LHZStatistic: Calculation of the Li et al. (2022) empirical characteristic...

In DataSimilarity: Quantifying Similarity of Datasets and Multivariate Two- And k-Sample Testing

Calculation of the Li et al. (2022) empirical characteristic distance

Description

The function calculates the Li et al. (2022) empirical characteristic distance

Usage

LHZStatistic(X1, X2)

Arguments

X1	First dataset as matrix
X2	Second dataset as matrix

Value

Returns the calculated value for the empirical characteristic distance

References

Li, X., Hu, W. and Zhang, B. (2022). Measuring and testing homogeneity of distributions by characteristic distance, Statistical Papers 64 (2), 529-556, \Sexpr[results=rd]{tools:::Rd_expr_doi("10.1007/s00362-022-01327-7")}

Stolte, M., Kappenberg, F., Rahnenführer, J., Bommert, A. (2024). Methods for quantifying dataset similarity: a review, taxonomy and comparison. Statist. Surv. 18, 163 - 298. \Sexpr[results=rd]{tools:::Rd_expr_doi("10.1214/24-SS149")}

See Also

LHZ

Examples

# Draw some data
X1 <- matrix(rnorm(1000), ncol = 10)
X2 <- matrix(rnorm(1000, mean = 0.5), ncol = 10)
# Calculate LHZ statistic
LHZStatistic(X1, X2)

DataSimilarity documentation built on April 3, 2025, 9:39 p.m.