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Summary Method for Prototype Computation Objects

Source: R/computations.R
summary.prototypeComputation.Rd

Computes and returns comprehensive summary statistics for a prototypeComputation object, including marginal and conditional probabilities for both categories and features. This provides a complete statistical overview of the prototype model results.

Usage

# S3 method for class 'prototypeComputation'
summary(object, s = 500, ...)

Arguments

object

A prototypeComputation object created by compute.

s

Integer. Number of draws to sample from the probabilities for computing conditional probabilities. Default is 500. Higher values provide more stable estimates.

...

Additional arguments (currently unused).

Value

A summary.prototypeComputation object containing:

marginal

List with marginal probabilities:

  • categories: Vector of category marginal probabilities

  • features: Vector of feature marginal probabilities

conditional

List with conditional probabilities:

  • categories: P(C|X) for feature values 0 and 1

  • features: P(X|C) matrix

Details

The summary provides four key probability distributions:

  • Category Marginals: Overall probability of each category across all observations

  • Feature Marginals: Overall probability of each feature being 1 across all observations

  • Conditional Features: P(X_k = 1 | C_j) for each feature k and category j

  • Conditional Categories: P(C_j | X_k = 0) and P(C_j | X_k = 1) for each category j and feature k

See also

conditionalProbs, compute