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Additive Models for Longitudinal Data with Application to KLIPS

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Authors
김민정
Advisor
박병욱
Major
자연과학대학 통계학과
Issue Date
2014-02
Publisher
서울대학교 대학원
Keywords
Additive modelSmooth backfittingKernel smoothingLongitudinal dataKLIPS.
Description
학위논문 (석사)-- 서울대학교 대학원 : 통계학과, 2014. 2. 박병욱.
Abstract
Many studies have taken to construct models between time-varying variables for longitudinal data. These longitudinal models are widely used in physics, biology and social sciences. In this paper, we introduce a time-varying additive model with smooth backfitting to overcome the limitations of parametric model. This modeling strategy allows us to provide dimension reduction and simultaneously retain flexibility of regression function. Furthermore, an application to Korean Labor and Income Panel Study (KLIPS) data is presented to illustrate the proposed methodologies. This model might be quite useful to fit a data and gives a good explanation on social phenomenon.
Language
English
URI
https://hdl.handle.net/10371/131276
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College of Natural Sciences (자연과학대학)Dept. of Statistics (통계학과)Theses (Master's Degree_통계학과)
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