chances {binda} R Documentation

## Estimate Bernoulli Parameters from Binary Matrix with Class Labels

### Description

`chances` estimates Bernoulli parameters (=chances) from a binary matrix and associated class labels.

### Usage

```chances(X, L, lambda.freqs, verbose=TRUE)
```

### Arguments

 `X` data matrix (columns correspond to variables, rows to samples). `L` factor containing the class labels, one for each sample (row). `lambda.freqs` shrinkage parameter for class frequencies (if not specified it is estimated). `verbose` report shrinkage intensity and other information.

### Details

The class-specific chances are estimated using the empirical means over the 0s and 1s in each class. For estimating the pooled mean the class-specific means are weighted using the estimated class frequencies. Class frequencies are estimated using `freqs.shrink`.

### Value

`chances` returns a list with the following components:

`samples`: the samples in each class,

`regularization`: the shrinkage intensity used to estimate the class frequencies,

`freqs`: the estimated class frequencies,

`means`: the estimated chances (parameters of Bernoulli distribution, expectations of 1s) for each variable conditional on class, as well as the marginal changes (pooled means).

### Author(s)

Sebastian Gibb and Korbinian Strimmer (https://strimmerlab.github.io).

`is.binaryMatrix`.

### Examples

```# load binda library
library("binda")

# example binary matrix with 6 variables (in columns) and 4 samples (in rows)
Xb = matrix(c(1, 1, 0, 1, 0, 0,
1, 1, 1, 1, 0, 0,
1, 0, 0, 0, 1, 1,
1, 0, 0, 0, 1, 1), nrow=4, byrow=TRUE)
colnames(Xb) = paste0("V", 1:ncol(Xb))

# Test for binary matrix
is.binaryMatrix(Xb) # TRUE

L = factor(c("Treatment", "Treatment", "Control", "Control") )

chances(Xb, L)
```

[Package binda version 1.0.4 Index]