Spatial autocorrelation and spatial-econometric estimators
morie_spatial_econometrics.RdMoran's I with its asymptotic test, the S0/S1/S2 weights constants, and the spatial lag and spatial error models estimated by two-stage least squares and by generalised moments.
Value
A number for morie_morans_i; otherwise a list holding the
estimate together with its expectation, variance, test statistic and
p-value, or for the regression estimators the spatial parameter, the
coefficient vector and the residuals.
Details
Verified numerically against the R reference implementations these
mirror – spdep::Szero, spdep::moran.test,
spatialreg::stsls and spatialreg::GMerrorsar – so the
analyses in Bivand, Pebesma and Gomez-Rubio can be run without
depending on those packages. The same functions exist in the Python
package as morie.fn._robust_core.
References
Cliff, A. D. & Ord, J. K. (1981) Spatial Processes. Pion.
Kelejian, H. H. & Prucha, I. R. (1998) A generalized spatial two-stage least squares procedure. Journal of Real Estate Finance and Economics 17, 99-121.
Kelejian, H. H. & Prucha, I. R. (1999) A generalized moments estimator for the autoregressive parameter in a spatial model. International Economic Review 40, 509-533.
Bivand, R. S., Pebesma, E. & Gomez-Rubio, V. (2013) Applied Spatial Data Analysis with R, 2nd ed. Springer (Use R!).