Rao Blackwellization of Generalized Accept Reject Schemes

نویسندگان

  • George Casella
  • Christian P. Robert
چکیده

This paper extends the accept reject algorithm to allow the pro posal distribution to change at each iteration We rst establish a necessary and su cient condition for this generalized accept reject al gorithm to be valid and then show how the Rao Blackwellization of Casella and Robert can be extended to this setting An impor tant application of these results is to the perfect sampling technique of Fill which is a generalized accept reject algorithm in disguise

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

Markov Chain Monte Carlo and Rao{blackwellization

We introduce a form of Rao{Blackwellization for Markov chains which uses the transition distribution for conditioning. We show that for reversible Markov chains, this form of Rao{Blackwellization always reduces the asymptotic variance, and derive two explicit forms of the variance reduction obtained through repeated Rao{Blackwellization. The result applies to many Markov chain Monte Carlo metho...

متن کامل

Optimal Stopping Policy for Multivariate Sequences a Generalized Best Choice Problem

  In the classical versions of “Best Choice Problem”, the sequence of offers is a random sample from a single known distribution. We present an extension of this problem in which the sequential offers are random variables but from multiple independent distributions. Each distribution function represents a class of investment or offers. Offers appear without any specified order. The objective is...

متن کامل

Particle rejuvenation of Rao-Blackwellized sequential Monte Carlo smoothers for conditionally linear and Gaussian models

This paper focuses on sequential Monte Carlo approximations of smoothing distributions in conditionally linear and Gaussian state spaces. To reduce Monte Carlo variance of smoothers, it is typical in these models to use Rao-Blackwellization: particle approximation is used to sample sequences of hidden regimes while the Gaussian states are explicitly integrated conditional on the sequence of reg...

متن کامل

Using DEA for Classification in Credit Scoring

Credit scoring is a kind of binary classification problem that contains important information for manager to make a decision in particularly in banking authorities. Obtained scores provide a practical credit decision for a loan officer to classify clients to reject or accept for payment loan. For this sake, in this paper a data envelopment analysis- discriminant analysis (DEA-DA) approach is us...

متن کامل

The Marginal Bayesian Cramér-Rao Bound for Jump Markov Systems

In this letter, numerical algorithms for computing the marginal version of the Bayesian Cramér-Rao bound (M-BCRB) for jump Markov nonlinear systems and jump Markov linear Gaussian systems are proposed. Benchmark examples for both systems illustrate that the M-BCRB is tighter than three other recently proposed BCRBs. Index Terms Jump Markov nonlinear systems, Bayesian Cramér-Rao bound, particle ...

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 2000