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Title: Confidence bounds and hypothesis tests for normal distribution coefficients of variation

Source: Research Paper FPL-RP-638. Madison, WI: U.S. Department of Agriculture, Forest Service, Forest Products Laboratory. 57 pages

Author(s)Verrill, Steve P.; Johnson, Richard A.

Publication Year: 2007  View PDF »

Category: Research Papers

Abstract: For normally distributed populations, we obtain confidence bounds on a ratio of two coefficients of variation, provide a test for the equality of k coefficients of variation, and provide confidence bounds on a coefficient of variation shared by k populations. To develop these confidence bounds and test, we first establish that estimators based on Newton steps from n-consistent estimators may be used in place of efficient solutions of the likelihood equations in likelihood ratio, Wald, and Rao tests. Taking a quadratic mean differentiability approach, Lehmann and Romano have outlined proofs of similar results. We take a Cramer condition approach and make the conditions and their use explicit.

Keywords: Coefficient of variation, signal to noise ratio, risk to return ratio, one-step Newton estimators, Newton's method, n-consistent estimators, efficient likelihood estimators, Cramer conditions, quadratic mean differentiability, likelihood ratio test, Wald test, Rao test, asymptotics, confidence internals, Newton-Raphson method

File size: 718 kb(s)

This publication is also viewable on Treesearch:  view
RITS Product ID: 2200
Current FPL Scientist associated with this product
Verrill, Steve P.
Mathematical Statistician
  

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