Symmetrizing and Variance Stabilizing Transformations of Sample Coefficient of Variation from Inverse Gaussian Distribution

Chaubey, Yogendra Prasad

Symmetrizing and Variance Stabilizing Transformations of Sample Coefficient of Variation from Inverse Gaussian Distribution

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Date

2017-06-23

Date Issued

2017-11-01

ISI Journal

Authors

Chaubey, Yogendra Prasad

Singh, Murari

Sen, Debaraj

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Citation

Yogendra Prasad Chaubey, Murari Singh, Debaraj Sen. (1/11/2017). Symmetrizing and Variance Stabilizing Transformations of Sample Coefficient of Variation from Inverse Gaussian Distribution. Sankhya B - Applied and Interdisciplinary Statistics, 79, pp. 217-246.

Abstract

Coefficient of variation (CV) plays an important role in statistical practice; however, its sampling distribution may not be easy to compute. In this paper, the distributional properties of the sample CV from an inverse Gaussian distribution are investigated through transformations. Specifically, the symmetrizing transformation as outlined in Chaubey and Mudholkar (1983), that requires numerical techniques, is contrasted with the explicitly available variance stabilizing transformation (VST). The symmetrizing transformation scores very high as compared to the VST, especially in a power family. The usefulness of the resulting approximation is illustrated through a numerical example.