Spatial Regression Analysis
Approximate profile-likelihood estimator (APLE) permutation test
Approximate profile-likelihood estimator (APLE) scatterplot
Approximate profile-likelihood estimator (APLE)
Spatial regression model Jacobian computations
Spatial weights matrix eigenvalues
Spatial simultaneous autoregressive error model estimation by GMM
Spatial simultaneous autoregressive SAC model estimation by GMM
Impacts in spatial lag models
Compute SAR generating operator
Matrix exponential spatial lag model
Find extreme eigenvalues of binary symmetric spatial weights
MCMC sample from fitted spatial regression
Moran eigenvector GLM filtering
Spatial simultaneous autoregressive model estimation by maximum likeli...
Prediction for spatial simultaneous autoregressive linear model object...
Likelihood ratio test
Bayesian MCMC spatial simultaneous autoregressive model estimation
Options for parallel support
Control checking of spatial object IDs
Create symmetric similar weights lists
Spatial Durbin linear (SLX, spatially lagged X) model
Spatial neighbour sparse representation
Semi-parametric spatial filtering
Spatial conditional and simultaneous autoregression model estimation
Generalized spatial two stage least squares
Spatial weights matrix powers traces
A collection of all the estimation functions for spatial cross-sectional models (on lattice/areal data using spatial weights matrices) contained up to now in 'spdep'. These model fitting functions include maximum likelihood methods for cross-sectional models proposed by 'Cliff' and 'Ord' (1973, ISBN:0850860369) and (1981, ISBN:0850860814), fitting methods initially described by 'Ord' (1975) <doi:10.1080/01621459.1975.10480272>. The models are further described by 'Anselin' (1988) <doi:10.1007/978-94-015-7799-1>. Spatial two stage least squares and spatial general method of moment models initially proposed by 'Kelejian' and 'Prucha' (1998) <doi:10.1023/A:1007707430416> and (1999) <doi:10.1111/1468-2354.00027> are provided. Impact methods and MCMC fitting methods proposed by 'LeSage' and 'Pace' (2009) <doi:10.1201/9781420064254> are implemented for the family of cross-sectional spatial regression models. Methods for fitting the log determinant term in maximum likelihood and MCMC fitting are compared by 'Bivand et al.' (2013) <doi:10.1111/gean.12008>, and model fitting methods by 'Bivand' and 'Piras' (2015) <doi:10.18637/jss.v063.i18>; both of these articles include extensive lists of references. A recent review is provided by 'Bivand', 'Millo' and 'Piras' (2021) <doi:10.3390/math9111276>. 'spatialreg' >= 1.1-* corresponded to 'spdep' >= 1.1-1, in which the model fitting functions were deprecated and passed through to 'spatialreg', but masked those in 'spatialreg'. From versions 1.2-*, the functions have been made defunct in 'spdep'.
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