Functional Varying Coefficient Model with Time-independent Covariate and Longitudinal Response
نویسندگان
چکیده
منابع مشابه
Functional random effect time-varying coefficient model for longitudinal data.
We propose a functional random effect time-varying coefficient model to establish the dynamic relationship between the response and predictor variables in longitudinal data. This model allows us not only to interpret time-varying covariate effects, but also to depict random effects via time-varying profiles that are characterized by functional principal components. We develop the functional pro...
متن کاملCovariate-adjusted varying coefficient models.
Covariate-adjusted regression was recently proposed for situations where both predictors and response in a regression model are not directly observed, but are observed after being contaminated by unknown functions of a common observable covariate. The method has been appealing because of its flexibility in targeting the regression coefficients under different forms of distortion. We extend this...
متن کاملFunctional varying coefficient models for longitudinal data
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...
متن کاملRobust Inference for Time-Varying Coefficient Models with Longitudinal Data
Time-varying coefficient models are useful in longitudinal data analysis. Various efforts have been invested for the estimation of the coefficient functions, based on the least squares principle. Related work includes smoothing spline and kernel methods among others, but these methods suffer from the shortcoming of non-robustness. In this paper, we introduce a local M-estimation method for esti...
متن کاملMultivariate Varying Coefficient Model for Functional Responses.
Motivated by recent work studying massive imaging data in the neuroimaging literature, we propose multivariate varying coefficient models (MVCM) for modeling the relation between multiple functional responses and a set of covariates. We develop several statistical inference procedures for MVCM and systematically study their theoretical properties. We first establish the weak convergence of the ...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: Journal of Data Science
سال: 2021
ISSN: 1680-743X,1683-8602
DOI: 10.6339/jds.201507_13(3).0002