{ "_id": "6a1040a7acfb0bcc41c9d2c1", "Package": "krm", "LazyLoad": "yes", "LazyData": "yes", "Version": "2022.10-17", "Title": "Kernel Based Regression Models", "Authors@R": "c(person(\"Youyi\", \"Fong\", role = \"cre\", email = \"youyifong@gmail.com\"), person(\"Saheli\", \"Datta\", role = \"aut\", email = \"saheli8@gmail.com\"), person(\"Krisztian\", \"Sebestyen\", role = \"aut\", email = \"ksebestyen@gmail.com\"), person(\"Steve\", \"Park\", role = \"ctb\"), person(\"Dave\", \"Geyer\", role = \"ctb\"))", "Description": "Implements several methods for testing the variance\ncomponent parameter in regression models that contain\nkernel-based random effects, including a maximum of adjusted\nscores test. Several kernels are supported, including a profile\nhidden Markov model mutual information kernel for protein\nsequence. This package is described in Fong et al. 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