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  "Title": "Variational Inference for High-Dimensional Joint Frailty Model",
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  "Description": "Joint frailty models have been widely used to study the\nassociations between recurrent events and a survival outcome.\nHowever, existing joint frailty models only consider one or a\nfew recurrent events and cannot deal with high-dimensional\nrecurrent events. This package can be used to fit our recently\ndeveloped penalized joint frailty model that can handle\nhigh-dimensional recurrent events. Specifically, an adaptive\nlasso penalty is imposed on the parameters for the effects of\nthe recurrent events on the survival outcome, which allows for\nvariable selection. Also, our algorithm is computationally\nefficient, which is based on the Gaussian variational\napproximation method.",
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  "Author": "Jiehuan Sun [aut, cre]",
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