An introduction to pspatreg

IF 1 Q2 AREA STUDIES Baltic Region Pub Date : 2022-12-07 DOI:10.18335/region.v9i2.450
R. Mínguez, Roberto Basile, M. Durbán
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引用次数: 0

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 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.
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pspatregg简介
本文介绍了一个新的R包(pspatreg),用于估计半参数空间自回归模型。pspatreg通过限制最大似然或最大似然拟合惩罚样条半参数空间自回归模型。这些模型非常灵活,因为它们可以同时控制空间依赖性、功能形式的非线性和时空异质性。该软件包还允许估计横截面和面板数据的参数空间自回归模型(具有固定效果),从而避免使用不同的库。该软件包的官方演示、插图和教程在CRAN或GitHub中分发。本文通过对横断面数据使用应用程序来演示包的潜力。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Baltic Region
Baltic Region AREA STUDIES-
CiteScore
1.60
自引率
37.50%
发文量
11
审稿时长
24 weeks
期刊最新文献
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