Simulation of truncated normal variables

9 Simulation of truncated normal variables Christian

We provide in this paper simulation algorithms for one-sided and two-sided truncated normal distributions. These algorithms are then used to simulate multivariate normal variables with restricted parameter space for any covariance structure.

Simulation of Non-normal Autocorrelated Variables

Simulation of Positive Normal Variables Using Several Proposal Distributions

In this paper, we propose a new methodology to generate random variables distributed according to a Gaussian with positive support. We narrow the study to the univariate case. The method consists in an accept-reject algorithm in which a previous step is added consisting in choosing among several proposal distributions the one which gives the highest average probability of acceptance for given p...

Moment bounds for truncated random variables

Given any random variable X ∈ [0,M ] with EX = m1 and EX = m2 fixed, various bounds are derived on the mean and variance of the truncated random variable max(0, X−K) with K > 0 given. The results are motivated by questions associated with European call option. The techniques are based on domination by quadratic functions and change of measures in the unimodal distribution case.

Saddlepoint Approximation for Moment Generating Functions of Truncated Random Variables

We consider the problem of approximating the moment generating function (MGF) of a truncated random variable in terms of the MGF of the underlying (i.e., untruncated) random variable. The purpose of approximating the MGF is to enable the application of saddlepoint approximations to certain distributions determined by truncated random variables. Two important statistical applications are the fol...