Conditional Monte Carlo revisited

نویسندگان

چکیده

Conditional Monte Carlo refers to sampling from the conditional distribution of a random vector X given value T ( ) = t for function . Classical methods were designed estimating expectations functions ϕ by unconditional distributions obtained certain weighting schemes. The basic ingredients use importance and change variables. In present paper we reformulate problem introducing an artificial parametric model in which is pivotal quantity, next representing within this new model. approach illustrated several examples, including short simulation study application goodness-of-fit testing real data. connection related based on sufficient statistics briefly discussed.

برای دانلود باید عضویت طلایی داشته باشید

برای دانلود 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

Replica Monte Carlo Simulation (revisited)

In 1986, Swendsen and Wang proposed a replica Monte Carlo algorithm for spin glasses [Phys. Rev. Lett. 57 (1986) 2607]. Two important ingredients are present, (1) the use of a collection of systems (replicas) at different of temperatures, but with the same random couplings, (2) defining and flipping clusters. Exchange of information between the systems is facilitated by fixing the τ spin (τ = σ...

متن کامل

The Fermion Monte Carlo revisited

In this work we present a detailed study of the Fermion Monte Carlo algorithm (FMC), a recently proposed stochastic method for calculating fermionic ground-state energies. A proof that the FMC method is an exact method is given. In this work the stability of the method is related to the difference between the lowest (bosonic-type) eigenvalue of the FMC diffusion operator and the exact fermi ene...

متن کامل

Conditional Monte Carlo Estimation of Quantile Sensitivities

E quantile sensitivities is important in many optimization applications, from hedging in financial engineering to service-level constraints in inventory control to more general chance constraints in stochastic programming. Recently, Hong (Hong, L. J. 2009. Estimating quantile sensitivities. Oper. Res. 57 118–130) derived a batched infinitesimal perturbation analysis estimator for quantile sensi...

متن کامل

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

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: Scandinavian Journal of Statistics

سال: 2021

ISSN: ['0303-6898', '1467-9469']

DOI: https://doi.org/10.1111/sjos.12549