mcmc-helpers: Number of outlier at each iteration of MCMC
In lgatto/pRoloc: A unifying bioinformatics framework for spatial proteomics

mcmc_get_outliers

R Documentation

Number of outlier at each iteration of MCMC

Description

Helper function to get the number of outlier at each MCMC iteration.

Helper function to get mean component allocation at each MCMC iteration.

Helper function to get mean probability of belonging to outlier at each iteration.

Wrapper for the geweke diagnostics from coda package also return p-values.

Helper function to pool chains together after processing

Helper function to burn n iterations from the front of the chains

Helper function to subsample the chains, known informally as thinning.

Produces a violin plot with the protein posterior probabilities distributions for all organelles.

Usage

mcmc_get_outliers(x)

mcmc_get_meanComponent(x)

mcmc_get_meanoutliersProb(x)

geweke_test(k)

mcmc_pool_chains(param)

mcmc_burn_chains(x, n = 50)

mcmc_thin_chains(x, freq = 5)

## S4 method for signature 'MCMCParams,character'
plot(x, y, ...)

Arguments

`x`	Object of class `MCMCParams`
`k`	A `list` of coda::mcmc objects, as returned by `mcmc_get_outliers`, `mcmc_get_meanComponent` and `mcmc_get_meanoutliersProb`.
`param`	An object of class `MCMCParams`.
`n`	`integer(1)` defining number of iterations to burn. The default is `50`
`freq`	Thinning frequency. The function retains every 'freq'th iteration and is an 'integer(1)'. The default thinning frequency is '5'.
`y`	A 'character(1)' with a protein name.
`...`	Currently ignored.