LR.sarlm: Likelihood ratio test
In spdep: Spatial Dependence: Weighting Schemes, Statistics and Models

Description Usage Arguments Value Note Author(s) References See Also Examples

The LR.sarlm() function provides a likelihood ratio test for objects for which a logLik() function exists for their class, or for objects of class logLik. LR1.sarlm() and Wald1.sarlm() are used internally in summary.sarlm(), but may be accessed directly; they report the values respectively of LR and Wald tests for the absence of spatial dependence in spatial lag or error models. The spatial Hausman test is available for models fitted with errorsarlm and GMerrorsar.

LR.sarlm(x, y)
## S3 method for class 'sarlm'
logLik(object, ...)
LR1.sarlm(object)
Wald1.sarlm(object)
## S3 method for class 'sarlm'
Hausman.test(object, ..., tol=NULL)
## S3 method for class 'gmsar'
Hausman.test(object, ..., tol=NULL)

`x`	a `logLik` object or an object for which a `logLik()` function exists
`y`	a `logLik` object or an object for which a `logLik()` function exists
`object`	a `sarlm` object from `lagsarlm()` or `errorsarlm()`
`...`	further arguments passed to or from other methods
`tol`	`tol` argument passed to `solve`, default NULL

The tests return objects of class htest with:

`statistic`	value of statistic
`parameter`	degrees of freedom
`p.value`	Probability value
`estimate`	varies with test
`method`	description of test method

logLik.sarlm() returns an object of class logLik LR1.sarlm, Hausman.sarlm and Wald1.sarlm returm objects of class htest

The numbers of degrees of freedom returned by logLik.sarlm() include nuisance parameters, that is the number of regression coefficients, plus sigma, plus spatial parameter esitmate(s).

Roger Bivand Roger.Bivand@nhh.no

LeSage J and RK Pace (2009) Introduction to Spatial Econometrics. CRC Press, Boca Raton, pp. 61–63; Pace RK and LeSage J (2008) A spatial Hausman test. Economics Letters 101, 282–284.

logLik.lm, anova.sarlm

example(columbus)
mixed <- lagsarlm(CRIME ~ HOVAL + INC, data=columbus, nb2listw(col.gal.nb),
  type="mixed")
error <- errorsarlm(CRIME ~ HOVAL + INC, data=columbus, nb2listw(col.gal.nb))
LR.sarlm(mixed, error)
Hausman.test(error)

Loading required package: sp
Loading required package: Matrix

colmbs> require(maptools)
Loading required package: maptools
Checking rgeos availability: TRUE

colmbs> columbus <- readShapePoly(system.file("etc/shapes/columbus.shp",
colmbs+  package="spdep")[1])

colmbs> col.gal.nb <- read.gal(system.file("etc/weights/columbus.gal",
colmbs+  package="spdep")[1])
Warning message:
use rgdal::readOGR or sf::st_read 

	Likelihood ratio for spatial linear models

data:  
Likelihood ratio = 4.2782, df = 2, p-value = 0.1178
sample estimates:
Log likelihood of mixed Log likelihood of error 
              -182.0161               -184.1552 


	Spatial Hausman test (asymptotic)

data:  NULL
Hausman test = 6.4729, df = 3, p-value = 0.09074