Comments on: Probability Enhanced Effective Dimension Reduction for Classifying Sparse Functional Data.
نویسندگان
چکیده
In this elegant paper, F. Yao, Y. Wu, and J. Zou offer a unified treatment of the problem of classifying sparse functional data via sliced inverse regression (e.g., Li, 1991). Such signals are typically encountered in longitudinal studies and various other scientific experiments. In this setting, only a few measurements are available for some, or even all, individuals, and a cumulative slicing approach is proposed by the authors to borrow information across individuals and recover the central subspace.
منابع مشابه
Probability Enhanced Effective Dimension Reduction for Classifying Sparse Functional Data
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ورودعنوان ژورنال:
- Test
دوره 25 1 شماره
صفحات -
تاریخ انتشار 2016