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QUANTILE-BASED STUDY OF (DYNAMIC) INACCURACY MEASURES

Published online by Cambridge University Press:  22 February 2019

Suchandan Kayal ,
Rajesh Moharana  and
S. M. Sunoj
Suchandan Kayal
Affiliation:
Department of Mathematics, National Institute of Technology Rourkela, Rourkela - 769008, India E-mail: suchandan.kayal@gmail.com; rajeshmoharana31@gmail.com
Rajesh Moharana
Affiliation:
Department of Mathematics, National Institute of Technology Rourkela, Rourkela - 769008, India E-mail: suchandan.kayal@gmail.com; rajeshmoharana31@gmail.com
S. M. Sunoj
Affiliation:
Department of Statistics, Cochin University of Science and Technology, Cochin - 682022, India E-mail: smsunoj@gmail.com
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Abstract

In the present communication, we introduce quantile-based (dynamic) inaccuracy measures and study their properties. Such measures provide an alternative approach to evaluate inaccuracy contained in the assumed statistical models. There are several models for which quantile functions are available in tractable form, though their distribution functions are not available in explicit form. In such cases, the traditional distribution function approach fails to compute inaccuracy between two random variables. Various examples are provided for illustration purpose. Some bounds are obtained. Effect of monotone transformations and characterizations are provided.

Keywords

boundscharacterizationKerridge's inaccuracy measurelikelihood ratio quantile orderquantile function

Information

Type
Research Article
Information
Probability in the Engineering and Informational Sciences , Volume 34 , Issue 2 , April 2020 , pp. 183 - 199
Copyright
Copyright © Cambridge University Press 2019

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