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  "Title": "Nonparametric Statistics",
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  "Author": "JiaSheng Zhang [aut,cre] (<zhangjiasheng0509@outlook.com>),\nSiWei Deng [aut], Feng Yu [aut], YangYang Zhang [aut]",
  "Maintainer": "JiaSheng Zhang <zhangjiasheng0509@outlook.com>",
  "Description": "We unify various nonparametric hypothesis testing problems\nin a framework of permutation testing, enabling hypothesis\ntesting on multi-sample, multidimensional data and contingency\ntables. Most of the functions available in the R environment to\nimplement permutation tests are single functions constructed\nfor specific test problems; to facilitate the use of the\npackage, the package encapsulates similar tests in a\ncategorized manner, greatly improving ease of use. We will all\nprovide functions for self-selected permutation scoring methods\nand self-selected p-value calculation methods (asymptotic,\nexact, and sampling). For two-sample tests, we will provide\nmean tests and estimate drift sizes; we will provide tests on\nvariance; we will provide paired-sample tests; we will provide\ncorrelation coefficient tests under three measures. For\nmulti-sample problems, we will provide both ordinary and\nordered alternative test problems. For multidimensional data,\nwe will implement multivariate means (including ordered\nalternatives) and multivariate pairwise tests based on four\nstatistics; the components with significant differences are\nalso calculated. For contingency tables, we will perform\npermutation chi-square test or ordered alternative.",
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  "Encoding": "UTF-8",
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