ntspsac: Estimates a Spatial Autocorrelation (SAC) lag model.
In judechays/STADL: Tools for analyzing country-year time-series-cross-sectional data with spatial and temporal dependence
ntspsac R Documentation
Estimates a Spatial Autocorrelation (SAC) lag model.
Description
ntspsac estimates a Spatial Autocorrelation (SAC) model (spatialreg::sacsarlm)
using the nearest neighbor spatial weights matrix you previously created
and a linear regression model.
Usage
ntspsac(lmobj, wm)
Arguments
lmobj
An object created by the lm function.
wm
neighbor spatial weight matrix created by the make_ntspmat.
Value
The output will be SAR model estimated.
Examples
## Not run:
sac_reex <- ntsperr(ols,wm)
## End(Not run)
judechays/STADL documentation built on May 12, 2022, 10:50 p.m.
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| ntspsac | R Documentation |
Estimates a Spatial Autocorrelation (SAC) lag model.
Description
ntspsac estimates a Spatial Autocorrelation (SAC) model (spatialreg::sacsarlm)
using the nearest neighbor spatial weights matrix you previously created
and a linear regression model.
Usage
ntspsac(lmobj, wm)
Arguments
lmobj |
An object created by the |
wm |
neighbor spatial weight matrix created by the |
Value
The output will be SAR model estimated.
Examples
## Not run: sac_reex <- ntsperr(ols,wm) ## End(Not run)
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
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