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https://doi.org/10.18335/region.v9i2.450

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An introduction to pspatreg: A new R package for semiparametric spatial autoregressive analysis

[journal article]

Mínguez, Román
Basile, Roberto
Durbán, María

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... view more

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.... view less

Classification
Area Development Planning, Regional Research

Free Keywords
R package; Spatial dependence; Semiparametric models; Splines

Document language
English

Publication Year
2022

Page/Pages
p. R1-R15

Journal
Region: the journal of ERSA, 9 (2022) 2

ISSN
2409-5370

Status
Published Version; reviewed

Licence
Creative Commons - Attribution 4.0


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© 2007 - 2025 Social Science Open Access Repository (SSOAR).
Based on DSpace, Copyright (c) 2002-2022, DuraSpace. All rights reserved.