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Detecting the Change of Variance by Using Conditional Distribution with Diverse Copula Functions

  • Jong-Min Kim
  • Jaiwook Baik
  • Mitch Reller
Conference paper
Part of the ICSA Book Series in Statistics book series (ICSABSS)

Abstract

We propose new method for detecting the change of variance by using conditional distribution with diverse copula functions. We generate the conditional asymmetric random transformed data by employing asymmetric copula function and apply the conditional transformed data to the cumulative sum control (CUSUM) statistics in order to detect the change point of conditional variance by measuring the average run length (ARL) of CUSUM control charts by using Monte Carlo simulation method. We show that the ARLs of change point of conditional variance by CUSUM are affected by the directional dependence by using the bivariate Gaussian copula beta regression (Kim and Hwang 2017).

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Copyright information

© Springer Nature Singapore Pte Ltd. 2018

Authors and Affiliations

  1. 1.Statistics Discipline, Division of Science and MathematicsUniversity of MinnesotaMorrisUSA
  2. 2.Department of Information StatisticsKorea National Open UniversitySeoulRepublic of Korea

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