Smoothing parameter selection in kernel nonparametric regression using bat optimization algorithm

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 regression for functional data: automatic smoothing parameter selection

We study regression estimation when the explanatory variable is functional. Nonparametric estimates of the regression operator have been recently introduced. They depend on a smoothing factor which controls its behavior, and the aim of our work is to construct some data-driven criterion for choosing this smoothing parameter. The criterion can be formulated in terms of a functional version of cr...

متن کامل

Gradient Based Smoothing Parameter Selection for Nonparametric Regression Estimation*

Data-driven bandwidth selection based on the gradient of an unknown regression function is considered. Uncovering gradients nonparametrically is of crucial importance across a broad range of economic environments such as determining risk premium or recovering distributions of individual preferences. The procedure developed here is shown to deliver bandwidths which have the optimal rate of conve...

متن کامل

Smoothing Parameter Selection in Nonparametric Regression Using an Improved Akaike Information Criterion

Your use of the JSTOR archive indicates your acceptance of JSTOR's Terms and Conditions of Use, available at http://www.jstor.org/about/terms.html. JSTOR's Terms and Conditions of Use provides, in part, that unless you have obtained prior permission, you may not download an entire issue of a journal or multiple copies of articles, and you may use content in the JSTOR archive only for your perso...

متن کامل

A Comparison of the Nonparametric Regression Models using Smoothing Spline and Kernel Regression

This paper study about using of nonparametric models for Gross National Product data in Turkey and Stanford heart transplant data. It is discussed two nonparametric techniques called smoothing spline and kernel regression. The main goal is to compare the techniques used for prediction of the nonparametric regression models. According to the results of numerical studies, it is concluded that smo...

متن کامل

Model Indexing and Smoothing Parameter Selection in Nonparametric Function Estimation

Smoothing parameter selection is among the most intensively studied subjects in nonpara-metric function estimation. A closely related issue, that of identifying a proper index for the smoothing parameter, is however largely neglected in the existing literature. Through heuris-tic arguments and simple simulations, we shall illustrate that most current working indices are conceptually \incorrect"...

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 Physics: Conference Series

سال: 2021

ISSN: 1742-6588,1742-6596

DOI: 10.1088/1742-6596/1897/1/012010