Abstract
In this paper, some properties of gamma-X family are discussed and a member of the family, the gamma-normal distribution, is studied in detail. The limiting behaviors, moments, mean deviations, dispersion, and Shannon entropy for the gamma-normal distribution are provided. Bounds for the non-central moments are obtained. The method of maximum likelihood estimation is proposed for estimating the parameters of the gamma-normal distribution. Two real data sets are used to illustrate the applications of the gamma-normal distribution.
| Original language | English |
|---|---|
| Pages (from-to) | 67-80 |
| Number of pages | 14 |
| Journal | Computational Statistics and Data Analysis |
| Volume | 69 |
| DOIs | |
| Publication status | Published - 2014 |
| Externally published | Yes |
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Keywords
- Estimation
- Hazard function
- Moments
- T-X distributions
ASJC Scopus subject areas
- Computational Mathematics
- Computational Theory and Mathematics
- Statistics and Probability
- Applied Mathematics
Cite this
The gamma-normal distribution : Properties and applications. / Alzaatreh, Ayman; Famoye, Felix; Lee, Carl.
In: Computational Statistics and Data Analysis, Vol. 69, 2014, p. 67-80.Research output: Contribution to journal › Article
}
TY - JOUR
T1 - The gamma-normal distribution
T2 - Properties and applications
AU - Alzaatreh, Ayman
AU - Famoye, Felix
AU - Lee, Carl
PY - 2014
Y1 - 2014
N2 - In this paper, some properties of gamma-X family are discussed and a member of the family, the gamma-normal distribution, is studied in detail. The limiting behaviors, moments, mean deviations, dispersion, and Shannon entropy for the gamma-normal distribution are provided. Bounds for the non-central moments are obtained. The method of maximum likelihood estimation is proposed for estimating the parameters of the gamma-normal distribution. Two real data sets are used to illustrate the applications of the gamma-normal distribution.
AB - In this paper, some properties of gamma-X family are discussed and a member of the family, the gamma-normal distribution, is studied in detail. The limiting behaviors, moments, mean deviations, dispersion, and Shannon entropy for the gamma-normal distribution are provided. Bounds for the non-central moments are obtained. The method of maximum likelihood estimation is proposed for estimating the parameters of the gamma-normal distribution. Two real data sets are used to illustrate the applications of the gamma-normal distribution.
KW - Estimation
KW - Hazard function
KW - Moments
KW - T-X distributions
UR - http://www.scopus.com/inward/record.url?scp=84882959047&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84882959047&partnerID=8YFLogxK
U2 - 10.1016/j.csda.2013.07.035
DO - 10.1016/j.csda.2013.07.035
M3 - Article
VL - 69
SP - 67
EP - 80
JO - Computational Statistics and Data Analysis
JF - Computational Statistics and Data Analysis
SN - 0167-9473
ER -