Adaptive Ridge Selector ( ARiS ) June 15 , 2008

نویسنده

  • Russell L. Zaretzki
چکیده

We introduce a new shrinkage variable selection operator for linear models which we term the adaptive ridge selector (ARiS). This approach is inspired by the relevance vector machine (RVM), which uses a Bayesian hierarchical linear setup to do variable selection and model estimation. Extending the RVM algorithm, we include a proper prior distribution for the precisions of the regression coefficients, v j ∼ f(v −1 j |η), where η is a scalar hyperparameter. A novel fitting approach which utilizes the full set of posterior conditional distributions is applied to maximize the joint posterior distribution p(β, σ2,v|y, η) given the value of the hyper-parameter η. An empirical Bayes method is proposed for choosing η. This approach is contrasted with other regularized least squares

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

2 8 M ay 2 00 8 Adaptive Ridge Selector ( ARiS ) May 28 , 2008

We introduce a new shrinkage variable selection operator for linear models which we term the adaptive ridge selector (ARiS). This approach is inspired by the relevance vector machine (RVM), which uses a Bayesian hierarchical linear setup to do variable selection and model estimation. Extending the RVM algorithm, we include a proper prior distribution for the precisions of the regression coeffic...

متن کامل

6 Sure Independence Screening for Ultra - High Dimensional Feature Space ∗

High dimensionality is a growing feature in many areas of contemporary statistics. Variable selection is fundamental to high-dimensional statistical modeling. For problems of large or huge scale pn, computational cost and estimation accuracy are always two top concerns. In a seminal paper, Candes and Tao (2007) propose a minimum l1 estimator, the Dantzig selector, and show that it mimics the id...

متن کامل

Optimized computational Afin image algorithm using combination of update coefficients and wavelet packet conversion

Updating Optimal Coefficients and Selected Observations Affine Projection is an effective way to reduce the computational and power consumption of this algorithm in the application of adaptive filters. On the other hand, the calculation of this algorithm can be reduced by using subbands and applying the concept of filtering the Set-Membership in each subband. Considering these concepts, the fir...

متن کامل

Detecting the "ngerprint minutiae by adaptive tracing the gray-level ridge

This paper presents a minutiae detection procedure based on adaptive tracing the gray-level ridge of the "ngerprint image with piecewise linear lines of di!erent length. The original "ngerprint image is smoothed with an adaptive-oriented smoothing "lter only at some selected points. This will greatly reduce the computational time. Each ridge in the skeleton is labeled with a number so that each...

متن کامل

Discussion of "Sure Independence Screening for Ultra-High Dimensional Feature Space.

June 30, 2008 Abstract Variable selection plays an important role in high dimensional statistical modeling which nowadays appears in many areas and is key to various scientific discoveries. For problems of large scale or dimensionality p, estimation accuracy and computational cost are two top concerns. In a recent paper, Candes and Tao (2007) propose the Dantzig selector using L1 regularization...

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 2009