{ "_id": "6a269bb824555f66ed51eb70", "Package": "catch", "Title": "Covariate-Adjusted Tensor Classification in High-Dimensions", "Version": "1.0.1", "Description": "Performs classification and variable selection on\nhigh-dimensional tensors (multi-dimensional arrays) after\nadjusting for additional covariates (scalar or vectors) as\nCATCH model in Pan, Mai and Zhang (2018) .\nThe low-dimensional covariates and the high-dimensional tensors\nare jointly modeled to predict a categorical outcome in a\nmulti-class discriminant analysis setting. The\nCovariate-Adjusted Tensor Classification in High-dimensions\n(CATCH) model is fitted in two steps: (1) adjust for the\ncovariates within each class; and (2) penalized estimation with\nthe adjusted tensor using a cyclic block coordinate descent\nalgorithm. The package can provide a solution path for tuning\nparameter in the penalized estimation step. Special case of the\nCATCH model includes linear discriminant analysis model and\nmatrix (or tensor) discriminant analysis without covariates.", "License": "GPL-2", "Encoding": "UTF-8", "LazyData": "true", "NeedsCompilation": "yes", "Packaged": { "Date": "2026-06-08 10:36:05 UTC", "User": "root" }, "Author": "Yuqing Pan , Qing Mai\n, Xin Zhang ", "Maintainer": "Yuqing Pan ", "Repository": "https://cran.r-universe.dev", "Date/Publication": "2021-01-04 16:10:02 UTC", "RemoteUrl": "https://github.com/cran/catch", "RemoteRef": "HEAD", "RemoteSha": "6bf45e82eaa2069c4e4dd077e24bc8403d4140be", "MD5sum": "cbb68dc80a028c457c52f1c272f006db", "_user": "cran", "_type": "src", "_file": "catch_1.0.1.tar.gz", "_fileid": "73c070cc78a18dfb3f685be27a01b85408816eb719ff9be837cd6b2d6748b8c3", "_filesize": 399515, "_sha256": "73c070cc78a18dfb3f685be27a01b85408816eb719ff9be837cd6b2d6748b8c3", "_created": "2026-06-08T10:36:05.000Z", "_published": "2026-06-08T10:38:48.774Z", "_distro": "noble", "_jobs": [ { 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