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  "Title": "Nonparametric Predictive Model for Sparse and Irregular\nLongitudinal Data",
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  "Authors@R": "c(person(\"Shixuan Wang\", role = c(\"aut\", \"cre\"),\nemail = \"wangs43@miamioh.edu\"),\nperson(\"Seonjin Kim\", role = \"aut\",\nemail = \"kims20@miamioh.edu\"),\nperson(\"Hyunkeun Cho\", role = \"aut\",\nemail = \"hyunkeun-cho@uiowa.edu\"),\nperson(\"Won Chang\", role = \"aut\",\nemail = \"changwn@ucmail.uc.edu\")\n)",
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  "Description": "The proposed method aims at predicting the longitudinal\nmean response trajectory by a kernel-based estimator. The\nkernel estimator is constructed by imposing weights based on\nsubject-wise similarity on L2 metric space between predictor\ntrajectories as well as time proximity. Users could also\nperform variable selections to derive functional predictors\nwith predictive significance by the proposed multiplicative\nmodel with multivariate Gaussian kernels.",
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  "Author": "Shixuan Wang [aut, cre], Seonjin Kim [aut], Hyunkeun Cho [aut],\nWon Chang [aut]",
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