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

## Convert bkmrfit to mcmc object for coda MCMC diagnostics

### Description

Converts a `kmrfit`

(from the bkmr package) into
an `mcmc`

object from the `coda`

package. The
`coda`

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

, `traceplot`

and
`effectiveSize`

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

and `summary.mcmc`

.

### Usage

```
## S3 method for class 'bkmrfit'
as.mcmc(x, iterstart = 1, thin = 1, ...)
```

### Arguments

`x` |
object of type kmrfit (from bkmr package) |

`iterstart` |
first iteration to use (e.g. for implementing burnin) |

`thin` |
keep 1/thin % of the total iterations (at regular intervals) |

`...` |
unused |

### Value

An `mcmc`

object

### Examples

```
# following example from https://jenfb.github.io/bkmr/overview.html
set.seed(111)
library(coda)
library(bkmr)
dat <- bkmr::SimData(n = 50, M = 4)
y <- dat$y
Z <- dat$Z
X <- dat$X
set.seed(111)
fitkm <- kmbayes(y = y, Z = Z, X = X, iter = 500, verbose = FALSE,
varsel = FALSE)
mcmcobj <- as.mcmc(fitkm, iterstart=251)
summary(mcmcobj) # posterior summaries of model parameters
# compare with default from bkmr package, which omits first 1/2 of chain
summary(fitkm)
# note this only works on multiple chains (see kmbayes_parallel)
# gelman.diag(mcmcobj)
# lots of functions in the coda package to use
traceplot(mcmcobj)
# will also fail with delta functions (when using variable selection)
try(geweke.plot(mcmcobj))
```

[Package

*bkmrhat*version 1.1.3 Index]