Variable Selection by Perfect Sampling

نویسندگان
چکیده

برای دانلود رایگان 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

Variable Selection by Perfect Sampling

Variable selection is very important in many fields, and for its resolution many procedures have been proposed and investigated. Among them are Bayesian methods that use Markov chain Monte-Carlo (MCMC) sampling algorithms. A problem with MCMC sampling, however, is that it cannot guarantee that the samples are exactly from the target distributions. This drawback is overcome by related methods kn...

متن کامل

Variable Selection Via Gibbs Sampling

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

Acceleration of perfect sampling by skipping events

This paper presents a new method to speed up perfect sampling of Markov chains by skipping passive events during the simulation. We show that this can be done without altering the distribution of the samples. This technique is particularly efficient for the simulation of Markov chains with different time scales such as queueing networks where certain servers are much faster than others. In such...

متن کامل

Fuzzy Double Variable Sampling Plan under Uncertainty

Double sampling plan is an examination with a certain parameter, so it cannot decide about manufactured products whose portion parameter ( ) is not certain. The main goal of this survey is to introduce double variable plan when  is indefinite to examine manufacturing products when concerned characteristics are normally distributed. Plan parameters are achieved by an optimization manner. Sum of ...

متن کامل

Toward a successful CRM: variable selection, sampling, and ensemble

This paper studies the effects of variable selection and class distribution on the performance of specific logit regression (i.e., a primitive classifier system) and artificial neural network (ANN; a relatively more sophisticated classifier system) implementations in a customer relationship management (CRM) setting. Finally, ensemble models are constructed by combining the predictions of multip...

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: EURASIP Journal on Advances in Signal Processing

سال: 2002

ISSN: 1687-6180

DOI: 10.1155/s1110865702000409