- Park J
- Yoon Kim T

Statistics and Probability Letters (2007) 77(13) 1459-1466

- 3Mendeley users who have this article in their library.
- 6Citations of this article.

In this paper, the exact form of Fisher information matrix for a four-parameter kappa distribution (K4D) is determined. The K4D is so general that includes a variety of distributions as special cases. The necessary condition for the existence of Fisher information matrix is { 0 < h < frac(1, 2), k < frac(1, 2) } ∪ { h < 0, frac(1, 2) h < k < frac(1, 2) } for k ≠ 0, h ≠ 0. © 2007 Elsevier B.V. All rights reserved.

- Beta function
- Digamma function
- Extreme value distribution
- Hydrology
- Maximum likelihood estimation

Mendeley saves you time finding and organizing research

Sign up here

Already have an account ?Sign in

Choose a citation style from the tabs below