sample_tmb_rwm {adnuts} | R Documentation |

## [Deprecated] Draw MCMC samples from a model posterior using a Random Walk Metropolis (RWM) sampler.

### Description

[Deprecated] Draw MCMC samples from a model posterior using a Random Walk Metropolis (RWM) sampler.

### Usage

```
sample_tmb_rwm(
iter,
fn,
init,
alpha = 1,
chain = 1,
warmup = floor(iter/2),
thin = 1,
seed = NULL,
control = NULL
)
```

### Arguments

`iter` |
The number of samples to draw. |

`fn` |
A function that returns the log of the posterior density. |

`init` |
A list of lists containing the initial parameter
vectors, one for each chain or a function. It is strongly
recommended to initialize multiple chains from dispersed
points. A of NULL signifies to use the starting values
present in the model (i.e., |

`alpha` |
The amount to scale the proposal, i.e,
Xnew=Xcur+alpha*Xproposed where Xproposed is generated from a mean-zero
multivariate normal. Varying |

`chain` |
The chain number, for printing only. |

`warmup` |
The number of warmup iterations. |

`thin` |
The thinning rate to apply to samples. Typically not used with NUTS. |

`seed` |
The random seed to use. |

`control` |
A list to control the sampler. See details for further use. |

### Details

This algorithm does not yet contain adaptation of `alpha`

so some trial and error may be required for efficient sampling.

### Value

A list containing samples and other metadata.

### References

Metropolis, N., Rosenbluth, A.W., Rosenbluth, M.N., Teller, A.H., Teller, E., 1953. Equation of state calculations by fast computing machines. J Chem Phys. 21:1087-1092.

### See Also

*adnuts*version 1.1.2 Index]