Optimal Prediction and Tolerance Intervals for the Ratio of Dependent Normal Random Variables

A simple exact method is proposed for computing prediction intervals and tolerance intervals for the distribution of the ratio X1/X2 when (X1,X2) follows a bivariate normal distribution. The methodology uses the factors available for computing one-sample prediction intervals and tolerance intervals for a univariate normal distribution. Both one-sided and two-sided intervals are constructed, and the two-sided tolerance intervals are obtained with and without imposing the equal-tail requirement. The results are illustrated using two practical applications that call for the computation of prediction intervals and tolerance intervals for the distribution of the ratio X1/X2. Thefirst application is an investigation of retroviral contamination in the raw materials used for the manufacture of the influenza vaccine FluMist. The second application is on the cost-effectiveness of a new drug compared to a standard drug. IJSS, Vol. 25(1), March, 2025, pp 11-22

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Publication Details

Journal
International Journal of Statistical Sciences
Published
2025-04-17
DOI
https://doi.org/10.3329/ijss.v25i1.81041
Primary Topic
Multi-Criteria Decision Making
Type
article
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article

Optimal Prediction and Tolerance Intervals for the Ratio of Dependent Normal Random Variables

K. Krishnamoorthy, Gboyega Adepoju
International Journal of Statistical Sciences
Multi-Criteria Decision Making
article

Optimal Prediction and Tolerance Intervals for the Ratio of Dependent Normal Random Variables

K. Krishnamoorthy, Gboyega Adepoju
article en

Abstract

A simple exact method is proposed for computing prediction intervals and tolerance intervals for the distribution of the ratio X1/X2 when (X1,X2) follows a bivariate normal distribution. The methodology uses the factors available for computing one-sample prediction intervals and tolerance intervals for a univariate normal distribution. Both one-sided and two-sided intervals are constructed, and the two-sided tolerance intervals are obtained with and without imposing the equal-tail requirement. The results are illustrated using two practical applications that call for the computation of prediction intervals and tolerance intervals for the distribution of the ratio X1/X2. Thefirst application is an investigation of retroviral contamination in the raw materials used for the manufacture of the influenza vaccine FluMist. The second application is on the cost-effectiveness of a new drug compared to a standard drug. IJSS, Vol. 25(1), March, 2025, pp 11-22

International Journal of Statistical SciencesVol. 25(1)
University of Louisiana at Lafayette (US)
Openalex Percentile: Top 91%
Multi-Criteria Decision Making
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