Penalized quadratic inference functions for single-index models with longitudinal data

نویسندگان
چکیده

برای دانلود باید عضویت طلایی داشته باشید

برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

منابع مشابه

Penalized quadratic inference functions for single-index models with longitudinal data

In this paper, we focus on single-index models for longitudinal data. We propose a procedure to estimate the single-index component and the unknown link function based on the combination of the penalized splines and quadratic inference functions. It is shown that the proposed estimation method has good asymptotic properties. We also evaluate the finite sample performance of the proposed method ...

متن کامل

Quadratic inference functions for partially linear single-index models with longitudinal data

AMS 2000 subject classifications: 62G05 62G10 62G20 Keywords: Bias correction Generalized likelihood ratio Longitudinal data Partially linear single-index models QIF a b s t r a c t In this paper, we consider the partially linear single-index models with longitudinal data. We propose the bias-corrected quadratic inference function (QIF) method to estimate the parameters in the model by accounti...

متن کامل

Quadratic inference functions for varying-coefficient models with longitudinal data.

Nonparametric smoothing methods are used to model longitudinal data, but the challenge remains to incorporate correlation into nonparametric estimation procedures. In this article, we propose an efficient estimation procedure for varying-coefficient models for longitudinal data. The proposed procedure can easily take into account correlation within subjects and deal directly with both continuou...

متن کامل

Quadratic inference functions in marginal models for longitudinal data.

The quadratic inference function (QIF) is a new statistical methodology developed for the estimation and inference in longitudinal data analysis using marginal models. This method is an alternative to the popular generalized estimating equations approach, and it has several useful properties such as robustness, a goodness-of-fit test and model selection. This paper presents an introductory revi...

متن کامل

The Graduate School PENALIZED QUADRATIC INFERENCE FUNCTIONS FOR VARIABLE SELECTION IN LONGITUDINAL RESEARCH

For decades, much research has been devoted to developing and comparing variable selection methods, but primarily for the classical case of independent observations. Existing variable-selection methods can be adapted to cluster-correlated observations, but some adaptation is required. For example, classical model fit statistics such as AIC and BIC are undefined if the likelihood function is unk...

متن کامل

ذخیره 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 Multivariate Analysis

سال: 2009

ISSN: 0047-259X

DOI: 10.1016/j.jmva.2008.04.004