Likelihood-based inference for the power half-normal distribution
In this paper we consider an extension of the half-normal distribution based on the distribution of the maximum of a random sample. It is shown that this distribution belongs to the family of beta generalized half-normal distributions. Properties of its density are investigated, maximum likelihood e...
| Main Authors: | , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Atlantis Press
2015-11-01
|
| Series: | Journal of Statistical Theory and Applications (JSTA) |
| Subjects: | |
| Online Access: | https://www.atlantis-press.com/article/25845143.pdf |
| Summary: | In this paper we consider an extension of the half-normal distribution based on the distribution of the maximum of a random sample. It is shown that this distribution belongs to the family of beta generalized half-normal distributions. Properties of its density are investigated, maximum likelihood estimation is discussed and the Fisher information matrix is derived. A real data illustration is presented, and comparisons with alternative extensions of the half-normal distribution reveal good performance of the proposed model. |
|---|---|
| ISSN: | 1538-7887 |