نویسندگان | Jarrahiferiz Jalil |
---|---|
نشریه | Journal of Nonparametric Statistics |
شماره صفحات | 88-99 |
شماره سریال | 1 |
شماره مجلد | 31 |
ضریب تاثیر (IF) | 0.507 |
نوع مقاله | Full Paper |
تاریخ انتشار | 2019 |
رتبه نشریه | ISI |
نوع نشریه | چاپی |
کشور محل چاپ | ایران |
نمایه نشریه | JCR،Scopus |
چکیده مقاله
Recently, Lad, Sanfilippo, and Agro [(2015), ‘Extropy: Complementary Dual of Entropy’, Statistical Science, 30, 40–58.] showed the measure of entropy has a complementary dual, which is termed extropy. The present article introduces some estimators of the extropy of a continuous random variable. Properties of the proposed estimators are stated, and comparisons are made with Qiu and Jia’s estimators [(2018a), ‘Extropy Estimators with Applications in Testing uniformity’, Journal of Nonparametric Statistics, 30, 182–196]. The results indicate that the proposed estimators have a smaller mean squared error than competing estimators. A real example is presented and analysed.
tags: Extropy; nonparametric kernel density estimation; local linear model; mean squared error; Monte Carlo simulation