as.mcmc.list.bkmrfit.list {bkmrhat} | R Documentation |

## Convert multi-chain bkmrfit to mcmc.list for coda MCMC diagnostics

### Description

Converts a `kmrfit.list`

(from the bkmrhat package) into
an `mcmc.list`

object from the `coda`

package.The
`coda`

package enables many different types of MCMC diagnostics,
including `geweke.diag`

, `traceplot`

and
`effectiveSize`

. Posterior summarization is also available,
such as `HPDinterval`

and `summary.mcmc`

.
Using multiple chains is necessary for certain MCMC diagnostics, such as
`gelman.diag`

, and `gelman.plot`

.

### Usage

```
## S3 method for class 'list.bkmrfit.list'
as.mcmc(x, ...)
```

### Arguments

`x` |
object of type kmrfit.list (from bkmrhat package) |

`...` |
arguments to |

### Value

An `mcmc.list`

object

### Examples

```
# following example from https://jenfb.github.io/bkmr/overview.html
set.seed(111)
library(coda)
dat <- bkmr::SimData(n = 50, M = 4)
y <- dat$y
Z <- dat$Z
X <- dat$X
set.seed(111)
future::plan(strategy = future::multisession, workers=2)
# run 2 parallel Markov chains (more usually better)
fitkm.list <- kmbayes_parallel(nchains=2, y = y, Z = Z, X = X, iter = 1000,
verbose = FALSE, varsel = FALSE)
mcmcobj = as.mcmc.list(fitkm.list)
summary(mcmcobj)
# Gelman/Rubin diagnostics won't work on certain objects,
# like delta parameters (when using variable selection),
# so the rstan version of this will work better (does not give errors)
try(gelman.diag(mcmcobj))
# lots of functions in the coda package to use
plot(mcmcobj)
# both of these will also fail with delta functions (when using variable selection)
try(gelman.plot(mcmcobj))
try(geweke.plot(mcmcobj))
closeAllConnections()
```

[Package

*bkmrhat*version 1.1.3 Index]