Improved Cramer-Rao Inequality for Randomly Censored Data

Abstract

As an application of the improved Cauchy-Schwartz inequality due to Walker (2017), we obtain an improved version of the Cramer-Rao inequality for randomly censored data derived by 2171-2185). We derive a lower bound of the Bhattacharya type for the mean square error of a parametric function based on randomly censored data.

Identifiers

DOI

10.29252/jirss.17.2.2

Citations and references