summary.hgwrm: Summary an 'hgwrm' object.
In hgwrr: Hierarchical and Geographically Weighted Regression

summary.hgwrm

R Documentation

Summary an `hgwrm` object.

Description

Summary an hgwrm object.

Usage

## S3 method for class 'hgwrm'
summary(object, ..., test_hetero = FALSE, verbose = 0)

Arguments

`object`	An `hgwrm` object returned from `hgwr()`.
`...`	Other arguments passed from other functions.
`test_hetero`	Logical/list value. Whether to test the spatial heterogeneity of GLSW effects. If it is set to `FALSE`, the test will not be executed. If it is set to `TRUE`, the test will be executed with default parameters (see details below). It accepts a list to enable the test with specified parameters.
`verbose`	An Integer value to control whether additional messages during testing spatial heterogeneity should be reported.

Details

The parameters used to perform test of spatial heterogeneity are

bw: Bandwidth (unit: number of nearest neighbours) used to make spatial kernel density estimation. Default: 10.
poly: The number of polynomial terms used in the local polynomial estimation. Default: 2.
resample: Total resampling times. Default: 5000.
kernel: The kernel function used in the local polynomial estimation. Options are "gaussian" and "bisquared". Default: "bisquared".

Value

A list containing summary informations of this hgwrm object with the following fields.

diagnostic: A list of diagnostic information.
random.stddev: The standard deviation of random effects.
random.corr: The correlation matrix of random effects.
residuals: The residual vector.

Examples

data(mulsam.test)
m <- hgwr(
  formula = y ~ L(g1 + g2) + x1 + (z1 | group),
  data = mulsam.test$data,
  coords = mulsam.test$coords,
  bw = 10
)
summary(m)
summary(m, test_hetero = TRUE)
summary(m, test_hetero = list(kernel = "gaussian"))

hgwrr documentation built on April 4, 2025, 3:57 a.m.