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Beta generalized normal distribution with an application for SAR image processing

2012; Taylor & Francis; Volume: 48; Issue: 2 Linguagem: Inglês

10.1080/02331888.2012.748776

1029-4910

Renato J. Cintra, Leandro Chaves Rêgo, Gauss M. Cordeiro, Abraão D. C. Nascimento,

Bayesian Methods and Mixture Models

We introduce the beta generalized normal distribution which is obtained by compounding the beta and generalized normal [Nadarajah, S., A generalized normal distribution, \emph{Journal of Applied Statistics}. 32, 685--694, 2005] distributions. The new model includes as sub-models the beta normal, beta Laplace, normal, and Laplace distributions. The shape of the new distribution is quite flexible, specially the skewness and the tail weights, due to two additional parameters. We obtain general expansions for the moments. The estimation of the parameters is investigated by maximum likelihood. We also proposed a random number generator for the new distribution. Actual synthetic aperture radar were analyzed and modeled after the new distribution. Results could outperform the $\mathcal{G}^0$, $\mathcal{K}$, and $\Gamma$ distributions in several scenarios.