MCMCsamp {spatialreg} | R Documentation |
MCMC sample from fitted spatial regression
Description
The MCMCsamp
method uses rwmetrop
, a random walk Metropolis algorithm, from LearnBayes to make MCMC samples from fitted maximum likelihood spatial regression models.
Usage
MCMCsamp(object, mcmc = 1L, verbose = NULL, ...)
## S3 method for class 'Spautolm'
MCMCsamp(object, mcmc = 1L, verbose = NULL, ...,
burnin = 0L, scale=1, listw, control = list())
## S3 method for class 'Sarlm'
MCMCsamp(object, mcmc = 1L, verbose = NULL, ...,
burnin=0L, scale=1, listw, listw2=NULL, control=list())
Arguments
object |
A spatial regression model object fitted by maximum likelihood with |
mcmc |
The number of MCMC iterations after burnin |
verbose |
default NULL, use global option value; if TRUE, reports progress |
... |
Arguments passed through |
burnin |
The number of burn-in iterations for the sampler |
scale |
a positive scale parameter |
listw , listw2 |
|
control |
list of extra control arguments - see |
Value
An object of class “mcmc” suited to coda, with attributes: “accept” acceptance rate; “type” input ML fitted model type “SAR”, “CAR”, “SMA”, “lag”, “mixed”, “error”, “sac”, “sacmixed”; “timings” run times
Note
If the acceptance rate is below 0.05, a warning will be issued; consider increasing mcmc.
Author(s)
Roger Bivand Roger.Bivand@nhh.no
References
Jim Albert (2007) Bayesian Computation with R, Springer, New York, pp. 104-105.
See Also
rwmetrop
, spautolm
, lagsarlm
, errorsarlm
, sacsarlm
Examples
require("sf", quietly=TRUE)
nydata <- st_read(system.file("shapes/NY8_bna_utm18.gpkg", package="spData")[1], quiet=TRUE)
suppressMessages(nyadjmat <- as.matrix(foreign::read.dbf(system.file(
"misc/nyadjwts.dbf", package="spData")[1])[-1]))
suppressMessages(ID <- as.character(names(foreign::read.dbf(system.file(
"misc/nyadjwts.dbf", package="spData")[1]))[-1]))
identical(substring(ID, 2, 10), substring(as.character(nydata$AREAKEY), 2, 10))
#require("spdep", quietly=TRUE)
listw_NY <- spdep::mat2listw(nyadjmat, as.character(nydata$AREAKEY), style="B")
esar1f <- spautolm(Z ~ PEXPOSURE + PCTAGE65P + PCTOWNHOME, data=nydata,
listw=listw_NY, family="SAR", method="eigen")
summary(esar1f)
res <- MCMCsamp(esar1f, mcmc=1000, burnin=200, listw=listw_NY)
summary(res)
## Not run:
esar1fw <- spautolm(Z ~ PEXPOSURE + PCTAGE65P + PCTOWNHOME, data=nydata,
listw=listw_NY, weights=POP8, family="SAR", method="eigen")
summary(esar1fw)
res <- MCMCsamp(esar1fw, mcmc=5000, burnin=500, listw=listw_NY)
summary(res)
ecar1f <- spautolm(Z ~ PEXPOSURE + PCTAGE65P + PCTOWNHOME, data=nydata,
listw=listw_NY, family="CAR", method="eigen")
summary(ecar1f)
res <- MCMCsamp(ecar1f, mcmc=5000, burnin=500, listw=listw_NY)
summary(res)
esar1fw <- spautolm(Z ~ PEXPOSURE + PCTAGE65P + PCTOWNHOME, data=nydata,
listw=listw_NY, weights=POP8, family="SAR", method="eigen")
summary(esar1fw)
res <- MCMCsamp(esar1fw, mcmc=5000, burnin=500, listw=listw_NY)
summary(res)
ecar1fw <- spautolm(Z ~ PEXPOSURE + PCTAGE65P + PCTOWNHOME, data=nydata,
listw=listw_NY, weights=POP8, family="CAR", method="eigen")
summary(ecar1fw)
res <- MCMCsamp(ecar1fw, mcmc=5000, burnin=500, listw=listw_NY)
summary(res)
## End(Not run)
esar0 <- errorsarlm(Z ~ PEXPOSURE + PCTAGE65P + PCTOWNHOME, data=nydata,
listw=listw_NY)
summary(esar0)
res <- MCMCsamp(esar0, mcmc=1000, burnin=200, listw=listw_NY)
summary(res)
## Not run:
esar0w <- errorsarlm(Z ~ PEXPOSURE + PCTAGE65P + PCTOWNHOME, data=nydata,
listw=listw_NY, weights=POP8)
summary(esar0)
res <- MCMCsamp(esar0w, mcmc=5000, burnin=500, listw=listw_NY)
summary(res)
esar1 <- errorsarlm(Z ~ PEXPOSURE + PCTAGE65P + PCTOWNHOME, data=nydata,
listw=listw_NY, etype="emixed")
summary(esar1)
res <- MCMCsamp(esar1, mcmc=5000, burnin=500, listw=listw_NY)
summary(res)
lsar0 <- lagsarlm(Z ~ PEXPOSURE + PCTAGE65P + PCTOWNHOME, data=nydata,
listw=listw_NY)
summary(lsar0)
res <- MCMCsamp(lsar0, mcmc=5000, burnin=500, listw=listw_NY)
summary(res)
lsar1 <- lagsarlm(Z ~ PEXPOSURE + PCTAGE65P + PCTOWNHOME, data=nydata,
listw=listw_NY, type="mixed")
summary(lsar1)
res <- MCMCsamp(lsar1, mcmc=5000, burnin=500, listw=listw_NY)
summary(res)
ssar0 <- sacsarlm(Z ~ PEXPOSURE + PCTAGE65P + PCTOWNHOME, data=nydata,
listw=listw_NY)
summary(ssar0)
res <- MCMCsamp(ssar0, mcmc=5000, burnin=500, listw=listw_NY)
summary(res)
ssar1 <- sacsarlm(Z ~ PEXPOSURE + PCTAGE65P + PCTOWNHOME, data=nydata,
listw=listw_NY, type="sacmixed")
summary(ssar1)
res <- MCMCsamp(ssar1, mcmc=5000, burnin=500, listw=listw_NY)
summary(res)
## End(Not run)