scholarly journals The Gumbel- Pareto Distribution: Theory and Applications

2019 ◽  
Vol 16 (4) ◽  
pp. 0937
Author(s):  
Saad Et al.
Keyword(s):  
Maximum Likelihood ◽  
Pareto Distribution ◽  
Real Data ◽  
Model Parameters ◽  
Numerical Illustration ◽  
Data Set ◽  
Mathematical Properties ◽  
Method Of Maximum Likelihood ◽  
First Time ◽  
New Distribution

In this paper, for the first time we introduce a new four-parameter model called the Gumbel- Pareto distribution by using the T-X method. We obtain some of its mathematical properties. Some structural properties of the new distribution are studied. The method of maximum likelihood is used for estimating the model parameters. Numerical illustration and an application to a real data set are given to show the flexibility and potentiality of the new model.

scholarly journals SOME PROPERTIES OF BETA TRANSMUTED DAGUM DISTRIBUTION WITH APPLICATIONS

2020 ◽  
Vol 4 (2) ◽  
pp. 327-340
Author(s):  
Ahmed Ali Hurairah ◽  
Saeed A. Hassen
Keyword(s):  
Maximum Likelihood ◽  
Likelihood Estimation ◽  
Real Data ◽  
Moment Generating Function ◽  
Model Parameters ◽  
Data Set ◽  
New Family ◽  
Method Of Maximum Likelihood ◽  
Dagum Distribution ◽  
New Distribution

In this paper, we introduce a new family of continuous distributions called the beta transmuted Dagum distribution which extends the beta and transmuted familys. The genesis of the beta distribution and transmuted map is used to develop the so-called beta transmuted Dagum (BTD) distribution. The hazard function, moments, moment generating function, quantiles and stress-strength of the beta transmuted Dagum distribution (BTD) are provided and discussed in detail. The method of maximum likelihood estimation is used for estimating the model parameters. A simulation study is carried out to show the performance of the maximum likelihood estimate of parameters of the new distribution. The usefulness of the new model is illustrated through an application to a real data set.

scholarly journals The Extended Marshall-Olkin Burr III Distribution: Properties and Applications

2021 ◽  
pp. 1-14
Author(s):  
Muhammad Ahsan ul Haq ◽  
Ahmed Z. Afify ◽  
Hazem Al- Mofleh ◽  
Rana Muhammad Usman ◽  
Mohammed Alqawba ◽  
...  
Keyword(s):  
Maximum Likelihood ◽  
Density Function ◽  
Continuous Distribution ◽  
Real Data ◽  
Model Parameters ◽  
Data Set ◽  
Mathematical Properties ◽  
Proposed Model ◽  
Method Of Maximum Likelihood ◽  
Burr Iii Distribution

We study a new continuous distribution called the Marshall-Olkin modified Burr III distribution. The density function of the proposed model can be expressed as a mixture of modified Burr III densities. A comprehensive account of its mathematical properties is derived. The model parameters are estimated by the method of maximum likelihood. The usefulness of the derived model is illustrated over other distributions using a real data set.

scholarly journals General Results for the Transmuted Family of Distributions and New Models

2016 ◽  
Vol 2016 ◽  
pp. 1-12 ◽  
Author(s):  
Marcelo Bourguignon ◽  
Indranil Ghosh ◽  
Gauss M. Cordeiro
Keyword(s):  
Maximum Likelihood ◽  
Generating Functions ◽  
Real Data ◽  
Model Parameters ◽  
Data Set ◽  
Proposed Model ◽  
Method Of Maximum Likelihood ◽  
The Family ◽  
New Models ◽  
Family Of Distributions

The transmuted family of distributions has been receiving increased attention over the last few years. For a baselineGdistribution, we derive a simple representation for the transmuted-Gfamily density function as a linear mixture of theGand exponentiated-Gdensities. We investigate the asymptotes and shapes and obtain explicit expressions for the ordinary and incomplete moments, quantile and generating functions, mean deviations, Rényi and Shannon entropies, and order statistics and their moments. We estimate the model parameters of the family by the method of maximum likelihood. We prove empirically the flexibility of the proposed model by means of an application to a real data set.

scholarly journals Complementary Kumaraswamy Weibull Power Series Distribution: Some Properties and Application

2020 ◽  
pp. 361-398
Author(s):  
Innocent Boyle Eraikhuemen ◽  
Julian Ibezimako Mbegbu ◽  
Friday Ewere
Keyword(s):  
Power Series ◽  
Likelihood Estimation ◽  
Real Data ◽  
Model Parameters ◽  
Data Set ◽  
Power Series Distribution ◽  
Mathematical Properties ◽  
Method Of Maximum Likelihood ◽  
The Family ◽  
Distance Problem

In this paper, we propose Complementary Kumaraswamy Weibull Power Series (CKWPS) Distributions. The method is obtained by compounding the Kumaraswamy-G distribution and Power Series distribution on a latent complementary distance problem base. The mathematical properties of the proposed class of distribution are studied. The method of Maximum Likelihood Estimation is used for obtaining the estimates of the model parameters. A member of the family is investigated in detail. Finally an application of the proposed class is illustrated using a real data set.

scholarly journals THE BETA TRANSMUTED POWER DISTRIBUTION: PROPERTIES AND APPLICATION

2019 ◽  
Vol 3 (1) ◽  
pp. 105-123
Author(s):  
Abdelhakim Alabid ◽  
Ahmed Ali Hurairah ◽  
Indonesian Journal of Statistics and Its Applications IJSA
Keyword(s):  
Probability Distribution ◽  
Power Distribution ◽  
Asymptotic Variance ◽  
Real Data ◽  
Mean Deviation ◽  
Model Parameters ◽  
Data Set ◽  
Method Of Maximum Likelihood ◽  
Asymptotic Confidence Intervals ◽  
New Distribution

In this this paper, we define and study a new generalization of the Power distribution and the quadratic rank transmutation map (QRTM) in order to generate a flexible family of probability distribution taking Power distribution as the base distribution. The new distribution is called the beta transmuted Power (BTP) distribution. Some properties of the distribution such as moments, quantiles, mean deviation and order statistics are derived. The method of maximum likelihood is proposed to estimate the model parameters. The asymptotic confidence intervals for the parameters are also obtained based on asymptotic variance-covariance matrix. A simulation study is conducted to study the performance of the estimators. The importance and flexibility of the new model is proved empirically using a real data set.

Extended exponentiated Nadarajah-Haghighi model: Mathematical properties, characterizations and applications

2018 ◽  
Vol 55 (4) ◽  
pp. 498-522
Author(s):  
Morad Alizadeh ◽  
Mahdi Rasekhi ◽  
Haitham M. Yousof ◽  
Thiago G. Ramires ◽  
G. G. Hamedani
Keyword(s):  
Maximum Likelihood ◽  
Survival Data ◽  
Likelihood Estimation ◽  
Real Data ◽  
Rate Function ◽  
Likelihood Method ◽  
Model Parameters ◽  
Failure Rate Function ◽  
Data Set ◽  
Mathematical Properties

In this article, a new four-parameter model is introduced which can be used in mod- eling survival data and fatigue life studies. Its failure rate function can be increasing, decreasing, upside down and bathtub-shaped depending on its parameters. We derive explicit expressions for some of its statistical and mathematical quantities. Some useful characterizations are presented. Maximum likelihood method is used to estimate the model parameters. The censored maximum likelihood estimation is presented in the general case of the multi-censored data. We demonstrate empirically the importance and exibility of the new model in modeling a real data set.

scholarly journals The New Odd Log-Logistic Generalized Inverse Gaussian Regression Model

2019 ◽  
Vol 2019 ◽  
pp. 1-13 ◽  
Author(s):  
Julio Cezar Souza Vasconcelos ◽  
Gauss M. Cordeiro ◽  
Edwin M. M. Ortega ◽  
Elton G. Araújo
Keyword(s):  
Maximum Likelihood ◽  
Regression Model ◽  
Generalized Inverse ◽  
Real Data ◽  
Model Parameters ◽  
Inverse Gaussian ◽  
Method Of Maximum Likelihood ◽  
Generalized Inverse Gaussian ◽  
Gaussian Regression ◽  
New Distribution

We define a new four-parameter model called the odd log-logistic generalized inverse Gaussian distribution which extends the generalized inverse Gaussian and inverse Gaussian distributions. We obtain some structural properties of the new distribution. We construct an extended regression model based on this distribution with two systematic structures, which can provide more realistic fits to real data than other special regression models. We adopt the method of maximum likelihood to estimate the model parameters. In addition, various simulations are performed for different parameter settings and sample sizes to check the accuracy of the maximum likelihood estimators. We provide a diagnostics analysis based on case-deletion and quantile residuals. Finally, the potentiality of the new regression model to predict price of urban property is illustrated by means of real data.

scholarly journals A Log-Beta Rayleigh Lomax Regression Model

2021 ◽  
Vol 16 (4) ◽  
pp. 2993-3007
Author(s):  
Nofiu Idowu Badmus ◽  
Mary Idowu Akinyemi ◽  
Josephine Nneamaka Onyeka-Ubaka
Keyword(s):  
Regression Model ◽  
Survival Data ◽  
Real Data ◽  
Model Parameters ◽  
Data Set ◽  
Cancer Data ◽  
Normal Probability ◽  
Method Of Maximum Likelihood ◽  
Classical Models ◽  
First Time

For the first time, a location-scale regression model based on the logarithm of an extended Raleigh Lomax distribution which has the ability to deal and model of any survival data than classical regression model is introduced. We obtain the estimate for the model parameters using the method of maximum likelihood by considering breast cancer data. In addition, normal probability plot of the residual is used to detect the outliers and evaluate model assumptions. We use a real data set to illustrate the performance of the new model, some of its submodels and classical models consider in the study. Also, we perform the statistics AIC, BIC and CAIC to select the most appropriate model among those regression models considered in the study.

Modified New Flexible Weibull Distribution

2017 ◽  
Vol 2 (6) ◽  
pp. 7-13
Author(s):  
Zubair Ahmad ◽  
Zawar Hussain
Keyword(s):  
Maximum Likelihood ◽  
Weibull Distribution ◽  
Mathematical Description ◽  
Real Data ◽  
Reliability Function ◽  
Model Parameters ◽  
Data Set ◽  
Mathematical Properties ◽  
Proposed Model ◽  
Parameter Modification

The present paper is devoted to introduce a four-parameter modification of new flexible Weibull distribution. The proposed model will be called modified new flexible Weibull distribution, able to model lifetime phenomena with increasing or bathtub-shaped failure rates. Some of its mathematical properties will be studied. The approach of maximum likelihood will be used for estimating the model parameters. A brief mathematical description for the reliability function will also be discussed. The usefulness of the proposed distribution will be illustrated by an application to a real data set.

scholarly journals Extending Singh-Maddala Distribution

2021 ◽  
Vol 19 (1) ◽  
pp. 2-23
Author(s):  
Mohammed Ali Ahmed
Keyword(s):  
Maximum Likelihood ◽  
Estimation Method ◽  
Real Data ◽  
Parameters Estimation ◽  
Random Numbers ◽  
Data Set ◽  
Mathematical Properties ◽  
New Distribution

A new distribution, the exponentiated transmuted Singh-Maddala distribution (ETSM), is presented, and three important special distributions are illustrated. Some mathematical properties are obtained, and parameters estimation method is applied using maximum likelihood. Illustrations based on random numbers and a real data set are given.

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