A novel unbiased estimator for estimating the probability mass of a multivariate exponential distribution over a measurable set is introduced and is called the Exponential Simplex (ES) estimator. For any measurable set, the standard error of the ES-estimator is at most the standard error of the well known Monte Carlo (MC) estimator. For non-radially shaped measurable sets, the ES-estimator has a strictly smaller standard error than the MC-estimator. For ray-convex sets, such as convex sets, the ES-estimator can be expressed in a simple analytical form.
|Number of pages||8|
|Journal||Stochastic Programming E-Print Series|
|Publication status||Published - 2006|
Olieman, N. J., & van Putten, B. (2006). Estimation method of multivariate exponential probabilities based on a simplex coordinates transform. Stochastic Programming E-Print Series, 2006(6). http://edoc.hu-berlin.de/series/speps/2006-6/PDF/6.pdf