fuzzyindex: Calculate fuzzy ground truth.

In cbg-ethz/mnem: Mixture Nested Effects Models

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)

cbg-ethz/mnem documentation built on Nov. 7, 2024, 7:35 p.m.