Browsing by Author "Leiva, Víctor"

Now showing 1 - 5 of 5
  • No Thumbnail Available
    Item
    Birnbaum-Saunders quantile regression and its diagnostics with application to economic data
    (2021) Sánchez, L.; Leiva, Víctor; Galea Rojas, Manuel Jesús; Saulo, H.
  • Thumbnail Image
    Item
    Birnbaum-Saunders quantile regression models with application to spatial data
    (2020) Sánchez, Luis; Leiva, Víctor; Galea Rojas, Manuel Jesús; Saulo, Helton
    In the present paper, a novel spatial quantile regression model based on the Birnbaum-Saunders distribution is formulated. This distribution has been widely studied and applied in many fields. To formulate such a spatial model, a parameterization of the multivariate Birnbaum-Saunders distribution, where one of its parameters is associated with the quantile of the respective marginal distribution, is established. The model parameters are estimated by the maximum likelihood method. Finally, a data set is applied for illustrating the formulated model.
  • Thumbnail Image
    Item
    Generalized tobit models : diagnostics and application in econometrics
    (2018) Barros, Michelli; Galea Rojas, Manuel Jesús; Leiva, Víctor; Santos Neto, Manoel
  • Thumbnail Image
    Item
    Influence diagnostics in the tobit censored response model
    (2010) Barros, Michelli; Galea Rojas, Manuel Jesús; González, Manuel; Leiva, Víctor
    In this article, we develop influence diagnostic tools for the tobit model. Specifically, we discuss global influence methods based on the Cook distance and residuals with envelopes, and total and conformal local influence techniques. In order to analyze the sensitivity of the maximum likelihood estimators of the parameters of the model to small perturbations on the assumptions of the model and/or data, we consider several perturbation schemes, such as case-weight and response perturbations. Finally, we illustrate the developed methodology by means of a real data set.
  • Thumbnail Image
    Item
    Influence diagnostics on the coefficient of variation of elliptically contoured distributions
    (2011) Riquelme, Marco; Leiva, Víctor; Galea Rojas, Manuel Jesús; Sanhueza, Antonio
    In this article, we study the behavior of the coefficient of variation (CV) of a random variable that follows a symmetric distribution in the real line. Specifically, we estimate this coefficient using the maximum-likelihood (ML) method. In addition, we provide asymptotic inference for this parameter, which allows us to contrast hypothesis and construct confidence intervals. Furthermore, we produce influence diagnostics to evaluate the sensitivity of the ML estimate of this coefficient when atypical data are present. Moreover, we illustrate the obtained results by using financial real data. Finally, we carry out a simulation study to detect the potential influence of atypical observations on the ML estimator of the CV of a symmetric distribution. The illustration and simulation demonstrate the robustness of the ML estimation of this coefficient.