Inferences for the DUS-Exponential Distribution Based on Upper Record Values

Tripathi, Ayush; Singh, Umesh; Singh, Sanjay Kumar

doi:10.1007/s40745-019-00231-6

Cited by 6 publications

(5 citation statements)

References 21 publications

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“…In recent years, neutrosophic statistics is appear and are defined as an extension of classical statistics and one deal with set values instead of crisp values. Ashbacher [5] introduced fuzzy logic and neutrosophy, for more details on neutrosophic statistics, see [25,26,28]. Many authors interested in neutrosophic probability distribution and are shown that it is better than the classical statistics in real life problems such as [25] introduced the neutrosophic Weibull distribution, [22,23] introduced neutrosophic beta distribution, Patro and Smarandache [19] introduced neutrosophic normal distribution and neutrosophic binomial distribution.…”

Section: Introductionmentioning

confidence: 99%

DUS-neutrosophic multivariate inverse Weibull distribution: properties and applications

Hassan

Aslam

2023

Complex Intell. Syst.

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The existing DUS-multivariate inverse Weibull distribution under classical statistics can be applied when all observations in the data are imprecise. In this paper, we introduce DUS-neutrosophic multivariate inverse Weibull distribution that can be used when the observations in the data are imprecise or in intervals. We derive some statistical properties and functions of DUS-neutrosophic multivariate inverse Weibull distribution. We also discuss the maximum likelihood estimation method for estimating the parameters. Monte-Carlo simulation study is performed to study the behavior of maximum likelihood estimates. We compare the efficiency of the proposed DUS-neutrosophic multivariate inverse Weibull distribution with the existing distributions under classical statistics. From the comparison, it is found that the proposed DUS-neutrosophic multivariate inverse Weibull distribution provides smaller values of Akaike’s information criteria and Bayesian information criteria than the existing distributions under classical statistics. The proposed study can be extended for other statistical distributions as future research.

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Section: Introductionmentioning

confidence: 99%

DUS-neutrosophic multivariate inverse Weibull distribution: properties and applications

Hassan

Aslam

2023

Complex Intell. Syst.

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“…Making the transition from classical to neutrosophic statistics is one technique; depending on the types of indeterminacies, however, numerous approaches may be available. Several advances have been made in recent years to model such inaccurate situations using fuzzy logic and neutrosophy [5,9,34,36,39,40]. In addition, according to neutrosophic logic, the parameters take undetermined values which arise while working with statistical data, particularly when working with vague and inaccurate statistical data [5].…”

Section: Introductionmentioning

confidence: 99%

“…In addition, according to neutrosophic logic, the parameters take undetermined values which arise while working with statistical data, particularly when working with vague and inaccurate statistical data [5]. Smarandache [33,36] proposed that a logical statement can be represented in a 3D Neutrosophic Space, where each dimension of the space represents the statement's Truth (T), Falsehood (F), and Indeterminacy (I). Several studies have been conducted using neutrosophic probability distributions to calculate indeterminacy in real-world scenarios, with better results than classical statistics.…”

Section: Introductionmentioning

confidence: 99%

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A new neutrosophic model using DUS-Weibull transformation with application

Nayana

Anakha

Chacko

et al. 2022

Complex Intell. Syst.

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There is a need to comprehend real-world problems that are marked by ambiguity and inflexibility. By taking into account the indeterminacies and inconsistencies, DUS transformation has been taken to Neutrosophic Weibull distribution and DUS-Neutrosophic Weibull distribution is proposed. The probability density function is unimodal and decreasing in nature. Several statistical properties have been studied. The parameters of the proposed distribution are estimated using the maximum likelihood method. The proposed distribution has been validated on a real data set. The estimates are found to be more accurate than the classical distributions.

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“…After that, a considerable number of authors have studied records and associated inferential problems. For more details related to the problems associated with record values, readers may refer (Galambos, 1978), (Nevzorov, 1987), (Bunge & Nagaraja, 1992), (Arnold, Balakrishnan, & Nagaraja, 1998), (Balakrishnan & Chan, 1998), (Raqab & Ahsanullah, 2001), (Ahsanullah & Nevzorov, 2015), (Shafay, Balakrishnan, & Ahmadi, 2017), (Tripathi, Singh, & Singh, 2019), (Tripathi, Singh, & Kumar Singh, 2021).…”

Section: Introductionmentioning

confidence: 99%

Model Discrimination Based on Record Values

Tripathi¹,

Singh²,

Singh³

2022

JSR

Self Cite

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In this study, the problem of model discrimination is discussed when only record data are available. The models considered are inverse Rayleigh and inverted exponential distribution. The ratio of the maximized likelihoods is used for discriminating between the two distribution functions. The probability of correct selection and power of the test are obtained through Monte Carlo simulation method for different sample sizes of record values. The problem is discussed for both lower as well as upper records. Real datasets are considered to illustrate the applicability of the proposed method.Index Terms-Inverse Rayleigh (IR) distribution, lower and upper record values, inverted exponential (IE) distribution, likelihood ratio (LR) test, probability of correct selection (PCS) and power of the test.

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Inferences for the DUS-Exponential Distribution Based on Upper Record Values

Cited by 6 publications

References 21 publications

DUS-neutrosophic multivariate inverse Weibull distribution: properties and applications

DUS-neutrosophic multivariate inverse Weibull distribution: properties and applications

A new neutrosophic model using DUS-Weibull transformation with application

Model Discrimination Based on Record Values

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