getSliceSamples: getSliceSamples
In petedodd/MCIR: Monte Carlo Inference Routines: A Collection of Generic Algorithms for Bayesian Inference
Description
Usage
Arguments
Details
Value
Author(s)
Examples
Description
Function to run automated-factor slice sampling
Usage
1
2
getSliceSamples(LL, x0, nBurnin = 10 * 1024, nSample = 10000,
verbose = FALSE, useFactor = TRUE, useTrueFactors = FALSE)
Arguments
LL
the loglikelihood function
x0
a vector specifying the start for the chain
Details
todo: more about provenance and optional arguments...
Value
a matrix with columns as parameters and rows as post-burnin samples
Author(s)
Pete Dodd
Examples
1
2
3
rosen <- function(x) -(1-x[1])^2 - 100*(x[2] - x[1]^2)^2
runss <- getSliceSamples(LL=arosen,x0=c(0,0),useFactor=TRUE)
corplot(runss)
petedodd/MCIR documentation built on Jan. 9, 2020, 9:18 a.m.
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Description Usage Arguments Details Value Author(s) Examples
Description
Function to run automated-factor slice sampling
Usage
1 2 | getSliceSamples(LL, x0, nBurnin = 10 * 1024, nSample = 10000,
verbose = FALSE, useFactor = TRUE, useTrueFactors = FALSE)
|
Arguments
LL |
the loglikelihood function |
x0 |
a vector specifying the start for the chain |
Details
todo: more about provenance and optional arguments...
Value
a matrix with columns as parameters and rows as post-burnin samples
Author(s)
Pete Dodd
Examples
1 2 3 | rosen <- function(x) -(1-x[1])^2 - 100*(x[2] - x[1]^2)^2
runss <- getSliceSamples(LL=arosen,x0=c(0,0),useFactor=TRUE)
corplot(runss)
|
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
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