Correction to "Inverse regression for longitudinal data"
نویسندگان
چکیده
منابع مشابه
A New Nonparametric Regression for Longitudinal Data
In many area of medical research, a relation analysis between one response variable and some explanatory variables is desirable. Regression is the most common tool in this situation. If we have some assumptions for such normality for response variable, we could use it. In this paper we propose a nonparametric regression that does not have normality assumption for response variable and we focus ...
متن کاملExtension of Logic regression to Longitudinal data: Transition Logic Regression
Logic regression is a generalized regression and classification method that is able to make Boolean combinations as new predictive variables from the original binary variables. Logic regression was introduced for case control or cohort study with independent observations. Although in various studies, correlated observations occur due to different reasons, logic regression have not been studi...
متن کاملInverse Regression from Longitudinal Data
Inverse regression, or statistical calibration, uses the estimated relationship between a response Y and a covariate x to infer the values of unknown x’s from their observed Y’s. Typically x is univariate but Y may be multivariate. A brief review of the basic theory will be given, followed by consideration of the problems involved in extending these approaches to longitudinal data, i.e. where t...
متن کاملa new nonparametric regression for longitudinal data
in many area of medical research, a relation analysis between one response variable and some explanatory variables is desirable. regression is the most common tool in this situation. if we have some assumptions for such normality for response variable, we could use it. in this paper we propose a nonparametric regression that does not have normality assumption for response variable and we focus ...
متن کاملINVERSE REGRESSION FOR LONGITUDINAL DATA By Ci - Ren Jiang
Sliced inverse regression (Duan and Li (1991), Li (1991)) is an appealing dimension reduction method for regression models with multivariate covariates. It has been extended by Ferré and Yao (2003, 2005) and Hsing and Ren (2009) to functional covariates where the whole trajectories of random functional covariates are completely observed. The focus of this paper is to develop sliced inverse regr...
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ژورنال
عنوان ژورنال: The Annals of Statistics
سال: 2015
ISSN: 0090-5364
DOI: 10.1214/15-aos1326