Nonparametric model checks of single-index assumptions

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

Nonparametric Checks for Single - Index Models

In this paper we study goodness-of-fit testing of single-index models. The large sample behavior of certain score-type test statistics is investigated. As a by-product, we obtain asymptotically distribution-free maximin tests for a large class of local alternatives. Furthermore, characteristic function based goodness-of-fit tests are proposed which are omnibus and able to detect peak alternativ...

متن کامل

Nonparametric Testing of an Index Model

Following a framework proposed in Bickel, Ritov and Stoker (2001) we propose and analyze the behavior of a broad family of tests for H : E(Y | U, V ) = E(Y | U) when we observe (Ui, Vi, Yi) ∈ Ru i.i.d., i = 1, . . . , n.

متن کامل

Sparse single-index model

Let (X, Y ) be a random pair taking values in Rp × R. In the socalled single-index model, one has Y = f?(θ?TX) + W , where f? is an unknown univariate measurable function, θ? is an unknown vector in Rd, and W denotes a random noise satisfying E[W |X] = 0. The single-index model is known to offer a flexible way to model a variety of high-dimensional real-world phenomena. However, despite its rel...

متن کامل

Single and Multiple Index Functional Regression Models with Nonparametric Link

Fully nonparametric methods for regression from functional data have poor accuracy from a statistical viewpoint, reflecting the fact that their convergence rates are slower than nonparametric rates for the estimation of high-dimensional functions. This difficulty has led to an emphasis on the so-called functional linear model, which is much more flexible than common linear models in finite dime...

متن کامل

Single-index model selections

We derive a new model selection criterion for single-index models, AICC , by minimizing the expected Kullback-Leibler distance between the true and candidate models. The proposed criterion selects not only relevant variables but also the smoothing parameter for an unknown link function. Thus, it is a general selection criterion that provides a uniÞed approach to model selection across both para...

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: Statistica Sinica

سال: 2018

ISSN: 1017-0405

DOI: 10.5705/ss.202015.0337