Estimation and inference in partially functional linear regression with multiple functional covariates

نویسندگان
چکیده

برای دانلود رایگان 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

Multiple functional regression with both discrete and continuous covariates

In this paper we present a nonparametric method for extending functional regression methodology to the situation where more than one functional covariate is used to predict a functional response. Borrowing the idea from Kadri et al. (2010a), the method, which support mixed discrete and continuous explanatory variables, is based on estimating a function-valued function in reproducing kernel Hilb...

متن کامل

Estimation in Partially Linear Models With Missing Covariates

The partially linear model Y DXT ̄C o.Z/C 2 has been studied extensively when data are completely observed. In this article, we consider the case where the covariate X is sometimes missing, with missingness probability 1⁄4 depending on .Y;Z/. New methods are developed for estimating ̄ and o.¢/. Our methods are shown to outperform asymptotically methods based only on the complete data. Asymptotic ...

متن کامل

Maximum Likelihood Estimation of Parameters in Generalized Functional Linear Model

Sometimes, in practice, data are a function of another variable, which is called functional data. If the scalar response variable is categorical or discrete, and the covariates are functional, then a generalized functional linear model is used to analyze this type of data. In this paper, a truncated generalized functional linear model is studied and a maximum likelihood approach is used to esti...

متن کامل

Estimation of the Functional Linear Regression with Smoothing Splines

We consider functional linear regression where a real variable Y depends on a functional variable X. The functional coefficient of the model is estimated by means of smoothing splines. We derive the rates of convergence with respect to the semi-norm induced by the covariance operator of X, which comes to evaluate the error of prediction. These rates, which essentially depend on the smoothness o...

متن کامل

Robust Estimation in Linear Regression with Molticollinearity and Sparse Models

‎One of the factors affecting the statistical analysis of the data is the presence of outliers‎. ‎The methods which are not affected by the outliers are called robust methods‎. ‎Robust regression methods are robust estimation methods of regression model parameters in the presence of outliers‎. ‎Besides outliers‎, ‎the linear dependency of regressor variables‎, ‎which is called multicollinearity...

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 Statistical Planning and Inference

سال: 2020

ISSN: 0378-3758

DOI: 10.1016/j.jspi.2020.02.007