summary.kmm: Extract summary from 'kmm' object, including two-sample...

In densityratio: Distribution Comparison Through Density Ratio Estimation

Extract summary from kmm object, including two-sample significance test for homogeneity of the numerator and denominator samples

Description

Extract summary from kmm object, including two-sample significance test for homogeneity of the numerator and denominator samples

Usage

## S3 method for class 'kmm'
summary(
  object,
  test = FALSE,
  n_perm = 100,
  parallel = FALSE,
  cluster = NULL,
  min_pred = 1e-06,
  ...
)

Arguments

object	Object of class kmm
test	logical indicating whether to statistically test for homogeneity of the numerator and denominator samples.
n_perm	Scalar indicating number of permutation samples
parallel	logical indicating to run the permutation test in parallel
cluster	NULL or a cluster object created by makeCluster. If NULL and parallel = TRUE, it uses the number of available cores minus 1.
min_pred	Scalar indicating the minimum value for the predicted density ratio values (used in the divergence statistic) to avoid negative density ratio values.
...	further arguments passed to or from other methods.

Value

Summary of the fitted density ratio model

Examples

set.seed(123)
# Fit model
dr <- kmm(numerator_small, denominator_small)
# Inspect model object
dr
# Obtain summary of model object
summary(dr)
# Plot model object
plot(dr)
# Plot density ratio for each variable individually
plot_univariate(dr)
# Plot density ratio for each pair of variables
plot_bivariate(dr)
# Predict density ratio and inspect first 6 predictions
head(predict(dr))
# Fit model with custom parameters
kmm(numerator_small, denominator_small,
    nsigma = 5, ncenters = 100, nfold = 10,
    constrained = TRUE)

densityratio documentation built on June 8, 2025, 11:17 a.m.