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- W2183637897 abstract "Here we develop methods for applications where random change points are known to be present a priori and the interest lies in their esti- mation and investigating risk factors that influence them. A simple least- square method estimating each individual's change point based on one's own observations is first proposed. An easy-to-compute empirical Bayes type shrinkage is then proposed to pool information from separately esti- mated change points. A method to improve the empirical Bayes estimates is developed. Simulations are conducted to compare least-square estimates and Bayes shrinkage estimates. The proposed methods are applied to the Berkeley Growth Study data to estimate the transition age of the puberty height growth." @default.
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- W2183637897 date "2021-07-10" @default.
- W2183637897 modified "2023-09-24" @default.
- W2183637897 title "Least square and Empirical Bayes Approaches for Estimating Random Change Points" @default.
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- W2183637897 doi "https://doi.org/10.6339/jds.200901_07(1).0001" @default.
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