summary.gwer: Summarizing Geographically Weighted Elliptical Regression...

In gwer: Geographically Weighted Elliptical Regression

Description

This function produce summary for the result of the fitted geographically weighted elliptical regression model.

Usage

## S3 method for class 'gwer'
summary(object, ...)

Arguments

object	an object with the result of the fitted geographically weighted elliptical regression model.
...	arguments to be used to form the default control argument if it is not supplied directly.

Value

returns an object of class “summary.gwer”, a list with follow components:

coefficients	the matrix of summarizing coefficients, standard errors and significance values for parameters hypothesis test.
dispersion	either the supplied argument or the estimated dispersion with standard error.
residuals	the residuals from object.
family	family from object.
results	a list of results values for fitted geographically weighted elliptical model.
spdisp	a logical value indicating whether the dispersion varies geographically from object.
df	degrees of freedom from object.
terms	the terms object used.
inter	number of iterations of optimization process.
nas	a logical vector indicating if there is na in estimation of coefficients.
type	a character string indicating the type of residuals was obtained from object
hatmatrix	a logical value indicating if hat matrix was obtained from object
call	the matched call from object.
scale	values of the 4d_g for the specified distribution from object.
scaledispersion	values of the 4f_g for the specified distribution from object.
scalevariance	values of the scale variance for the specified distribution from object.

References

Brunsdon, C., Fotheringham, A. S. and Charlton, M. E. (1996). Geographically weighted regression: a method for exploring spatial nonstationarity. Geographical analysis, 28(4), 281-298. doi: 10.1111/j.1538-4632.1996.tb00936.x

Cysneiros, F. J. A., Paula, G. A., and Galea, M. (2007). Heteroscedastic symmetrical linear models. Statistics & probability letters, 77(11), 1084-1090. doi: 10.1016/j.spl.2007.01.012

See Also

summary, gwer, family.elliptical

Examples

data(georgia, package = "spgwr")
fit.formula <- PctBach ~ TotPop90 + PctRural + PctFB + PctPov
gwer.bw.t <- bw.gwer(fit.formula, data = gSRDF, family = Student(3), adapt = TRUE)
gwer.fit.t <- gwer(fit.formula, data = gSRDF, family = Student(3), bandwidth = gwer.bw.t, 
                   adapt = TRUE, parplot = FALSE, hatmatrix = TRUE, spdisp = TRUE, 
                   method = "gwer.fit")
summary(gwer.fit.t) 

gwer documentation built on April 28, 2021, 9:07 a.m.