mcmc.samples {krige} | R Documentation |
Extract MCMC Samples
Description
Extract MCMC samples estimated by metropolis.krige()
Usage
mcmc.samples(object, as.matrix, as.data.frame, ...)
## S3 method for class 'krige'
mcmc.samples(object, as.matrix = !as.data.frame, as.data.frame = FALSE, ...)
## S3 method for class 'summary.krige'
mcmc.samples(object, as.matrix = !as.data.frame, as.data.frame = FALSE, ...)
## S3 method for class 'krige'
as.matrix(x, ...)
## S3 method for class 'summary.krige'
as.matrix(x, ...)
## S3 method for class 'krige'
as.data.frame(x, ...)
## S3 method for class 'summary.krige'
as.data.frame(x, ...)
Arguments
object |
A |
as.matrix |
Logical values indicating if the output format should be a matrix. Defaults to |
as.data.frame |
Logical values indicating if the output format should be a
data.frame. Defaults to |
... |
Additional arguments passed to |
x |
A |
Details
The function extracts the MCMC samples from the a krige
or summary.krige
object from the metropolis.krige
function. Users can define the output by using as.matrix
or as.data.frame
.
Value
A summary.krige
list object.
See Also
Examples
## Not run:
# Summarize Data
summary(ContrivedData)
# Initial OLS model
contrived.ols<-lm(y~x.1+x.2,data=ContrivedData)
# summary(contrived.ols)
# Set seed
set.seed(1241060320)
M <- 100
#M<-10000
contrived.run <- metropolis.krige(y ~ x.1 + x.2, coords = c("s.1","s.2"),
data = ContrivedData, n.iter = M, n.burnin = 20, range.tol = 0.05)
contrived.run.mat <- mcmc.samples(contrived.run)
### Alternatively, use generic methods
contrived.run.mat <- as.matrix(contrived.run)
contrived.run.df <- as.data.frame(contrived.run)
## End(Not run)
[Package krige version 0.6.2 Index]