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Variance Change Point Detection Under a Smoothly-Changing Mean Trend with Application to Liver Procurement

平滑变化均值趋势下的方差变点检测及肝脏获取应用

Literature on change point analysis mostly requires a sudden change in the data distribution, either in a few parameters or the distribution as a whole. We are interested in the scenario, where the variance of data may make a significant jump while the mean changes in a smooth fashion. The motivation is a liver procurement experiment monitoring organ surface temperature. Blindly applying the existing methods to the example can yield erroneous change point estimates since the…

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Optimal Penalized Function-on-Function Regression Under a Reproducing Kernel Hilbert Space Framework

再生核希尔伯特空间下的最优惩罚函数对函数回归

Many scientific studies collect data where the response and predictor variables are both functions of time, location, or some other covariate. Understanding the relationship between these functional variables is a common goal in these studies. Motivated from two real-life examples, we present in this paper a function-on-function regression model that can be used to analyze such kind of functional data. Our estimator of the 2D coefficient function is the optimizer of a form…

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Penalized variable selection procedure for Cox models with semiparametric relative risk

半参数相对风险Cox模型的惩罚变量选择

We study the Cox models with semiparametric relative risk, which can be partially linear with one nonparametric component, or multiple additive or nonadditive nonparametric components. A penalized partial likelihood procedure is proposed to simultaneously estimate the parameters and select variables for both the parametric and the nonparametric parts. Two penalties are applied sequentially. The first penalty, governing the smoothness of the multivariate nonlinear covariate…

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