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  "Description": "Our recently developed fully robust Bayesian\nsemiparametric mixed-effect model for high-dimensional\nlongitudinal studies with heterogeneous observations can be\nimplemented through this package. This model can distinguish\nbetween time-varying interactions and constant-effect-only\ncases to avoid model misspecifications. Facilitated by\nspike-and-slab priors, this model leads to superior performance\nin estimation, identification and statistical inference. In\nparticular, robust Bayesian inferences in terms of valid\nBayesian credible intervals on both parametric and\nnonparametric effects can be validated on finite samples. The\nMarkov chain Monte Carlo algorithms of the proposed and\nalternative models are efficiently implemented in 'C++'.",
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