduces a new R package (pspatreg) for the estimation of semiparametric spatial autoregressive models. pspatreg fits penalized spline semiparametric spatial autoregressive models via Restricted Maximum Likelihood or Maximum Likelihood. These models are very flexible since they make it possible to simultaneously control for spatial dependence, nonlinearities in the functional form, and spatio-temporal heterogeneity. The package also allows to estimate parametric spatial autoregressive models for both cross sectional and panel data (with fixed effects), thus avoiding the use of different libraries. The official demos, vignettes, and tutorials of the package are distributed either in CRAN or GitHub. This article illustrates the potential of the package by using an application to cross-sectional data.... weniger
Klassifikation
Raumplanung und Regionalforschung
Freie Schlagwörter
R package; Spatial dependence; Semiparametric models; Splines
Sprache Dokument
Englisch
Publikationsjahr
2022
Seitenangabe
S. R1-R15
Zeitschriftentitel
Region: the journal of ERSA, 9 (2022) 2
ISSN
2409-5370
Status
Veröffentlichungsversion; begutachtet