scholarly journals The Transmuted Muth Generated Class of Distributions with Applications

Symmetry ◽  
2020 ◽  
Vol 12 (10) ◽  
pp. 1677
Author(s):  
Abdulhakim A. Al-Babtain ◽  
Ibrahim Elbatal ◽  
Christophe Chesneau ◽  
Farrukh Jamal
Keyword(s):  
Survival Data ◽  
Natural Extension ◽  
Real Life ◽  
Environmental Data ◽  
Logistic Distribution ◽  
Data Sets ◽  
New Class ◽  
Real Life Data ◽  
Proposed Model ◽  
Mean And Variance

Recently, the Muth generated class of distributions has been shown to be useful for diverse statistical purposes. Here, we make some contributions to this class by first discussing new theoretical facts and then introducing a natural extension of it via the transmuted scheme. The extended class is described in detail, emphasizing the characteristics of its probability and reliability functions, as well as its moments. Among other things, we show that it can extend the possible values of the mean and variance of the parental distribution, while maintaining symmetry or creating various types of asymmetry. The mathematical inference of the parameters is also discussed. Special attention is paid to the distribution of the new class using the log-logistic distribution as a parent. In an applied work, we evaluate the behavior of the corresponding model by using simulated and practical data. In particular, we employ it to fit two real-life data sets, one with environmental data and the other with survival data. Standard statistical criteria validate the importance of the proposed model.

scholarly journals An Extension of Log-Logistic Distribution for Analyzing Survival Data

2020 ◽  
pp. 789-801
Author(s):  
Aliya Syed Malik ◽  
S.P. Ahmad
Keyword(s):  
Survival Data ◽  
Real Life ◽  
Likelihood Estimation ◽  
Estimation Procedure ◽  
Logistic Distribution ◽  
Data Sets ◽  
Alpha Power ◽  
Real Life Data ◽  
Proposed Model ◽  
New Distribution

In this paper, a new generalization of Log Logistic Distribution using Alpha Power Transformation is proposed. The new distribution is named Alpha Power Log-Logistic Distribution. A comprehensive account of some of its statistical properties are derived. The maximum likelihood estimation procedure is used to estimate the parameters. The importance and utility of the proposed model are proved empirically using two real life data sets.

A new generalized version of Log-logistic distribution with applications in medical sciences and other applied fields

2018 ◽  
Vol 09 (05) ◽  
pp. 1850043
Author(s):  
Bilal Ahmad Para ◽  
Tariq Rashid Jan
Keyword(s):  
Real Life ◽  
Logistic Distribution ◽  
Model Parameters ◽  
Medical Sciences ◽  
Real Life Data ◽  
Proposed Model ◽  
Asymptotic Confidence Intervals ◽  
Mc Simulation ◽  
Robust Measures ◽  
Applied Fields

In this paper, we studied a two-parameter transmuted model of Log-logistic distribution (LLD) using the quadratic rank transmutation map technique studied by Shaw and Buckley1 as a new survival model in medical sciences and other applied fields. Statistical properties of Transmuted LLD (TLLD) are discussed comprehensively. Robust measures of skewness and kurtosis of the proposed model have also been discussed along with graphical overview. The estimation of the model parameters is performed by Maximum Likelihood (ML) method followed by a Monte Carlo (MC) simulation procedure to investigate the performance of the ML estimators and the asymptotic confidence intervals of the parameters. Applications of the proposed model to real-life data are also presented.

scholarly journals A New Three-parameter Xgamma Fréchet Distribution with Different Methods of Estimation and Applications

2021 ◽  
pp. 291-308
Author(s):  
Mohamed Ibrahim Mohamed ◽  
Laba Handique ◽  
Subrata Chakraborty ◽  
Nadeem Shafique Butt ◽  
Haitham M. Yousof
Keyword(s):  
Real Life ◽  
Estimation Methods ◽  
Data Sets ◽  
Clear Preference ◽  
Life Data ◽  
Fréchet Distribution ◽  
Real Life Data ◽  
Proposed Model ◽  
Frechet Distribution

In this article an attempt is made to introduce a new extension of the Fréchet model called the Xgamma Fréchet model. Some of its properties are derived. The estimation of the parameters via different estimation methods are discussed. The performances of the proposed estimation methods are investigated through simulations as well as real life data sets. The potentiality of the proposed model is established through modelling of two real life data sets. The results have shown clear preference for the proposed model compared to several know competing ones.

scholarly journals An extensive extension of exponentiated exponential distribution using alpha power transformation – statistical properties and applications in engineering science

2021 ◽  
Vol 17 (2) ◽  
pp. 59-74
Author(s):  
S. Qurat Ul Ain ◽  
K. Ul Islam Rather
Keyword(s):  
Exponential Distribution ◽  
Real Life ◽  
Statistical Properties ◽  
Data Sets ◽  
Alpha Power ◽  
Real Life Data ◽  
Proposed Model ◽  
Mean Variance ◽  
New Distribution ◽  
Extra Parameter

Abstract In this article, an extension of exponentiated exponential distribution is familiarized by adding an extra parameter to the parent distribution using alpha power technique. The new distribution obtained is referred to as Alpha Power Exponentiated Exponential Distribution. Various statistical properties of the proposed distribution like mean, variance, central and non-central moments, reliability functions and entropies have been derived. Two real life data sets have been applied to check the flexibility of the proposed model. The new density model introduced provides the better fit when compared with other related statistical models.

scholarly journals A New Extended Burr XII Distribution

2017 ◽  
Vol 46 (1) ◽  
pp. 33-39 ◽  
Author(s):  
Indranil Ghosh ◽  
Marcelo Bourguinon
Keyword(s):  
Real Life ◽  
Maximum Likelihood Estimates ◽  
Model Parameters ◽  
Data Sets ◽  
Monte Carlo Simulation Study ◽  
Burr Xii Distribution ◽  
Life Data ◽  
Real Life Data ◽  
Proposed Model ◽  
New Distribution

In this paper, we propose a new lifetime distribution, namely the extended Burr XII distribution (using the technique as mentioned in Cordeiro et al. (2015)). We derive some basic properties of the new distribution and provide a Monte Carlo simulation study to evaluate the maximum likelihood estimates of model parameters. For illustrative purposes, two real life data sets have been considered as an application of the proposed model.

A new kumaraswamy generalized family of distributions: Properties and applications

2020 ◽  
Vol 70 (6) ◽  
pp. 1491-1510
Author(s):  
Muhammad Adnan Hussain ◽  
Muhammad Hussain Tahir ◽  
Gauss M. Cordeiro
Keyword(s):  
Maximum Likelihood ◽  
Real Life ◽  
Linear Representation ◽  
Maximum Likelihood Estimates ◽  
Data Sets ◽  
Modern Distribution ◽  
Real Life Data ◽  
Proposed Model ◽  
Method Of Maximum Likelihood ◽  
Family Of Distributions

AbstractThe Kumaraswamy generalized family of distributions proposed by Cordeiro and de-Castro (2011), has received increased attention in modern distribution theory with 624 google citations, and more than 50 special models have been studied so far. We define another generator, and then propose a new Kumaraswamy generalized family of distributions by inducting this new generator. Some useful properties of the proposed family are obtained such as quantiles, linear representation of the density, moments and generating function. The method of maximum likelihood is used for estimating family parameters. The properties of a special model of the family, called new Kumaraswamy-Burr XII distribution, are reported. A simulation study is conducted to assess the performance of maximum likelihood estimates of the proposed model. Two real-life data sets are analyzed to illustrate the flexibility of proposed model.

scholarly journals Type II Topp-Leone Gumbel Type-2 distribution: Properties and Applications

2021 ◽  
pp. 50-60
Author(s):  
Fatoki Olayode ◽  
Phillips Samuel Ademola ◽  
Adeleye Najeem Friday
Keyword(s):  
Survival Data ◽  
Goodness Of Fit ◽  
Real Life ◽  
Likelihood Estimation ◽  
Life Time ◽  
Data Sets ◽  
Type Ii ◽  
Time Model ◽  
Real Life Data

In this paper, a three parameter life time model named Type II Topp-Leone Gumbel type-2 distribution which can be used to model reliability problems, fatigue life studies, and survival data has been studied. We derived explicit expressions for some of its statistical properties such as ordinary moments, generating function, incomplete moments, and order statistics. The maximum likelihood estimation technique is used to estimate the parameters of the model. The tractability of the model was illustrated by using two real life data sets. The proposed distribution provides a better fit than some well known distributions using criteria of criteria of goodness of fit.

scholarly journals On a Power Transformation of Half-Logistic Distribution

2016 ◽  
Vol 2016 ◽  
pp. 1-10 ◽  
Author(s):  
S. D. Krishnarani
Keyword(s):  
Real Line ◽  
Continuous Distribution ◽  
Real Life ◽  
Logistic Distribution ◽  
Data Sets ◽  
Estimation Of Parameters ◽  
Positive Real ◽  
Real Life Data ◽  
New Distribution ◽  
Positive Real Line

A new continuous distribution on the positive real line is constructed from half-logistic distribution, using a transformation and its analytical characteristics are studied. Some characterization results are derived. Classical procedures for the estimation of parameters of the new distribution are discussed and a comparative study is done through numerical examples. Further, different families of continuous distributions on the positive real line are generated using this distribution. Application is discussed with the help of real-life data sets.

Periodic Streaming Data Reduction Using Flexible Adjustment of Time Section Size

2008 ◽  
pp. 1231-1249
Author(s):  
Jaehoon Kim ◽  
Seong Park
Keyword(s):  
Data Stream ◽  
Estimation Error ◽  
Real Life ◽  
Streaming Data ◽  
Data Sets ◽  
Storage Allocation ◽  
Time Section ◽  
Proper Size ◽  
Real Life Data ◽  
Past Data

Much of the research regarding streaming data has focused only on real time querying and analysis of recent data stream allowable in memory. However, as data stream mining, or tracking of past data streams, is often required, it becomes necessary to store large volumes of streaming data in stable storage. Moreover, as stable storage has restricted capacity, past data stream must be summarized. The summarization must be performed periodically because streaming data flows continuously, quickly, and endlessly. Therefore, in this paper, we propose an efficient periodic summarization method with a flexible storage allocation. It improves the overall estimation error by flexibly adjusting the size of the summarized data of each local time section. Additionally, as the processing overhead of compression and the disk I/O cost of decompression can be an important factor for quick summarization, we also consider setting the proper size of data stream to be summarized at a time. Some experimental results with artificial data sets as well as real life data show that our flexible approach is more efficient than the existing fixed approach.

PROFIT ESTIMATION FOR A PRODUCT UNDER WARRANTY: AN EVALUATION BASED ON CUSTOMER'S EXPECTATION AND SATISFACTION

2014 ◽  
Vol 21 (06) ◽  
pp. 1450029 ◽  
Author(s):  
P. K. KAPUR ◽  
ADARSH ANAND ◽  
NITIN SACHDEVA
Keyword(s):  
Real Life ◽  
Fixed Cost ◽  
Inventory Cost ◽  
Data Set ◽  
Customer Complaints ◽  
Customer Expectation ◽  
Real Life Data ◽  
Proposed Model ◽  
The Difference ◽  
Warranty Claims

Performance of a product not as expected by the customer brings warranty expenditure into the picture. In other words, the deviation of the product performance (PP) from the customer expectation (CE) is the reason for customer complaints and warranty expenses. When this conflicting scenario occurs in market, warranty comes into existence and fulfilling warranty claims of customers adds to product's overall cost. In this paper, based on the difference between PP and CE about the product we estimate profit for the firm. Furthermore, factors like fixed cost, production cost and inventory cost have also been considered in framing the optimization problem. In the proposed model, a two-dimensional innovation diffusion model (TD-IDM) which combines the adoption time of technological diffusion and price of the product has been used. Classical Cobb–Douglas function that takes into account the technological adoptions and other dimensions explicitly has been used to structure the production function. The proposed model has been validated on real life data set.

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