This paper introduces and studies a unique probability distribution. The maximum likelihood estim... more This paper introduces and studies a unique probability distribution. The maximum likelihood estimation, the ordinary least squares, the weighted least squares, and the Anderson–Darling estimation methods all take into account a number of financial risk indicators, including the value-at-risk, tail-value-at-risk, tail variance, tail mean-variance, and mean excess loss function. These four approaches were used in a simulation study and an application to insurance claims data for the actuarial evaluation. The well-known Nikulin–Rao–Robson statistic is taken into consideration for distributional validation under the whole set of data. Three complete actual datasets and a simulation study are used to evaluate the Nikulin–Rao–Robson test statistic. An updated version of the Nikulin–Rao–Robson statistic is taken into consideration for censored distributional validation. Three censored actual datasets and a thorough simulation analysis are used to evaluate the novel Nikulin–Rao–Robson test ...
Journal of Advances in Applied & Computational Mathematics, 2020
The logistic-X (LX) family of distributions based on the logistic random variable was formulated ... more The logistic-X (LX) family of distributions based on the logistic random variable was formulated recently by Tahir et al. [1]. We study a new special model of this family called the logistic exponentiated-exponential (LEE) distribution. Its density function can be symmetric, left-skewed, right-skewed, and reversed-J shaped, and its hazard rate can be decreasing and upside-down bathtub shapes. We provide a useful power series for its quantile function and a mixture representation for its density function. The parameters of the LEE model are estimated by maximum likelihood. Three Ozone data sets are modeled to illustrate the applicability of the new model.
A generalization of the Lindley distribution namely, Lindley negative-binomial distribution, is i... more A generalization of the Lindley distribution namely, Lindley negative-binomial distribution, is introduced. The Lindley and the exponentiated Lindley distributions are considered as sub-models of the proposed distribution. The proposed model has flexible density and hazard rate functions. The density function can be decreasing, right-skewed, left-skewed and approximately symmetric. The hazard rate function possesses various shapes including increasing, decreasing and bathtub. Furthermore, the survival and hazard rate functions have closed form representations which make this model tractable for censored data analysis. Some general properties of the proposed model are studied such as ordinary and incomplete moments, moment generating function, mean deviations, Lorenz and Bonferroni curve. The maximum likelihood and the Bayesian estimation methods are utilized to estimate the model parameters. In addition, a small simulation study is conducted in order to evaluate the performance of t...
We propose a new flexible generalized family (NFGF) for constructing many families of distributio... more We propose a new flexible generalized family (NFGF) for constructing many families of distributions. The importance of the NFGF is that any baseline distribution can be chosen and it does not invol...
International Journal of Reliability, Quality and Safety Engineering, 2019
A new three-parameter compounded extended-exponential distribution “Poisson Nadarajah–Haghighi” i... more A new three-parameter compounded extended-exponential distribution “Poisson Nadarajah–Haghighi” is introduced and studied, which is quite flexible and can be used effectively in modeling survival data. It can have increasing, decreasing, upside-down bathtub and bathtub-shaped failure rate. A comprehensive account of the mathematical properties of the model is presented. We discuss maximum likelihood estimation for complete and censored data. The suitability of the maximum likelihood method to estimate its parameters is assessed by a Monte Carlo simulation study. Four empirical illustrations of the new model are presented to real data and the results are quite satisfactory.
Journal of Statistical Computation and Simulation, 2017
ABSTRACT We study some mathematical properties of a new generator of continuous distributions wit... more ABSTRACT We study some mathematical properties of a new generator of continuous distributions with one extra parameter called the odd power Cauchy family including asymptotics, linear representation, moments, quantile and generating functions, entropies, order statistics and extreme values. We introduce two bivariate extensions of the new family. The maximum likelihood method is discussed to estimate the model parameters by means of a Monte Carlo simulation study. We define a new log-odd power Cauchy–Weibull regression model. The usefulness of the proposed models is proved empirically by means of three real data sets.
Communications in Statistics - Theory and Methods, 2018
ABSTRACT We introduce a three-parameter extension of the exponential distribution which contains ... more ABSTRACT We introduce a three-parameter extension of the exponential distribution which contains as sub-models the exponential, logistic-exponential and Marshall-Olkin exponential distributions. The new model is very flexible and its associated density function can be decreasing or unimodal. Further, it can produce all of the four major shapes of the hazard rate, that is, increasing, decreasing, bathtub and upside-down bathtub. Given that closed-form expressions are available for the survival and hazard rate functions, the new distribution is quite tractable. It can be used to analyze various types of observations including censored data. Computable representations of the quantile function, ordinary and incomplete moments, generating function and probability density function of order statistics are obtained. The maximum likelihood method is utilized to estimate the model parameters. A simulation study is carried out to assess the performance of the maximum likelihood estimators. Two actual data sets are used to illustrate the applicability of the proposed model.
We introduce and study some general mathematical properties of a new generator of continuous dist... more We introduce and study some general mathematical properties of a new generator of continuous distributions with two extra parameters called the Gompertz-G generator. We present some special models. We investigate the shapes of the density and hazard functions and derive explicit expressions for the ordinary and incomplete moments, quantile and generating functions, probability weighted moments, Bonferroni and Lorenz curves, Shannon and Rényi entropies, and order statistics. Two bivariate extensions of this model are proposed. We discuss the estimation of the model parameters by maximum likelihood and prove empirically the potentiality of the new class by means of two real data sets.
We propose a new generator of continuous distributions with one extra positive parameter called t... more We propose a new generator of continuous distributions with one extra positive parameter called the odd Lindley-G family. Some special cases are presented. The new density function can be expressed as a linear combination of exponentiated densities based on the same baseline distribution. Various structural properties of the new family, which hold for any baseline model, are derived including explicit expressions for the quantile function, ordinary and incomplete moments, generating function, Renyi entropy, reliability, order statistics and their moments and k upper record values. We discuss estimation of the model parameters by maximum likelihood and provide an application to a real data set.
Communications in Statistics - Theory and Methods, 2016
ABSTRACT We introduce and study general mathematical properties of a new generator of continuous ... more ABSTRACT We introduce and study general mathematical properties of a new generator of continuous distributions with one extra parameter called the generalized odd half-Cauchy family. We present some special models and investigate the asymptotics and shapes. The new density function can be expressed as a linear mixture of exponentiated densities based on the same baseline distribution. We derive a power series for the quantile function. We discuss the estimation of the model parameters by maximum likelihood and prove empirically the flexibility of the new family by means of two real data sets.
Journal of Statistical Computation and Simulation, 2016
ABSTRACT We study a new family of continuous distributions with two extra shape parameters called... more ABSTRACT We study a new family of continuous distributions with two extra shape parameters called the Burr generalized family of distributions. We investigate the shapes of the density and hazard rate function. We derive explicit expressions for some of its mathematical quantities. The estimation of the model parameters is performed by maximum likelihood. We prove the flexibility of the new family by means of applications to two real data sets. Furthermore, we propose a new extended regression model based on the logarithm of the Burr generalized distribution. This model can be very useful to the analysis of real data and provide more realistic fits than other special regression models.
This paper introduces and studies a unique probability distribution. The maximum likelihood estim... more This paper introduces and studies a unique probability distribution. The maximum likelihood estimation, the ordinary least squares, the weighted least squares, and the Anderson–Darling estimation methods all take into account a number of financial risk indicators, including the value-at-risk, tail-value-at-risk, tail variance, tail mean-variance, and mean excess loss function. These four approaches were used in a simulation study and an application to insurance claims data for the actuarial evaluation. The well-known Nikulin–Rao–Robson statistic is taken into consideration for distributional validation under the whole set of data. Three complete actual datasets and a simulation study are used to evaluate the Nikulin–Rao–Robson test statistic. An updated version of the Nikulin–Rao–Robson statistic is taken into consideration for censored distributional validation. Three censored actual datasets and a thorough simulation analysis are used to evaluate the novel Nikulin–Rao–Robson test ...
Journal of Advances in Applied & Computational Mathematics, 2020
The logistic-X (LX) family of distributions based on the logistic random variable was formulated ... more The logistic-X (LX) family of distributions based on the logistic random variable was formulated recently by Tahir et al. [1]. We study a new special model of this family called the logistic exponentiated-exponential (LEE) distribution. Its density function can be symmetric, left-skewed, right-skewed, and reversed-J shaped, and its hazard rate can be decreasing and upside-down bathtub shapes. We provide a useful power series for its quantile function and a mixture representation for its density function. The parameters of the LEE model are estimated by maximum likelihood. Three Ozone data sets are modeled to illustrate the applicability of the new model.
A generalization of the Lindley distribution namely, Lindley negative-binomial distribution, is i... more A generalization of the Lindley distribution namely, Lindley negative-binomial distribution, is introduced. The Lindley and the exponentiated Lindley distributions are considered as sub-models of the proposed distribution. The proposed model has flexible density and hazard rate functions. The density function can be decreasing, right-skewed, left-skewed and approximately symmetric. The hazard rate function possesses various shapes including increasing, decreasing and bathtub. Furthermore, the survival and hazard rate functions have closed form representations which make this model tractable for censored data analysis. Some general properties of the proposed model are studied such as ordinary and incomplete moments, moment generating function, mean deviations, Lorenz and Bonferroni curve. The maximum likelihood and the Bayesian estimation methods are utilized to estimate the model parameters. In addition, a small simulation study is conducted in order to evaluate the performance of t...
We propose a new flexible generalized family (NFGF) for constructing many families of distributio... more We propose a new flexible generalized family (NFGF) for constructing many families of distributions. The importance of the NFGF is that any baseline distribution can be chosen and it does not invol...
International Journal of Reliability, Quality and Safety Engineering, 2019
A new three-parameter compounded extended-exponential distribution “Poisson Nadarajah–Haghighi” i... more A new three-parameter compounded extended-exponential distribution “Poisson Nadarajah–Haghighi” is introduced and studied, which is quite flexible and can be used effectively in modeling survival data. It can have increasing, decreasing, upside-down bathtub and bathtub-shaped failure rate. A comprehensive account of the mathematical properties of the model is presented. We discuss maximum likelihood estimation for complete and censored data. The suitability of the maximum likelihood method to estimate its parameters is assessed by a Monte Carlo simulation study. Four empirical illustrations of the new model are presented to real data and the results are quite satisfactory.
Journal of Statistical Computation and Simulation, 2017
ABSTRACT We study some mathematical properties of a new generator of continuous distributions wit... more ABSTRACT We study some mathematical properties of a new generator of continuous distributions with one extra parameter called the odd power Cauchy family including asymptotics, linear representation, moments, quantile and generating functions, entropies, order statistics and extreme values. We introduce two bivariate extensions of the new family. The maximum likelihood method is discussed to estimate the model parameters by means of a Monte Carlo simulation study. We define a new log-odd power Cauchy–Weibull regression model. The usefulness of the proposed models is proved empirically by means of three real data sets.
Communications in Statistics - Theory and Methods, 2018
ABSTRACT We introduce a three-parameter extension of the exponential distribution which contains ... more ABSTRACT We introduce a three-parameter extension of the exponential distribution which contains as sub-models the exponential, logistic-exponential and Marshall-Olkin exponential distributions. The new model is very flexible and its associated density function can be decreasing or unimodal. Further, it can produce all of the four major shapes of the hazard rate, that is, increasing, decreasing, bathtub and upside-down bathtub. Given that closed-form expressions are available for the survival and hazard rate functions, the new distribution is quite tractable. It can be used to analyze various types of observations including censored data. Computable representations of the quantile function, ordinary and incomplete moments, generating function and probability density function of order statistics are obtained. The maximum likelihood method is utilized to estimate the model parameters. A simulation study is carried out to assess the performance of the maximum likelihood estimators. Two actual data sets are used to illustrate the applicability of the proposed model.
We introduce and study some general mathematical properties of a new generator of continuous dist... more We introduce and study some general mathematical properties of a new generator of continuous distributions with two extra parameters called the Gompertz-G generator. We present some special models. We investigate the shapes of the density and hazard functions and derive explicit expressions for the ordinary and incomplete moments, quantile and generating functions, probability weighted moments, Bonferroni and Lorenz curves, Shannon and Rényi entropies, and order statistics. Two bivariate extensions of this model are proposed. We discuss the estimation of the model parameters by maximum likelihood and prove empirically the potentiality of the new class by means of two real data sets.
We propose a new generator of continuous distributions with one extra positive parameter called t... more We propose a new generator of continuous distributions with one extra positive parameter called the odd Lindley-G family. Some special cases are presented. The new density function can be expressed as a linear combination of exponentiated densities based on the same baseline distribution. Various structural properties of the new family, which hold for any baseline model, are derived including explicit expressions for the quantile function, ordinary and incomplete moments, generating function, Renyi entropy, reliability, order statistics and their moments and k upper record values. We discuss estimation of the model parameters by maximum likelihood and provide an application to a real data set.
Communications in Statistics - Theory and Methods, 2016
ABSTRACT We introduce and study general mathematical properties of a new generator of continuous ... more ABSTRACT We introduce and study general mathematical properties of a new generator of continuous distributions with one extra parameter called the generalized odd half-Cauchy family. We present some special models and investigate the asymptotics and shapes. The new density function can be expressed as a linear mixture of exponentiated densities based on the same baseline distribution. We derive a power series for the quantile function. We discuss the estimation of the model parameters by maximum likelihood and prove empirically the flexibility of the new family by means of two real data sets.
Journal of Statistical Computation and Simulation, 2016
ABSTRACT We study a new family of continuous distributions with two extra shape parameters called... more ABSTRACT We study a new family of continuous distributions with two extra shape parameters called the Burr generalized family of distributions. We investigate the shapes of the density and hazard rate function. We derive explicit expressions for some of its mathematical quantities. The estimation of the model parameters is performed by maximum likelihood. We prove the flexibility of the new family by means of applications to two real data sets. Furthermore, we propose a new extended regression model based on the logarithm of the Burr generalized distribution. This model can be very useful to the analysis of real data and provide more realistic fits than other special regression models.
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Papers by Gauss Cordeiro