scholarly journals The Adjusted Log-logistic Generalized Exponential Distribution with Application to Lifetime Data

2017 ◽  
Vol 5 (4) ◽  
pp. 1
Author(s):  
I. E. Okorie ◽  
A. C. Akpanta ◽  
J. Ohakwe ◽  
D. C. Chikezie ◽  
C. U. Onyemachi ◽  
...  
Keyword(s):  
Exponential Distribution ◽  
Likelihood Estimation ◽  
Model Parameters ◽  
Data Sets ◽  
Lifetime Data ◽  
Generalized Exponential Distribution ◽  
Data Set ◽  
Method Of Maximum Likelihood ◽  
The One ◽  
Special Case

This paper introduces a new generator of probability distribution-the adjusted log-logistic generalized (ALLoG) distribution and a new extension of the standard one parameter exponential distribution called the adjusted log-logistic generalized exponential (ALLoGExp) distribution. The ALLoGExp distribution is a special case of the ALLoG distribution and we have provided some of its statistical and reliability properties. Notably, the failure rate could be monotonically decreasing, increasing or upside-down bathtub shaped depending on the value of the parameters $\delta$ and $\theta$. The method of maximum likelihood estimation was proposed to estimate the model parameters. The importance and flexibility of he ALLoGExp distribution was demonstrated with a real and uncensored lifetime data set and its fit was compared with five other exponential related distributions. The results obtained from the model fittings shows that the ALLoGExp distribution provides a reasonably better fit than the one based on the other fitted distributions. The ALLoGExp distribution is therefore ecommended for effective modelling of lifetime data sets.

scholarly journals Length biased Weighted New Quasi Lindley Distribution: Statistical Properties and Applications

2021 ◽  
pp. 123-136
Author(s):  
Rashid A. Ganaie ◽  
V. Rajagopalan
Keyword(s):  
Information Matrix ◽  
Real Life ◽  
Likelihood Estimation ◽  
Model Parameters ◽  
Data Sets ◽  
Lindley Distribution ◽  
Method Of Maximum Likelihood ◽  
Special Case ◽  
Biased Distribution ◽  
Length Biased Distribution

In this Paper, we have introduced a new version of new quasi lindley distribution known as the length-biased weighted new quasi lindley distribution (LBWNQLD). Length biased distribution is a special case of weighted distribution. The different structural properties of the newly proposed distribution are derived and the model parameters are estimated by using the method of maximum likelihood estimation and also the Fisher’s information matrix have been discussed. Finally, applications to real life two data sets are presented for illustration.

scholarly journals The Exponentiated Gumbel Type-2 Distribution: Properties and Application

2016 ◽  
Vol 2016 ◽  
pp. 1-10 ◽  
Author(s):  
I. E. Okorie ◽  
A. C. Akpanta ◽  
J. Ohakwe
Keyword(s):  
Lifetime Distribution ◽  
The Other ◽  
Maximum Likelihood Estimates ◽  
Model Parameters ◽  
Lifetime Data ◽  
Data Set ◽  
Method Of Maximum Likelihood ◽  
Log Likelihood ◽  
New Distribution

We introduce a generalized version of the standard Gumble type-2 distribution. The new lifetime distribution is called the Exponentiated Gumbel (EG) type-2 distribution. The EG type-2 distribution has three nested submodels, namely, the Gumbel type-2 distribution, the Exponentiated Fréchet (EF) distribution, and the Fréchet distribution. Some statistical and reliability properties of the new distribution were given and the method of maximum likelihood estimates was proposed for estimating the model parameters. The usefulness and flexibility of the Exponentiated Gumbel (EG) type-2 distribution were illustrated with a real lifetime data set. Results based on the log-likelihood and information statistics values showed that the EG type-2 distribution provides a better fit to the data than the other competing distributions. Also, the consistency of the parameters of the new distribution was demonstrated through a simulation study. The EG type-2 distribution is therefore recommended for effective modelling of lifetime data.

scholarly journals HALF LOGISTIC MODIFIED EXPONENTIAL DISTRIBUTION: PROPERTIES AND APPLICATIONS

2020 ◽  
pp. 276-287
Author(s):  
Arun Kumar Chaudhary ◽  
Vijay Kumar
Keyword(s):  
Exponential Distribution ◽  
Likelihood Estimation ◽  
Real Data ◽  
Least Square ◽  
Estimation Methods ◽  
Logistic Distribution ◽  
Model Parameters ◽  
Type I ◽  
Data Set ◽  
Von Mises

In this study, we have introduced a three-parameter probabilistic model established from type I half logistic-Generating family called half logistic modified exponential distribution. The mathematical and statistical properties of this distribution are also explored. The behavior of probability density, hazard rate, and quantile functions are investigated. The model parameters are estimated using the three well known estimation methods namely maximum likelihood estimation (MLE), least-square estimation (LSE) and Cramer-Von-Mises estimation (CVME) methods. Further, we have taken a real data set and verified that the presented model is quite useful and more flexible for dealing with a real data set. KEYWORDS— Half-logistic distribution, Estimation, CVME ,LSE, , MLE

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 Weibull-G Poisson Family for Analyzing Lifetime Data

2020 ◽  
pp. 131-148 ◽  
Author(s):  
Haitham Yousof ◽  
Muhammad Mansoor ◽  
Morad Alizadeh ◽  
Ahmed Afify ◽  
Indranil Ghosh
Keyword(s):  
Generating Functions ◽  
Likelihood Estimation ◽  
Real Data ◽  
Model Parameters ◽  
Data Sets ◽  
Lifetime Data ◽  
New Family ◽  
Mathematical Properties ◽  
Independent Identically Distributed ◽  
Family Of Distributions

We study a new family of distributions defined by the minimum of the Poissonrandom number of independent identically distributed random variables having a general Weibull-G distribution (see Bourguignon et al. (2014)). Some mathematical properties of the new family including ordinary and incomplete moments, quantile and generating functions, mean deviations, order statistics, reliability and entropies are derived. Maximum likelihood estimation of the model parameters is investigated. Three special models of the new family are discussed. We perform three applications to real data sets to show the potentiality of theproposed family.

scholarly journals Generalized Weighted Rama Distribution: Properties and Application to Model Lifetime Data

2021 ◽  
pp. 9-37
Author(s):  
Samuel U. Enogwe ◽  
Chisimkwuo John ◽  
Happiness O. Obiora-Ilouno ◽  
Chrisogonus K. Onyekwere
Keyword(s):  
Maximum Likelihood ◽  
Likelihood Estimation ◽  
Real Data ◽  
Maximum Likelihood Estimates ◽  
Model Parameters ◽  
Data Sets ◽  
Estimation Of Parameters ◽  
Data Set ◽  
Bathtub Shape ◽  
Asymptotic Confidence Intervals

In this paper, we propose a new lifetime distribution called the generalized weighted Rama (GWR) distribution, which extends the two-parameter Rama distribution and has the Rama distribution as a special case. The GWR distribution has the ability to model data sets that have positive skewness and upside-down bathtub shape hazard rate. Expressions for mathematical and reliability properties of the GWR distribution have been derived. Estimation of parameters was achieved using the method of maximum likelihood estimation and a simulation was performed to verify the stability of the maximum likelihood estimates of the model parameters. The asymptotic confidence intervals of the parameters of the proposed distribution are obtained. The applicability of the GWR distribution was illustrated with a real data set and the results obtained show that the GWR distribution is a better candidate for the data than the other competing distributions being investigated.

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 Weibull Logistic-exponential Distribution: Its Properties and Applications

2020 ◽  
pp. 197-216
Author(s):  
I. U. Akata ◽  
J. E. Osemwenkhae
Keyword(s):  
Exponential Distribution ◽  
Estimation Method ◽  
Likelihood Estimation ◽  
Lifetime Data ◽  
Data Set ◽  
Lifetime Distributions ◽  
Mathematical Properties ◽  
Maximum Likelihood Estimation Method ◽  
New Distribution ◽  
Generalized Distribution

In this paper, a new generalized distribution known as Weibull Logistic-Exponential Distribution (WLED) is proposed using the T-R{Y} framework. Several mathematical properties of this new distribution are studied. The maximum likelihood estimation method was used in estimating the parameters of the proposed distribution. Finally, an application of the proposed distribution to a real lifetime data set is presented and its fit was compared with the fit obtained by some comparable lifetime distributions.

scholarly journals The Odd Log-Logistic Generalized Half-Normal Lifetime Poisson Model

2019 ◽  
pp. 111-128
Author(s):  
Fazlollah Lak ◽  
Mehdi Basikhasteh ◽  
Morad Alizadeh ◽  
Haitham M. Yousof
Keyword(s):  
Random Number ◽  
Poisson Model ◽  
Model Parameters ◽  
Data Sets ◽  
Lifetime Data ◽  
Simulation Studies ◽  
Fatigue Lifetime ◽  
Method Of Maximum Likelihood ◽  
Fatigue Data ◽  
Lifetime Model

Recently, Corderio et al. (2016) applied a model called odd-logistic generalized half-normal distribution for describing fatigue lifetime data, based on this model, we propose a new wider model with a strong physical motivation called the odd-log-logistic generalized half-normal poisson distribution which is commonly used in reliability studies and modeling maximum of a random number of lifetime variables. Various of its structural properties are derived. The method of maximum likelihood is adapted to estimate the model parameters and its potentiality is illustrated with applications to two real fatigue data sets. For different parameter settings and sample sizes, some simulation studies compare the performance of the new lifetime model.

scholarly journals The Poisson Topp Leone Generator of Distributions for Lifetime Data: Theory, Characterizations and Applications

2020 ◽  
pp. 343-355 ◽  
Author(s):  
Faton Merovci ◽  
Haitham Yousof ◽  
G. G Hamedani
Keyword(s):  
Generating Functions ◽  
Random Number ◽  
Likelihood Estimation ◽  
Real Data ◽  
Model Parameters ◽  
Lifetime Data ◽  
Data Set ◽  
New Family ◽  
Independent Identically Distributed ◽  
Family Of Distributions

We study a new family of distributions defined by the minimum of the Poisson random number of independent identically distributed random variables having a Topp Leone-G distribution (see Rezaei et al., (2016)). Some mathematicalproperties of the new family including ordinary and incomplete moments, quantile and generating functions, mean deviations, order statistics, reliability and entropies are derived. Maximum likelihood estimation of the model parameters is investigated. Some special models of the newfamily are discussed. An application is carried out on  real data set applications sets to show the potentiality of the proposed family.

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