Yazar "Saracoglu, Bugra" seçeneğine göre listele

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    Maximum Likelihood Estimation for the Parameters of the Generalized Gompertz Distribution under Progressive Type-II Right Censored Samples
    (Selçuk Üniversitesi, 2015) Demir, Ecem; Saracoglu, Bugra
    In this study, it is obtained maximum likelihood estimators (MLEs) for the unknown parameters of the Generalized Gompertz (GG) distribution under progressive type II censored sample. The MLEs can not be obtained in closed forms. But, MLEs can be computed with Newton Raphson method. The Mean Square Error (MSE)s and biases of the ML estimators are computed using Monte Carlo simulation method.
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    A new statistical distribution: cubic rank transmuted Kumaraswamy distribution and its properties
    (NATL SCIENCE FOUNDATION SRI LANKA, 2018) Saracoglu, Bugra; Tanis, Caner
    This article suggests a new statistical distribution named 'Cubic rank transmuted Kumaraswamy distribution' using cubic rank transmutation map. Various statistical properties of this new distribution such as, hazard function and its graphics, moments, variance, coefficients of skewness and kurtosis, moment generating function and order statistics are examined. In estimation problem, the maximum likelihood estimators of unknown parameters of this distribution are derived. A Monte Carlo simulation study based on bias and mean square error criteria of this estimator is conducted. Also, this new distribution is compared with other well known distributions in terms of fitting to the total milk production proportion, operation and empirical datasets in previous studies.
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    Statistical inference of stress-strength reliability for the exponential power (EP) distribution based on progressive type-II censored samples
    (HACETTEPE UNIV, FAC SCI, 2017) Akdam, Neriman; Kinaci, Ismail; Saracoglu, Bugra
    Suppose that X represents the stress which is applied to a component and Y is strength of this component. Let X and Y have Exponential Power (EP) distribution with (alpha(1), beta(1)) and (alpha(2), beta(2)) parameters, respectively. In this case, stress-strength reliability (SSR) is shown by P = P (X < Y). In this study, the SSR for EP distribution are obtained with numerical methods. Also maximum likelihood estimate (MLE) and approximate bayes estimates by using Lindley approximation method under squared-error loss function for SSR under progressive type-II censoring are obtained. Moreover, performances of these estimators are compared in terms of MSEs by using Monte Carlo simulation. Furthermore coverage probabilities of parametric bootstrap estimates are computed. Finally, real data analysis is presented.