Time-dynamic varying coefficient models for longitudinal data
Autor: | Byeong U. Park, Kyeong Eun Lee, Young Kyung Lee, Seong J. Yang |
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Rok vydání: | 2018 |
Předmět: |
Statistics and Probability
010504 meteorology & atmospheric sciences Longitudinal data Applied Mathematics Asymptotic distribution Estimator Function (mathematics) Conditional expectation 01 natural sciences 010104 statistics & probability Computational Mathematics Computational Theory and Mathematics Sample size determination Convergence (routing) Kernel smoother Applied mathematics 0101 mathematics 0105 earth and related environmental sciences Mathematics |
Zdroj: | Computational Statistics & Data Analysis. 123:50-65 |
ISSN: | 0167-9473 |
Popis: | A new varying coefficient model that relates functional response to functional predictors is proposed and studied. The model accommodates the influence of the functional predictors on the time-varying coefficient functions. A powerful kernel smoothing technique is developed for estimating the model with longitudinal observations of the functional response and predictors. The method involves a backfitting iteration that is based on alternating conditional expectation. The convergence of the algorithm is established and the asymptotic distribution of the coefficient function estimators is derived. It is shown that the method works well for finite sample sizes via simulation studies. The proposed model and method are also applied to analyzing an air quality dataset. |
Databáze: | OpenAIRE |
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