Accession Number : ADA330896

Title :   Multivariate Nonparametric Statistical Techniques for Simulation Model Validation

Descriptive Note : Final technical rept.

Corporate Author : BARRON ASSOCIATES INC CHARLOTTESVILLE VA

Personal Author(s) : Larson, Edward C. ; Parker, B. E., Jr. ; Poor, H. V.

PDF Url : ADA330896

Report Date : 21 OCT 1997

Pagination or Media Count : 32

Abstract : This report documents the findings of an Army SBIR Phase 1 study on multivariate nonparametric tests for stochastic model validation. We herein introduce a method for generalizing rank transformations to the multivariate domain such that the rank-transformed set is uniformly distributed in multiple dimensions. This furnishes a more robust hypothesis testing technique than earlier proposed approaches and has certain computational advantages. This approach is well adapted for continuous-output models. For tests based on partitioning the model output space into bins and computing a confidence statistic based directly on bin counts, as opposed to computing statistical moments, we introduce a log-likelihood statistic that appears to be an excellent summary indicator of correspondence between a simulation model and test data. The approach is extremely versatile and well-adapted to discrete-output models.

Descriptors :   *MATHEMATICAL MODELS, *MULTIVARIATE ANALYSIS, STOCHASTIC PROCESSES, STATISTICAL INFERENCE, GAUSSIAN NOISE, NONPARAMETRIC STATISTICS, COMPUTER PROGRAM VERIFICATION, RANK ORDER STATISTICS.

Subject Categories : Statistics and Probability
      Operations Research

Distribution Statement : APPROVED FOR PUBLIC RELEASE