fuzzyindex {mnem} | R Documentation

## Calculate fuzzy ground truth.

### Description

Calculates responsibilities and mixture weights based on the ground truth and noisy data.

### Usage

    fuzzyindex(x, data, logtype = 2, complete = FALSE, marginal = FALSE, ...)

### Arguments

`x` | mnem_sim object
`data` | noisy data matrix
`logtype` | logarithm type of the data
`complete` | if TRUE, complete data log likelihood is considered (for very large data sets, e.g. 1000 cells and 1000 E-genes)
`marginal` | logical to compute the marginal likelihood (TRUE)
`...` | additional parameters for the function getAffinity

### Value

list with cell log odds mixture weights and log likelihood

### Author(s)

Martin Pirkl

### Examples

    sim <- simData(Sgenes = 3, Egenes = 2, Nems = 2, mw = c(0.4,0.6))
    data <- sim$data
    data[which(sim$data == 1)] <- rnorm(sum(sim$data == 1), 1, 1)
    data[which(sim$data == 0)] <- rnorm(sum(sim$data == 0), -1, 1)
    fuzzy <- fuzzyindex(sim, data)

[Package mnem version 1.8.0 Index]