Volume 17, Issue 2 (12-2018)                   JIRSS 2018, 17(2): 1-12 | Back to browse issues page


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Prakasarao B. Improved Cramer-Rao Inequality for Randomly Censored Data. JIRSS. 2018; 17 (2) :1-12
URL: http://jirss.irstat.ir/article-1-472-en.html
Ph.D. CR RAO AIMSCS, HYDERABAD, INDIA
Abstract:   (673 Views)
As an application of the improved Cauchy-Schwartz inequality due to Walker (Statist. Probab. Lett. (2017) 122:86-90), we obtain an improved version of the Cramer-Rao inequality for randomly censored data derived by Abdushukurov and Kim (J. Soviet. Math. (1987) pp. 2171-2185). We derive a lower bound of Bhattacharya type for the mean square error of a parametric function based on randomly censored data.
Full-Text [PDF 58 kb]   (43 Downloads)    
Type of Study: Original Paper | Subject: 62Fxx: Parametric inference
Received: 2017/10/5 | Accepted: 2018/02/5 | Published: 2018/02/5

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