Wsp_it

A spatial weight matrix row-standardized for Italian NUTS-3 provinces

datasets

Estimation and inference of spatial and spatio-temporal
semiparametric models including spatial or spatio-temporal non-parametric
trends, parametric and non-parametric covariates and, possibly, a spatial
lag for the dependent variable and temporal correlation in the noise.
The spatio-temporal trend can be decomposed in ANOVA way including main and
interaction functional terms. Use of SAP algorithm to estimate the spatial
or spatio-temporal trend and non-parametric covariates. The methodology of
these models can be found in next references
Basile, R. et al. (2014), <doi:10.1016/j.jedc.2014.06.011>;
Rodriguez-Alvarez, M.X. et al. (2015) <doi:10.1007/s11222-014-9464-2> and,
particularly referred to the focus of the package, Minguez, R.,
Basile, R. and Durban, M. (2020) <doi:10.1007/s10260-019-00492-8>.

Roman Minguez

pspatreg

Spatial and Spatio-Temporal Semiparametric Regression Models
with Spatial Lags

Roberto Basile

Maria Durban

Gonzalo Espana-Heredia

Wsp_it function

A row-standardized squared matrix with 103 rows and columns. 
The rows and columns follow the same order than provinces included in 
unemp_it data frame.

Format

Spatial weight matrix for Italian provinces — Wsp_it

Spatial weight matrix for Italian provinces

Wsp_it: Spatial weight matrix for Italian provinces

Description

Usage

Arguments

Format