{ "_id": "6abccd3b99f7aa8c6aa4bf69", "Package": "HDLSSkST", "Type": "Package", "Title": "Distribution-Free Exact High Dimensional Low Sample Size\nk-Sample Tests", "Version": "2.1.0", "Date": "2022-02-01", "Authors@R": "c(person(\"Biplab\", \"Paul\", role = c(\"aut\", \"cre\"), email = \"paul.biplab497@gmail.com\"),\nperson(\"Shyamal K.\", \"De\", role = c(\"aut\")),\nperson(\"Anil K.\", \"Ghosh\", role = c(\"aut\")))", "Maintainer": "Biplab Paul ", "Description": "Testing homogeneity of k multivariate distributions is a\nclassical and challenging problem in statistics, and this\nbecomes even more challenging when the dimension of the data\nexceeds the sample size. We construct some tests for this\npurpose which are exact level (size) alpha tests based on\nclustering. These tests are easy to implement and\ndistribution-free in finite sample situations. Under\nappropriate regularity conditions, these tests have the\nconsistency property in HDLSS asymptotic regime, where the\ndimension of data grows to infinity while the sample size\nremains fixed. We also consider a multiscale approach, where\nthe results for different number of partitions are aggregated\njudiciously. Details are in Biplab Paul, Shyamal K De and Anil\nK Ghosh (2021) ; Soham Sarkar\nand Anil K Ghosh (2019) ;\nWilliam M Rand (1971) ;\nCyrus R Mehta and Nitin R Patel (1983) ;\nJoseph C Dunn (1973) ; Sture\nHolm (1979) ; Yoav Benjamini and Yosef\nHochberg (1995) .", "License": "GPL (>= 2)", "Author": "Biplab Paul [aut, cre], Shyamal K. De [aut], Anil K. 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