A generalized Rayleigh distribution and its application

Tomy, Lishamol; Gillariose, Jiju

doi:10.15406/bbij.2019.08.00282

Cited by 5 publications

(5 citation statements)

References 14 publications

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“…The data represent the strengths of 1.5 cm glass fibers, measured at the National Physical Laboratory, England. The second data in Table (3) represents breaking stress of carbon fibers of 50 mm length (GPa) and have been previously used by [35]. Certain criteria are used in order to compare between the distributions.…”

Section: Applicationmentioning

confidence: 99%

The New Dagum-X Family of Distributions: Properties and Applications

Alghamdi¹,

Al-Ghamdi²,

Fayomi³

2023

Int. J. Anal. Appl.

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Various statistical distributions are still being used extensively over the previous decades for modeling data in numerous areas such as engineering, sciences, and finance. Nonetheless, in a lot of applied areas, there is a continuous need for expanded forms of these distributions. However, many common distributions do not fit the data well. Thus, new distributions have been constructed in literature. The purpose of this article is to present a new family of distributions using the Dagum distribution as a generator and to study its properties such as hazard rate functions, moments, quantile function, ordered statistics and Renyi entropy. Moreover, one sub model called Dagum-Frechet distribution is discussed with some of its properties. The maximum likelihood estimation is employed to estimate the parameters of the proposed distribution, and the confidence intervals are obtained. Finally, two real data sets are analyzed to illustrate the performance of the purposed distribution.

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Section: Applicationmentioning

confidence: 99%

The New Dagum-X Family of Distributions: Properties and Applications

Alghamdi¹,

Al-Ghamdi²,

Fayomi³

2023

Int. J. Anal. Appl.

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“…In (1880) Lord Rayleigh presented the Rayleigh distribution [5]. It shows the main role in connection with a problem in various branches modeling and analyzing lifetime data for instance project effort loading modeling, communication, survival and reliability theory, physical sciences, technology, diagnostic imaging, clinical subjects, and applied statistics [7].…”

Section: 𝑂 𝑖 Represents the Observed Frequency In Class I 𝐸 𝑖 Represents The Expected Frequency In Class Imentioning

confidence: 99%

“…Now, based on an invariant property of the 𝑀𝐿𝐸 estimator, the survival function at mission time (t) of the 𝐸𝑅 distribution can be obtained by replacing 𝛼 and 𝜆 in equation (7), by their 𝑀𝐿𝐸 estimators as follows:…”

Section: Maximum Likelihood Estimationmentioning

confidence: 99%

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An Estimation of Survival and Hazard Rate Functions of Exponential Rayleigh Distribution

Hussein¹,

Hussein²,

Rasheed³

2021

IHJPAS

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In this paper, we used the maximum likelihood estimation method to find the estimation values â€‹â€‹for survival and hazard rate functions of the Exponential Rayleigh distribution based on a sample of the real data for lung cancer and stomach cancer obtained from the Iraqi Ministry of Health and Environment, Department of Medical City, Tumor Teaching Hospital, depending on patients' diagnosis records and number of days the patient remains in the hospital until his death.

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“…This distribution finds its significance in numerous disciplines such as Physical Science, Engineering, Medical Sciences, and so on. For instance An extension of Rayleigh distribution and its properties by Kahkashan Ateeq, Tahira Bano Qasim and Ayesha Rehman Alvi [1], A generalized Rayleigh distribution and its applications by Lishamol Tomy and jiju Gillariose [2], Odd Lindley-Rayleigh distribution by Terna Godfrey Ieren [3], New generalization of Rayleigh distribution by A.A Bhat et al [4], Top-Leone power Rayleigh distribution with properties and application related in engineering sciences by Aijaz et al [5], Alpha-Power Exponentiated Inverse Rayleigh Distribution and its applications to real and simulated data(2021).…”

Section: Original Research Articlementioning

confidence: 99%

A New Two-Parametric Maxwell-Rayleigh Distribution: Application to the Analysis of Engineering Data

Jallal

Ahmad

Tripathi

2021

AJPAS

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In this study a new generalisation of Rayleigh Distribution has been studied and referred it is as “A New Two-Parametric Maxwell-Rayleigh Distribution”. This distribution is obtained by adopting T-X family procedure. Several distributional properties of the formulated distribution including moments, moment generating function, Characteristics function and incomplete moments have been discussed. The expressions for ageing properties have been derived and discussed explicitly. The behaviour of the pdf and Hazard rate function has been illustrated through different graphs. The parameters are estimated through the technique of MLE. Eventually the versatility and the efficacy of the formulated distribution have been examined through real life data sets related to engineering science.

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A generalized Rayleigh distribution and its application

Cited by 5 publications

References 14 publications

The New Dagum-X Family of Distributions: Properties and Applications

The New Dagum-X Family of Distributions: Properties and Applications

An Estimation of Survival and Hazard Rate Functions of Exponential Rayleigh Distribution

A New Two-Parametric Maxwell-Rayleigh Distribution: Application to the Analysis of Engineering Data

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