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 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 Properties, Inference and Applications of Alpha Power Extended Inverted Weibull Distribution

2020 ◽  
Vol 9 (6) ◽  
pp. 90
Author(s):  
A. A. Ogunde ◽  
S. T. Fayose ◽  
B. Ajayi ◽  
D. O. Omosigho
Keyword(s):  
Weibull Distribution ◽  
Information Matrix ◽  
Real Life ◽  
Simulation Method ◽  
Quantile Function ◽  
Transformation Method ◽  
Model Parameters ◽  
Data Sets ◽  
Alpha Power ◽  
Real Life Data

In this work, we introduce a new generalization of the Inverted Weibull distribution called the alpha power Extended Inverted Weibull distribution using the alpha power transformation method. This approach adds an extra parameter to the baseline distribution. The statistical properties of this distribution including the mean, variance, coefficient of variation, quantile function, median, ordinary and incomplete moments, skewness, kurtosis, moment and moment generating functions, reliability analysis, Lorenz and Bonferroni and curves, Rényi of entropy and order statistics are studied. We consider the method of maximum likelihood for estimating the model parameters and the observed information matrix is derived. Simulation method and three real life data sets are presented to demonstrate the effectiveness of the new model.

scholarly journals On the inferences and applications of transmuted exponential Lomax distribution

2018 ◽  
Vol 6 (1) ◽  
pp. 30
Author(s):  
Umar Kabir ◽  
Terna Godfrey IEREN
Keyword(s):  
Real Life ◽  
Likelihood Estimation ◽  
Cumulative Distribution ◽  
Data Sets ◽  
Lomax Distribution ◽  
Real Life Data ◽  
Method Of Maximum Likelihood ◽  
Probability Density Function Pdf ◽  
New Distribution ◽  
Better Than

This article proposed a new distribution referred to as the transmuted Exponential Lomax distribution as an extension of the popular Lomax distribution in the form of Exponential Lomax by using the Quadratic rank transmutation map proposed and studied in earlier research. Using the transmutation map, we defined the probability density function (PDF) and cumulative distribution function (CDF) of the transmuted Exponential Lomax distribution. Some properties of the new distribution were extensively studied after derivation. The estimation of the distribution’s parameters was also done using the method of maximum likelihood estimation. The performance of the proposed probability distribution was checked in comparison with some other generalizations of Lomax distribution using three real-life data sets. The results obtained indicated that TELD performs better than the other distributions comprising power Lomax, Exponential-Lomax, and the Lomax distributions.

scholarly journals A New Generalization of the Lomax Distribution with Increasing, Decreasing, and Constant Failure Rate

2017 ◽  
Vol 2017 ◽  
pp. 1-6 ◽  
Author(s):  
Pelumi E. Oguntunde ◽  
Mundher A. Khaleel ◽  
Mohammed T. Ahmed ◽  
Adebowale O. Adejumo ◽  
Oluwole A. Odetunmibi
Keyword(s):  
Maximum Likelihood ◽  
Maximum Likelihood Estimation ◽  
Real Life ◽  
Likelihood Estimation ◽  
Model Parameters ◽  
Lomax Distribution ◽  
Life Data ◽  
Real Life Data ◽  
Method Of Maximum Likelihood ◽  
Better Than

Developing new compound distributions which are more flexible than the existing distributions have become the new trend in distribution theory. In this present study, the Lomax distribution was extended using the Gompertz family of distribution, its resulting densities and statistical properties were carefully derived, and the method of maximum likelihood estimation was proposed in estimating the model parameters. A simulation study to assess the performance of the parameters of Gompertz Lomax distribution was provided and an application to real life data was provided to assess the potentials of the newly derived distribution. Excerpt from the analysis indicates that the Gompertz Lomax distribution performed better than the Beta Lomax distribution, Weibull Lomax distribution, and Kumaraswamy Lomax distribution.

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 Modified Laplace Distribution, Its Statistical Properties and Applications

2019 ◽  
pp. 1-14 ◽  
Author(s):  
F. I. Agu ◽  
C. E. Onwukwe
Keyword(s):  
Real Life ◽  
Simulated Data ◽  
Likelihood Estimation ◽  
Laplace Distribution ◽  
Error Distribution ◽  
Statistical Properties ◽  
Data Sets ◽  
Realistic Modeling ◽  
Method Of Maximum Likelihood ◽  
Error Distributions

Increasing the parameter of a distribution helps to capture the skewness and peakedness characteristic in the data sets. This allows a more realistic modeling of data arising from different real life situations. In this paper, we modified Laplace distribution using the exponentiation method. The study proved that the modified Laplace distribution (MLD) is a probability density function. Some of the basic statistical properties of the modified Laplace distribution are obtained. We applied the proposed modified Laplace distribution on two life datasets and simulated data. Parameters of the distributions were estimated using method of maximum likelihood estimation. The study compared the modified Laplace distribution with Laplace distribution and Generalized error distribution using Schwartz Criteria (SC) measure of fitness. The results obtained revealed that the modified Laplace distribution has a better fit than the Laplace and Generalized error distributions and can be used for more realistic modeling of data arising from different real life situations. The simulation results obtained shows that as the sample size increases, the Biasedness and Root Mean Square Error (RMSE) of the proposed modified Laplace distribution reduces.

scholarly journals A Generalized Transmuted Moment Exponential Distribution: Properties and Application

2019 ◽  
pp. 41-52
Author(s):  
Amal S. Hassan ◽  
Ibrahim B. Abdul-Moniem ◽  
Khater A. E. Gad
Keyword(s):  
Exponential Distribution ◽  
Generating Functions ◽  
Likelihood Estimation ◽  
Real Data ◽  
Data Sets ◽  
New Model ◽  
Parameter Estimators ◽  
New Distribution ◽  
Biased Distribution ◽  
Length Biased Distribution

This paper introduces a new generalization of moment exponential (or length biased) distribution. The new model is referred to as generalized transmuted moment exponential distribution. This model contains some new existing distributions. Structural properties of the suggested distribution including closed forms for ordinary and incomplete moments, quantile and generating functions and Rényi entropy are derived. Maximum likelihood estimation is employed to obtain the parameter estimators of the new distribution. We illustrate the importance of the new model by means of three applications to real data sets.

scholarly journals Generalized Beta-Exponential Weibull Distribution and its Applications

2020 ◽  
Vol 24 (1) ◽  
pp. 1-33
Author(s):  
N. I. Badmus ◽  
◽  
Olanrewaju Faweya ◽  
K. A. Adeleke ◽  
◽  
...  
Keyword(s):  
Weibull Distribution ◽  
Information Matrix ◽  
Estimation Method ◽  
Likelihood Estimation ◽  
Real Data ◽  
Quantile Function ◽  
Model Parameters ◽  
Data Sets ◽  
Hazard Functions ◽  
Generalized Distributions

In this article, we investigate a distribution called the generalized beta-exponential Weibull distribution. Beta exponential x family of link function which is generated from family of generalized distributions is used in generating the new distribution. Its density and hazard functions have different shapes and contains special case of distributions that have been proposed in literature such as beta-Weibull, beta exponential, exponentiated-Weibull and exponentiated-exponential distribution. Various properties of the distribution were obtained namely; moments, generating function, Renyi entropy and quantile function. Estimation of model parameters through maximum likelihood estimation method and observed information matrix are derived. Thereafter, the proposed distribution is illustrated with applications to two different real data sets. Lastly, the distribution clearly shown that is better fitted to the two data sets than other distributions.

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 Weibull Birnbaum-Saunders Distribution And Its Applications

2020 ◽  
Vol 9 (1) ◽  
pp. 61-81
Author(s):  
Lazhar BENKHELIFA
Keyword(s):  
Maximum Likelihood ◽  
Estimation Method ◽  
Likelihood Estimation ◽  
Real Data ◽  
Reliability Estimation ◽  
Maximum Likelihood Estimates ◽  
Model Parameters ◽  
Data Sets ◽  
Proposed Model ◽  
Modeling Data

A new lifetime model, with four positive parameters, called the Weibull Birnbaum-Saunders distribution is proposed. The proposed model extends the Birnbaum-Saunders distribution and provides great flexibility in modeling data in practice. Some mathematical properties of the new distribution are obtained including expansions for the cumulative and density functions, moments, generating function, mean deviations, order statistics and reliability. Estimation of the model parameters is carried out by the maximum likelihood estimation method. A simulation study is presented to show the performance of the maximum likelihood estimates of the model parameters. The flexibility of the new model is examined by applying it to two real data sets.

Sign in / Sign up

Export Citation Format

Share Document