Automatic Smoothing Parameter Selection: A Sunrey by

نویسنده

  • J. S. Marron
چکیده

This is a survey of recent developments in smoothing parameter selection for curve estimation. The first goal of this paper is to provide an introduction to the methods available, with discussion at both a practical and also a nontechnical theoretical level, including comparison of methods. The second goal is to provide access to the literature, especially on smoothing parameter selection, but also on curve estimation in general. The two main settings considered here are nonparametric regression and probability density estimation, although the points made apply to other settings as well. These points also apply to many different estimators, although the focus is on kernel estimators, because they are the most easily understood and motivated, and have been at the heart of the development in the field.-1

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

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

منابع مشابه

How Far Are Automatically Chosen Regression Smoothing Parameters from Their Optimum?

· ABSTRACT In the setting of nonparametric curve estimation the problem of smoothing parameter selection is addressed. The deviation between the the squared error optimal smoothing parameter and the smoothing parameters provided by a number of automatic selection methods is studied both theoretically and by simUlation. The theoretical results include a central limit theorem which shows both the...

متن کامل

An innovative procedure for smoothing parameter selection

Smoothing with penalized splines calls for an automatic method to select the size of the penalty parameter λ . We propose a not well known smoothing parameter selection procedure: the L-curve method. AIC and (generalized) cross validation represent the most common choices in this kind of problems even if they indicate light smoothing when the data represent a smooth trend plus correlated noise....

متن کامل

Pixel Dependent Automatic Parameter Selection for Image Denoising with Bilateral Filter

Image denoising using bilateral filter is controlled by the width of its smoothing functions namely the domain and the range components. The choice of the width of range function is image dependent and requires several experiments. This paper presents an automatic method based on power-law scaling of the inverse of local statistics for pixel wise estimation of range parameter. This leads to an ...

متن کامل

Local Factor Analysis with Automatic Model Selection and Data Smoothing Based Regularization

Local factor analysis (LFA) is regarded as an efficient approach that implements local feature extraction and dimensionality reduction. A further investigation is made on an automatic BYY harmony data smoothing LFA (LFA-HDS) from the Bayesian Ying-Yang (BYY) harmony learning point of view. On the level of regularization, an data smoothing based regularization technique is adapted into this auto...

متن کامل

Automatic Smoothing and Variable Selection via Regularization

This thesis focuses on developing computational methods and the general theory of automatic smoothing and variable selection via regularization. Methods of regularization are a commonly used technique to get stable solution to ill-posed problems such as nonparametric regression and classification. In recent years, methods of regularization have also been successfully introduced to address a cla...

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

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

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

عنوان ژورنال:

دوره   شماره 

صفحات  -

تاریخ انتشار 2008