DEST - Departamento de Estatística
URI Permanente desta comunidadehttps://repositorio.ufrn.br/handle/1/136
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Navegando DEST - Departamento de Estatística por Assunto "Asymptotic normality"
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Artigo On moment-type estimators for a class of log-symmetric distributions(Computacional Statistics, 2017) Balakrishnan, N.; Saulo, Helton; Bourguignon, Marcelo; Zhu, XiaojunIn this paper, we propose three simple closed form estimators for a class of log-symmetric distributions on R+. The proposed methods make use of some key properties of this class of distributions.We derive the asymptotic distributions of these estimators. The performance of the proposed estimators are then compared with those of themaximum likelihood estimators through MonteCarlo simulations. Finally, some illustrative examples are presented to illustrate the methods of estimation developed here.Artigo Poisson–geometric INAR(1) process for modeling count time series with overdispersion(Statistica Neerlandica, 2016) Bourguignon, MarceloIn this paper, we propose a new first-order non-negative integervalued autoregressive [INAR(1)] process with Poisson–geometric marginals based on binomial thinning for modeling integer-valued time series with overdispersion. Also, the new process has, as a particular case, the Poisson INAR(1) and geometric INAR(1) processes. The main properties of the model are derived, such as probability generating function, moments, conditional distribution, higher-order moments, and jumps. Estimators for the parameters of process are proposed, and their asymptotic properties are established. Some numerical results of the estimators are presented with a discussion of the obtained results. Applications to two real data sets are given to show the potentiality of the new process.