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A Monte-Carlo study of asymptotically robust tests for correlation coefficients

1973; Oxford University Press; Volume: 60; Issue: 3 Linguagem: Inglês

10.1093/biomet/60.3.551

1464-3510

George T. Duncan, M. W. J. Layard,

Financial Risk and Volatility Modeling

Monte-Carlo simulation is used to compare the small-sample performance of the usual normal theory procedures for inference about correlation coefficients with that of two asymptotically robust procedures, one of which is based on a grouping of the observations and the other on the jackknife technique. The sampled distributions comprise the normal and five nonnormal distributions. The small-sample results support the conclusion based on asymptotic theory that the normal test is not robust. The jackknife procedure works well for most of the sampled distributions.