# estimate_prob: Estimate marginal and multivariate probabilities In oliviermfmartin/zebu: Local Association Measures

 estimate_prob R Documentation

## Estimate marginal and multivariate probabilities

### Description

Maximum-likelihood estimation of marginal and multivariate observed and expected independence probabilities. Marginal probability refers to probability of each factor per individual column. Multivariate probability refer to cross-classifying factors for all columns.

### Usage

``````estimate_prob(x)
``````

### Arguments

 `x` data.frame or matrix.

### Value

List containing the following values:

• margins: a list of marginal probabilities. Names correspond to colnames(x).

• observed: observed multivariate probability array.

• expected: expected multivariate probability array

### Examples

``````# This is what happens behind the curtains in the 'lassie' function
# Here we compute the association between the 'Girth' and 'Height' variables
# of the 'trees' dataset

# 'select' and 'continuous' take column numbers or names
select <- c('Girth', 'Height') # select subset of trees
continuous <-c(1, 2) # both 'Girth' and 'Height' are continuous

# equal-width discretization with 3 bins
breaks <- 3

# Preprocess data: subset, discretize and remove missing data
pre <- preprocess(trees, select, continuous, breaks)

# Estimates marginal and multivariate probabilities from preprocessed data.frame
prob <- estimate_prob(pre\$pp)

# Computes local and global association using Ducher's Z
lam <- local_association(prob, measure = 'z')
``````

oliviermfmartin/zebu documentation built on Sept. 1, 2023, 9:12 p.m.