Abstract
The cumulative residual Kullback–Leibler information is defined on the semi-infinite (non negative) interval. In this paper, we extend the cumulative residual Kullback–Leibler information to the whole real line and propose a general cumulative Kullback–Leibler information. We study its application to a test for normality in comparison with some competing test statistics based on the empirical distribution function including the well-known tests applied in practice like Kolmogorov–Smirnov, Cramer–von Mises, Anderson–Darling, and other existing tests.
| Original language | English |
|---|---|
| Pages (from-to) | 1551-1560 |
| Number of pages | 10 |
| Journal | Communications in Statistics - Theory and Methods |
| Volume | 47 |
| Issue number | 7 |
| DOIs | |
| Publication status | Published - 2018 Apr 3 |
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All Science Journal Classification (ASJC) codes
- Statistics and Probability
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General cumulative Kullback–Leibler information. / Park, Sangun; Noughabi, Hadi Alizadeh; Kim, Ilmun.
In: Communications in Statistics - Theory and Methods, Vol. 47, No. 7, 03.04.2018, p. 1551-1560.Research output: Contribution to journal › Article
TY - JOUR
T1 - General cumulative Kullback–Leibler information
AU - Park, Sangun
AU - Noughabi, Hadi Alizadeh
AU - Kim, Ilmun
PY - 2018/4/3
Y1 - 2018/4/3
N2 - The cumulative residual Kullback–Leibler information is defined on the semi-infinite (non negative) interval. In this paper, we extend the cumulative residual Kullback–Leibler information to the whole real line and propose a general cumulative Kullback–Leibler information. We study its application to a test for normality in comparison with some competing test statistics based on the empirical distribution function including the well-known tests applied in practice like Kolmogorov–Smirnov, Cramer–von Mises, Anderson–Darling, and other existing tests.
AB - The cumulative residual Kullback–Leibler information is defined on the semi-infinite (non negative) interval. In this paper, we extend the cumulative residual Kullback–Leibler information to the whole real line and propose a general cumulative Kullback–Leibler information. We study its application to a test for normality in comparison with some competing test statistics based on the empirical distribution function including the well-known tests applied in practice like Kolmogorov–Smirnov, Cramer–von Mises, Anderson–Darling, and other existing tests.
UR - http://www.scopus.com/inward/record.url?scp=85030160499&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85030160499&partnerID=8YFLogxK
U2 - 10.1080/03610926.2017.1321767
DO - 10.1080/03610926.2017.1321767
M3 - Article
AN - SCOPUS:85030160499
VL - 47
SP - 1551
EP - 1560
JO - Communications in Statistics - Theory and Methods
JF - Communications in Statistics - Theory and Methods
SN - 0361-0926
IS - 7
ER -