GWPR.moran.test: Moran's I Test for Panel Regression

In GWPR.light: Geographically Weighted Panel Regression

Moran's I Test for Panel Regression

Description

Moran's I test for spatial autocorrelation in residuals from an estimated panel linear model (plm).

Usage

GWPR.moran.test(plm_model, SDF, bw, adaptive = FALSE, p = 2,
                       kernel = "bisquare", longlat = FALSE, alternative = "greater")

Arguments

plm_model	An object of class inheriting from "plm", see plm
SDF	Spatial*DataFrame on which is based the data, with the "ID" in the index
bw	The optimal bandwidth, either adaptive or fixed distance
adaptive	If TRUE, adaptive distance bandwidth is used, otherwise, fixed distance bandwidth.
p	The power of the Minkowski distance, default is 2, i.e. the Euclidean distance
kernel	bisquare: wgt = (1-(vdist/bw)^2)^2 if vdist < bw, wgt=0 otherwise (default); gaussian: wgt = exp(-.5*(vdist/bw)^2); exponential: wgt = exp(-vdist/bw); tricube: wgt = (1-(vdist/bw)^3)^3 if vdist < bw, wgt=0 otherwise; boxcar: wgt=1 if dist < bw, wgt=0 otherwise
longlat	If TRUE, great circle distances will be calculated
alternative	A character string specifying the alternative hypothesis, must be one of greater (default), less or two.sided.

Value

A list of result:

statistic

the value of the standard deviate of Moran's I.

p.value

the p-value of the test.

Estimated.I

the value of the observed Moran's I.

Excepted.I

the value of the expectation of Moran's I.

V2

the value of the variance of Moran's I.

alternative

a character string describing the alternative hypothesis.

Note

: Current version of panel Moran's I test can only chech the balanced panel data.

Author(s)

Chao Li <[e-mail]> Shunsuke Managi

References

Beenstock, M., Felsenstein, D., 2019. The econometric analysis of non-stationary spatial panel data. Springer.

Examples

data(TransAirPolCalif)
data(California)
formula.GWPR <- pm25 ~ co2_mean + Developed_Open_Space_perc + Developed_Low_Intensity_perc +
   Developed_Medium_Intensity_perc + Developed_High_Intensity_perc +
   Open_Water_perc + Woody_Wetlands_perc + Emergent_Herbaceous_Wetlands_perc +
   Deciduous_Forest_perc + Evergreen_Forest_perc + Mixed_Forest_perc +
   Shrub_perc + Grassland_perc + Pasture_perc + Cultivated_Crops_perc +
   pop_density + summer_tmmx + winter_tmmx + summer_rmax + winter_rmax

pdata <- plm::pdata.frame(TransAirPolCalif, index = c("GEOID", "year"))
moran.plm.model <- plm::plm(formula = formula.GWPR, data = pdata, model = "within")
summary(moran.plm.model)

#precomputed bandwidth
bw.AIC.Fix <- 2.010529

# moran's I test
GWPR.moran.test(moran.plm.model, SDF = California, bw = bw.AIC.Fix, kernel = "bisquare",
                 adaptive = FALSE, p = 2, longlat = FALSE, alternative = "greater")

GWPR.light documentation built on June 21, 2022, 5:05 p.m.