scholarly journals The Lomax-Lindley distribution: properties and applications to lifetime data

2021 ◽  
Vol 70 (2) ◽  
pp. 965-983
Author(s):  
Bahman TARVİRDİZADE
Keyword(s):  
Lifetime Data ◽  
Lindley Distribution

scholarly journals New class of Lindley distributions: properties and applications

2021 ◽  
Vol 8 (1) ◽  
Author(s):  
Duha Hamed ◽  
Ahmad Alzaghal
Keyword(s):  
Maximum Likelihood ◽  
Maximum Likelihood Estimation ◽  
Simulation Study ◽  
Likelihood Estimation ◽  
Statistical Properties ◽  
Data Sets ◽  
Lifetime Data ◽  
Unknown Parameters ◽  
Lindley Distribution ◽  
New Class

AbstractA new generalized class of Lindley distribution is introduced in this paper. This new class is called the T-Lindley{Y} class of distributions, and it is generated by using the quantile functions of uniform, exponential, Weibull, log-logistic, logistic and Cauchy distributions. The statistical properties including the modes, moments and Shannon’s entropy are discussed. Three new generalized Lindley distributions are investigated in more details. For estimating the unknown parameters, the maximum likelihood estimation has been used and a simulation study was carried out. Lastly, the usefulness of this new proposed class in fitting lifetime data is illustrated using four different data sets. In the application section, the strength of members of the T-Lindley{Y} class in modeling both unimodal as well as bimodal data sets is presented. A member of the T-Lindley{Y} class of distributions outperformed other known distributions in modeling unimodal and bimodal lifetime data sets.

scholarly journals The Weighted Power Lindley Distribution with Applications on the Life Time Data

2020 ◽  
pp. 225-237
Author(s):  
Aafaq A. Rather ◽  
Gamze Özel
Keyword(s):  
Information Matrix ◽  
Life Time ◽  
Real Data ◽  
Data Sets ◽  
Lifetime Data ◽  
Time Data ◽  
Data Set ◽  
Lindley Distribution ◽  
Power Lindley Distribution ◽  
New Distribution

In this paper, we have proposed a new version of power lindley distribution known as weighted power lindley distribution. The different structural properties of the newly model have been studied. The maximum likelihood estimators of the parameters and the Fishers information matrix have been discussed. It also provides more flexibility to analyze complex real data sets.  An application of the model to a real data set is analyzed using the new distribution, which shows that the weighted power Lindley distribution can be used quite effectively in analyzing real lifetime data.

scholarly journals On a new generalized lindley distribution: Properties, estimation and applications

PLoS ONE ◽  
2021 ◽  
Vol 16 (2) ◽  
pp. e0244328
Author(s):  
Ali Algarni
Keyword(s):  
Asymptotic Variance ◽  
Real Data ◽  
Lifetime Data ◽  
Unknown Parameters ◽  
Data Set ◽  
Lindley Distribution ◽  
New Family ◽  
Proposed Model ◽  
The Subject ◽  
Mean Square Error Criterion

In this study, an extension of the generalized Lindley distribution using the Marshall-Olkin method and its own sub-models is presented. This new model for modelling survival and lifetime data is flexible. Several statistical properties and characterizations of the subject distribution along with its reliability analysis are presented. Statistical inference for the new family such as the Maximum likelihood estimators and the asymptotic variance covariance matrix of the unknown parameters are discussed. A simulation study is considered to compare the efficiency of the different estimators based on mean square error criterion. Finally, a real data set is analyzed to show the flexibility of our proposed model compared with the fit attained by some other competitive distributions.

scholarly journals A New Two-Parameter Lindley Distribution

2020 ◽  
Vol 1 ◽  
pp. 33-42
Author(s):  
Rama Shanker ◽  
Umme Habibah Rahman
Keyword(s):  
Maximum Likelihood ◽  
Goodness Of Fit ◽  
Fisher Information Matrix ◽  
Information Matrix ◽  
Likelihood Estimation ◽  
Lifetime Data ◽  
Lindley Distribution ◽  
Method Of Maximum Likelihood ◽  
Two Parameter ◽  
Family Of Distributions

In this paper, a new two-parameter Lindley distribution has been proposed. Descriptive statistical properties along with order statistics, Fisher information matrix and confidence interval of the proposed distribution have been discussed. Parameters are estimated by the method of Maximum Likelihood estimation. A real lifetime data has been presented to test the goodness of fit of the proposed distribution over other one parameter and two –parameter Lindley family of distributions.

scholarly journals An Extended Generalized Lindley Distribution and Its Applications to Lifetime Data

2015 ◽  
Vol 11 (2) ◽  
pp. 203-222
Author(s):  
H Torabi ◽  
M Falahati-Naeini ◽  
N.H Montazeri ◽  
◽  
◽  
...  
Keyword(s):  
Lifetime Data ◽  
Lindley Distribution

scholarly journals An Extended Lindley Distribution with Application to Lifetime Data with Bayesian Estimation

2021 ◽  
Vol 9 (4) ◽  
pp. 849-870
Author(s):  
Morad Alizadeh ◽  
Vahid Ranjbar ◽  
Abbas Eftekharian ◽  
Omid Kharazmi
Keyword(s):  
Bayesian Analysis ◽  
Gibbs Sampling ◽  
Simulation Study ◽  
Asymptotic Properties ◽  
Data Sets ◽  
Lifetime Data ◽  
Lindley Distribution ◽  
Hazard Functions ◽  
Distribution Parameters ◽  
High Flexibility

A four-parameter extended of Lindley distribution with application to lifetime data is introduced.It is called extended Marshal-Olkin generalized Lindley distribution. Some mathematical propertiessuch as moments, skewness, kurtosis and extreme value are derived. These properties with plotsof density and hazard functions are shown the high flexibility of the mentioned distribution. Themaximum likelihood estimations of proposed distribution parameters with asymptotic properties ofthese estimations are examined. A simulation study to investigate the performance of maximumlikelihood estimations is presented. Moreover, the performance and flexibility of the new distributionare investigated by comparing with several generalizations of Lindley distribution through two realdata sets. Finally, Bayesian analysis and efficiency of Gibbs sampling are provided based on the tworeal data sets.

scholarly journals A Notable Bounded Probability Distribution for Environmental and Lifetime Data

2021 ◽  
Author(s):  
Hassan Bakouch ◽  
Tassaddaq Hussain ◽  
Christophe Chesneau ◽  
Jónás Tamás
Keyword(s):  
Probability Distribution ◽  
Return Period ◽  
Annual Rainfall ◽  
Lifetime Data ◽  
Lindley Distribution ◽  
Rainfall Analysis ◽  
Gamma Distributions ◽  
Proposed Model ◽  
Competing Models ◽  
Points Of View

Abstract In this article, we introduce a notable bounded distribution based on a modification of the epsilon function which creates an upper bound on the domain of the distribution. Further, a key feature of the distribution links the readers with the asymptotic connections with the famous Lindley distribution, which is a weighted variant of the exponential distribution and also a mixture of exponential and gamma distributions. In some ways, the proposed distribution provides a flexible solution to the modeling of bounded characteristics that can be almost well-fitted by the Lindley distribution if the domain is restricted. Moreover, we have also explored its application, particularly with reference to lifetime and environmental points of view, and found that the proposed model exhibits a better fit among the competing models. Further, from the annual rainfall analysis, the proposed model exhibits a realistic return period of the rainfall.

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