Yazar "Genc, Ali I." seçeneğine göre listele

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    A generalization of the multivariate slash distribution
    (ELSEVIER SCIENCE BV, 2009) Arslan, Olcay; Genc, Ali I.
    In this paper, we propose a generalization of the multivariate slash distribution and investigate some of its properties. We show that the new distribution belongs to the elliptically contoured distributions family, and can have heavier tails than the multivariate slash distribution. Therefore, this generalization of the multivariate slash distribution can be considered as an alternative heavy-tailed distribution for modeling data sets in a variety of settings. We apply the generalized multivariate slash distribution to two real data sets to provide some illustrative examples. (C) 2008 Elsevier B.V. All rights reserved.
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    A generalization of the univariate slash by a scale-mixtured exponential power distribution
    (TAYLOR & FRANCIS INC, 2007) Genc, Ali I.
    A generalization of the slash distribution is derived using the scale mixture of the exponential power distribution. The newly defined family of distributions provides a rich flexibility on the tail heaviness and yields alternative robust estimators of location and scale in non normal situations. In order to investigate asymptotically the bias properties of the estimators, a simulation study is performed. The performance of the estimators on two well-known real data sets is also illustrated.
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    Distribution of linear functions from ordered bivariate log-normal distribution
    (SPRINGER, 2012) Genc, Ali I.
    In this work we consider the problem of finding the distribution of linear functions of the minimum and the maximum of the bivariate log-normal distribution. We derive the distribution function, density function and moments of these statistics. This work will provide a generalization of the minimum and the maximum cases.
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    Estimation of P(X > Y) with ToppLeone distribution
    (TAYLOR & FRANCIS LTD, 2013) Genc, Ali I.
    We consider the estimation problem of the probability P=P(X>Y) for the standard ToppLeone distribution. After discussing the maximum likelihood and uniformly minimum variance unbiased estimation procedures for the problem on both complete and left censored samples, we perform a Monte Carlo simulation to compare the estimators based on the mean square error criteria. We also consider the interval estimation of P.
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    Moments of order statistics of Topp-Leone distribution
    (SPRINGER, 2012) Genc, Ali I.
    We derive explicit algebraic expressions for both of the single and product moments of order statistics from Topp-Leone distribution. We also give an identity about single moments of order statistics. These expressions will be useful for computational purposes.
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    On order statistics from sine distribution
    (TAYLOR & FRANCIS INC, 2007) Genc, Ali I.
    We derive closed form expressions for the first two moments of order statistics from the sine distribution. For the higher moments, a recurrence relation is given. We also give a recurrence relation for the product moments. These relations will be useful for moment computations based on ordered data.
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    The generalized T Birnbaum-Saunders family
    (TAYLOR & FRANCIS LTD, 2013) Genc, Ali I.
    In this work, we generalize the BirnbaumSaunders distribution using the generalized t distribution alternatively to the normal distribution. The newly defined family is positively skewed and contains distributions with different kurtosis and skewness. We study its properties and special cases and demonstrate its use on some real data sets considering the maximum-likelihood estimation procedure.
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    The skew generalized t distribution as the scale mixture of a skew exponential power distribution and its applications in robust estimation
    (TAYLOR & FRANCIS LTD, 2009) Arslan, Olcay; Genc, Ali I.
    In this paper, we consider the family of skew generalized t (SGT) distributions originally introduced by Theodossiou [P. Theodossiou, Financial data and the skewed generalized t distribution, Manage. Sci. Part 1 44 (12) ( 1998), pp. 1650-1661] as a skew extension of the generalized t (GT) distribution. The SGT distribution family warrants special attention, because it encompasses distributions having both heavy tails and skewness, and many of the widely used distributions such as Student's t, normal, Hansen's skew t, exponential power, and skew exponential power (SEP) distributions are included as limiting or special cases in the SGT family. We show that the SGT distribution can be obtained as the scale mixture of the SEP and generalized gamma distributions. We investigate several properties of the SGT distribution and consider the maximum likelihood estimation of the location, scale, and skewness parameters under the assumption that the shape parameters are known. We show that if the shape parameters are estimated along with the location, scale, and skewness parameters, the influence function for the maximum likelihood estimators becomes unbounded. We obtain the necessary conditions to ensure the uniqueness of the maximum likelihood estimators for the location, scale, and skewness parameters, with known shape parameters. We provide a simple iterative re-weighting algorithm to compute the maximum likelihood estimates for the location, scale, and skewness parameters and show that this simple algorithm can be identified as an EM-type algorithm. We finally present two applications of the SGT distributions in robust estimation.