Package: KMD
Type: Package
Title: Kernel Measure of Multi-Sample Dissimilarity
Version: 0.1.1
Authors@R: 
    person("Zhen", "Huang", , "zh2395@columbia.edu", role = c("aut", "cre"))
Maintainer: Zhen Huang <zh2395@columbia.edu>
Description: Implementations of the kernel measure of multi-sample
        dissimilarity (KMD) between several samples using K-nearest
        neighbor graphs and minimum spanning trees. The KMD measures
        the dissimilarity between multiple samples, based on the
        observations from them. It converges to the population quantity
        (depending on the kernel) which is between 0 and 1. A small
        value indicates the multiple samples are from the same
        distribution, and a large value indicates the corresponding
        distributions are different. The population quantity is 0 if
        and only if all distributions are the same, and 1 if and only
        if all distributions are mutually singular. The package also
        implements the tests based on KMD for H0: the M distributions
        are equal against H1: not all the distributions are equal. Both
        permutation test and asymptotic test are available. These tests
        are consistent against all alternatives where at least two
        samples have different distributions. For more details on KMD
        and the associated tests, see Huang, Z. and B. Sen (2024)
        <doi:10.1080/01621459.2023.2298036>.
License: GPL-3
Encoding: UTF-8
RoxygenNote: 7.3.3
Depends: R (>= 4.5.0), data.table
Imports: RANN, proxy, mlpack, boot, igraph
Config/pak/sysreqs: libglpk-dev libxml2-dev
Repository: https://zh2395.r-universe.dev
Date/Publication: 2026-07-10 02:05:29 UTC
RemoteUrl: https://github.com/zh2395/kmd
RemoteRef: HEAD
RemoteSha: 70403a838a20c6cacac1d8759b1d08faf877a981
NeedsCompilation: no
Packaged: 2026-10-08 08:08:34 UTC; root
Author: Zhen Huang [aut, cre]
