Accession Number : ADA146673


Title :   Efficient Scores, Variance Decompositions and Monte Carlo Swindles.


Descriptive Note : Technical rept.,


Corporate Author : STANFORD UNIV CA DEPT OF STATISTICS


Personal Author(s) : Johnstone,I ; Velleman,P


Full Text : https://apps.dtic.mil/dtic/tr/fulltext/u2/a146673.pdf


Report Date : 28 Aug 1984


Pagination or Media Count : 47


Abstract : Monte Carlo swindles or variance reduction techniques exploit the experimenter's knowledge of the stochastic structure governing the simulated data to construct more precise estimates of unknown parameters. Alternatively, one can reduce the number of replications (and thus the cost) needed to gain a desired level of precision. This paper reviews the common case of swindles based on variance decompositions for estimating efficiencies and variances of location and regression estimators. It then proposes a new swindle based on Fisher's efficient score function that can be applied to a much wider range of situations than can the Gaussian-over-independent swindles used in many studies of robust estimators. The authors compare these methods by performing simulations for the efficiencies of location estimates and by placing them in a simple geometric framework. They illustrate the use of the score function swindle in estimating the variances of Pitman estimates of location for samples from the t-distribution at selected degrees of freedom. Finally, applications to scale estimation, exponential regression, statistical decision theory, and bootstrap computations are sketched. (Author)


Descriptors :   *MONTE CARLO METHOD , COMPUTATIONS , EFFICIENCY , ESTIMATES , VARIATIONS , NAVAL RESEARCH , DECOMPOSITION , SCORING


Subject Categories : Numerical Mathematics


Distribution Statement : APPROVED FOR PUBLIC RELEASE