Varying coefficient models for data with auto-correlated error process
نویسندگان
چکیده
منابع مشابه
Varying Coefficient Models for Data with Auto-correlated Error Process.
Varying coefficient model has been popular in the literature. In this paper, we propose a profile least squares estimation procedure to its regression coefficients when its random error is an auto-regressive (AR) process. We further study the asymptotic properties of the proposed procedure, and establish the asymptotic normality for the resulting estimate. We show that the resulting estimate fo...
متن کاملOnline Supplemental Appendix for VARYING COEFFICIENT MODELS FOR DATA WITH AUTO-CORRELATED ERROR PROCESS
with et = (ε̂t−1, . . . , ε̂t−d) T , where ε̂t is the estimated residual in the initial step when the profile least squares method is implemented. Define ∆ = E− F. Our proof follows a similar strategy to that used in Fan and Huang (2005) and Li and Li (2009). Note that the proof of Fan and Huang (2005) is for iid data, and the proof of Li and Li (2009) is for nonparametric regression models rather...
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tion (DMS-08-06199). We are grateful to two referees and an Associate Editor for their constructive comments and careful reading. Summary The proposed functional varying coefficient model provides a versatile and flexible analysis tool for relating longitudinal responses to longitudinal predictors. Specifically , this approach provides a novel representation of varying coefficient functions thr...
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We propose a generalization of the varying coefficient model for longitudinal data to cases where not only current but also recent past values of the predictor process affect current response. More precisely, the targeted regression coefficient functions of the proposed model have sliding window supports around current time t. A variant of a recently proposed two-step estimation method for vary...
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Abstract Both varying-coefficient and additive models have been studied extensively in the literature as extensions to linear models. They have also been extended to functional response data. However, existing extensions are still not sufficiently flexible to reflect the functional feature of the responses. In this paper, we extend both varying-coefficient and additive models to a much more fle...
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ژورنال
عنوان ژورنال: Statistica Sinica
سال: 2015
ISSN: 1017-0405
DOI: 10.5705/ss.2012.301