We estimate the parameter of a stationary time series process by minimizing integrated weighted mean squared error between empirical and simulated characteristic function, when true functions cannot be explicitly computed. Motivated Indirect Inference, we use Monte Carlo approximation function based on i.i.d. blocks. As classical variance reduction technique, propose control variates for reduci...

Many Monte Carlo simulation problems lend themselves readily to the application of variance reduction techniques. These techniques can result in great improvements in simulation efficiency. This document describes the basic concepts of variance reduction (Part I), and a methodology for application of variance reduction techniques is presented in Part II. Appendices include the basic analytical ...

This paper presents a new control variate method for general multi-dimensional stochastic differential equations (SDEs) including jumps in order to reduce the variance of Monte Carlo method. Our control variate method is based on an asymptotic expansion technique, and does not require an explicit characteristic function of SDEs. This is an extension of previous researches using asymptotic expan...

We develop an exact simple random variate generator for the theta distribution, which occurs as the limit distribution of the height of nearly all models of uniform random trees. Even though the density is only known as an infinite sum of functions, our algorithm does not require any summation. The properties of the theta distribution with distribution function F(x)= ~ (1-2j2x2)e-J2x2 j~-(x3 oo...

In the present article, we derive an explicit expression for truncated mean and variance multivariate normal distribution with arbitrary rectangular double truncation. We use moment generating approach of Tallis (1961) extend it to general ?, ? all combinations As part solution, also give a formula bivariate marginal density multinormal variates. prove invariance property some elements inverse ...