{ "_id": "6ac75ff9de46216d5edcf113", "Package": "DPpack", "Type": "Package", "Title": "Differentially Private Statistical Analysis and Machine Learning", "Version": "0.2.2", "Authors@R": "c(person(\"Spencer\", \"Giddens\", email=\"giddens2spencer@gmail.com\",\nrole=c(\"aut\", \"cre\")),\nperson(\"Fang\", \"Liu\", email=\"fliu2@nd.edu\", role=c(\"ctb\")))", "Maintainer": "Spencer Giddens ", "Description": "An implementation of common statistical analysis and\nmodels with differential privacy (Dwork et al., 2006a)\n guarantees. The package contains, for\nexample, functions providing differentially private\ncomputations of mean, variance, median, histograms, and\ncontingency tables. It also implements some statistical models\nand machine learning algorithms such as linear regression\n(Kifer et al., 2012)\n and SVM\n(Chaudhuri et al., 2011)\n. 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