Description Usage Arguments Details Slots See Also

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).

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 | ```
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)
``` |

`object` |
An instance of appropriate class. |

`x` |
Object to be subset. |

`i` |
An |

`j` |
Missing. |

`drop` |
Missing. |

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.

`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.

The function `tagmMcmcTrain()`

to construct object of
this class.

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