estimate_prob {zebu} | R Documentation |
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.
estimate_prob(x)
x |
data.frame or matrix. |
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
# 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')