MCMCChains-class {pRoloc} | R Documentation

## Instrastructure to store and process MCMC results

### Description

The `MCMCParams` infrastructure is used to store and process Marchov chain Monte Carlo results for the T-Augmented Gaussian Mixture model (TAGM) from Crook et al. (2018).

### Usage

    chains(object)

    ## S4 method for signature 'MCMCParams'
    show(object)

    ## S4 method for signature 'ComponentParam'
    show(object)

    ## S4 method for signature 'MCMCChain'
    show(object)

    ## S4 method for signature 'MCMCChains'
    length(x)

    ## S4 method for signature 'MCMCParams'
    length(x)

    ## S4 method for signature 'MCMCChains,ANY,ANY'
    x[[i, j = "missing",
      drop = "missing"]]

    ## S4 method for signature 'MCMCParams,ANY,ANY'
    x[[i, j = "missing",
      drop = "missing"]]

    ## S4 method for signature 'MCMCChains,ANY,ANY,ANY'
    x[i, j = "missing",
      drop = "missing"]

    ## S4 method for signature 'MCMCParams,ANY,ANY,ANY'
    x[i, j = "missing",
      drop = "missing"]

    ## S4 method for signature 'MCMCChains'
    show(object)

### Arguments

`object` | An instance of appropriate class.
`x` | Object to be subset.
`i` | An `integer()`. Should be of length 1 for `[[`.
`j` | Missing.
`drop` | Missing.

### Details

Objects of the `MCMCParams` class are created with the `tagmMcmcTrain()` function. These objects store the priors of the generative TAGM model and the results of the MCMC chains, which themselves are stored as an instance of class `MCMCChains` and can be accessed with the `chains()` function. A summary of the MCMC chains (or class `MCMCSummary`) can be further computed with the `tagmMcmcProcess()` function.

See the pRoloc-bayesian vignette for examples.

### Slots

`chains`

  `list()` containing the individual full MCMC chain results in an `MCMCChains` instance. Each element must be a valid `MCMCChain` instance.

`posteriorEstimates`

  A `data.frame` documenting the prosterior priors in an `MCMCSummary` instance. It contains N rows and columns `tagm.allocation`, `tagm.probability`, `tagm.outlier`, `tagm.probability.lowerquantile`, `tagm.probability.upperquantile` and `tagm.mean.shannon`.

`diagnostics`

  A `matrix` of dimensions 1 by 2 containing the `MCMCSummary` diagnostics.

`tagm.joint`

  A `matrix` of dimensions N by K storing the joint probability in an `MCMCSummary` instance.

`method`

  `character(1)` describing the method in the `MCMCParams` object.

`chains`

  Object of class `MCMCChains` containing the full MCMC chain results stored in the `MCMCParams` object.

`priors`

  `list()`

`summary`

  Object of class `MCMCSummary` the summarised MCMC results available in the `MCMCParams` instance.

`n`

  `integer(1)` indicating the number of MCMC interactions. Stored in an `MCMCChain` instance.

`K`

  `integer(1)` indicating the number of components. Stored in an `MCMCChain` instance.

`N`

  `integer(1)` indicating the number of proteins. Stored in an `MCMCChain` instance.

`Component`

  `matrix(N, n)` component allocation results of an `MCMCChain` instance.

`ComponentProb`

  `matrix(N, n, K)` component allocation probabilities of an `MCMCChain` instance.

`Outlier`

  `matrix(N, n)` outlier allocation results.

`OutlierProb`

  `matrix(N, n, 2)` outlier allocation probabilities of an `MCMCChain` instance.

### See Also

The function `tagmMcmcTrain()` to construct object of this class.

[Package pRoloc version 1.30.0 Index]