Classical testing in functional linear models
نویسندگان
چکیده
منابع مشابه
Classical Testing in Functional Linear Models.
We extend four tests common in classical regression - Wald, score, likelihood ratio and F tests - to functional linear regression, for testing the null hypothesis, that there is no association between a scalar response and a functional covariate. Using functional principal component analysis, we re-express the functional linear model as a standard linear model, where the effect of the functiona...
متن کاملTESTING FOR AUTOCORRELATION IN UNEQUALLY REPLICATED FUNCTIONAL MEASUREMENT ERROR MODELS
In the ordinary linear models, regressing the residuals against lagged values has been suggested as an approach to test the hypothesis of zero autocorrelation among residuals. In this paper we extend these results to the both equally and unequally replicated functionally measurement error models. We consider the equally and unequally replicated cases separately, because in the first case the re...
متن کاملAdaptive Global Testing for Functional Linear Models
This paper studies global testing of the slope function in functional linear regression models. A major challenge in functional global testing is to choose the dimension of projection when approximating the functional regression model by a finite dimensional multivariate linear regression model. We develop a new method that simultaneously tests the slope vectors in a sequence of functional prin...
متن کاملtesting for autocorrelation in unequally replicated functional measurement error models
in the ordinary linear models, regressing the residuals against lagged values has been suggested as an approach to test the hypothesis of zero autocorrelation among residuals. in this paper we extend these results to the both equally and unequally replicated functionally measurement error models. we consider the equally and unequally replicated cases separately, because in the first case the re...
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 Nonparametric Statistics
سال: 2016
ISSN: 1048-5252,1029-0311
DOI: 10.1080/10485252.2016.1231806