Asymptotic Normality in Monte Carlo Integration

نویسندگان

  • Masashi Okamoto
  • MASASHI OKAMOTO
چکیده

To estimate a multiple integral of a function over the unit cube, Haber proposed two Monte Carlo estimators /'j and J'2 based on 2N and 4N observations, respec2 2 » tively, of the function. He also considered estimators Dy and D2 of the variances of/j and J'2, respectively. This paper shows that all these estimators are asymptotically normally distributed as N tends to infinity.

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

Parametric Conditional Monte Carlo Density Estimation

In applied density estimation problems, one often has data not only on the target variable, but also on a collection of covariates. In this paper, we study a density estimator that incorporates this additional information by combining parametric estimation and conditional Monte Carlo. We prove an approximate functional asymptotic normality result that illustrates convergence rates and the asymp...

متن کامل

A Monte Carlo estimation of the entropy for Markov chains

Abstract. We introduce an estimate of the entropy Ept(log p ) of the marginal density p of a (eventually inhomogeneous) Markov chain at time t ≥ 1. This estimate is based on a double Monte Carlo integration over simulated i.i.d. copies of the Markov chain, whose transition density kernel is supposed to be known. The technique is extended to compute the external entropy Ept 1 (log p), where the ...

متن کامل

Nonparametric K-Sample Tests with Panel Count Data

In this manuscript, we study the nonparametric k-sample test problem with panel count data. The asymptotic normality of a smooth functional of the nonparametric maximum pseudo-likelihood estimator (Wellner and Zhang, 2000) is established under some mild conditions. We construct a class of easy-to-implement nonparametric tests for comparing mean functions of k populations based on this asymptoti...

متن کامل

Asymptotic normality of the QMLE of possibly nonstationary GARCH with serially dependent innovations∗

This paper proposes a new parametric volatility model that introduces serially dependent innovations in GARCH specifications. We first prove the asymptotic normality of the QML estimator in this setting, allowing for possible explosive and nonstationary behavior of the GARCH process. We show that this model can generate an alternative measure of risk premium relative to the GARCH-M. Finally, we...

متن کامل

Statistical inferences on partially linear models and their applications

In this paper, we propose a class of partially nonlinear models, and develop two new estimation procedures for these models. Asymptotic normality of the resulting estimates are established. We further propose an estimation procedure and a generalized likelihood ratio test for the baseline function in partially nonlinear models. Asymptotic properties of the newly proposed estimation procedure an...

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 2010