monitor | R Documentation |

Similar to the `print`

method for `stanfit`

objects, but `monitor`

takes an array of simulations as its argument rather than a `stanfit`

object. For a 3-D array (iterations * chains * parameters) of MCMC draws,
`monitor`

computes means, standard deviations, quantiles, Monte Carlo
standard errors, split Rhats, and effective sample sizes. By default, half of
the iterations are considered warmup and are excluded.

monitor(sims, warmup = floor(dim(sims)[1]/2), probs = c(0.025, 0.25, 0.5, 0.75, 0.975), digits_summary = 1, print = TRUE, ...) ## S3 method for class 'simsummary' print(x, digits = 3, se = FALSE, ...) ## S3 method for class 'simsummary' x[i, j, drop = if (missing(i)) TRUE else length(j) == 1]

`sims` |
A 3-D array (iterations * chains * parameters) of MCMC simulations from any MCMC algorithm. |

`warmup` |
The number of warmup iterations to be excluded
when computing the summaries. The default is half of the total number
of iterations. If |

`probs` |
A numeric vector specifying quantiles of interest. The
defaults is |

`digits_summary` |
The number of significant digits to use when printing the summary, defaulting to 1. Applies to the quantities other than the effective sample size, which is always rounded to the nearest integer. |

`print` |
Logical, indicating whether to print the summary after the computations are performed. |

`...` |
Additional arguments passed to the underlying |

`x` |
An object of class |

`digits` |
An integer scalar defaulting to 3 for the number of decimal places to print |

`se` |
A logical scalar defaulting to |

`i` |
A vector indicating which rows of the object created by |

`j` |
A vector indicating which columns of the object crated by |

`drop` |
A logical scalar indicating whether the resulting object should return a vector where possible |

A 2-D array with rows corresponding to parameters and columns to the summary statistics that can be printed and subset.

The Stan Development Team
*Stan Modeling Language User's Guide and Reference Manual*.
https://mc-stan.org.

S4 class `stanfit`

and particularly its
`print`

method.

csvfiles <- dir(system.file('misc', package = 'rstan'), pattern = 'rstan_doc_ex_[0-9].csv', full.names = TRUE) fit <- read_stan_csv(csvfiles) # The following is just for the purpose of giving an example # since print can be used for a stanfit object. monitor(extract(fit, permuted = FALSE, inc_warmup = TRUE))

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