Confluent hypergeometric slashed-Rayleigh distribution: Properties, estimation and applications

Olmos, Neveka M.; Venegas, Osvaldo; Gómez, Yolanda M.; Iriarte, Yuri A.

doi:10.1016/j.cam.2019.112548

Cited by 3 publications

(2 citation statements)

References 14 publications

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“…The main aim of the authors was to generate a model with a higher kurtosis that allows better modeling of positive data in the presence of outliers. Other authors have worked on a similar idea, e.g., Iriarte et al [7], Reyes et al [8], Olmos et al [9], Segovia et al [10], and Astorga et al [11].…”

Section: Introductionmentioning

confidence: 94%

Slash Truncation Positive Normal Distribution and Its Estimation Based on the EM Algorithm

2021

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In this paper, we present an extension of the truncated positive normal (TPN) distribution to model positive data with a high kurtosis. The new model is defined as the quotient between two random variables: the TPN distribution (numerator) and the power of a standard uniform distribution (denominator). The resulting model has greater kurtosis than the TPN distribution. We studied some properties of the distribution, such as moments, asymmetry, and kurtosis. Parameter estimation is based on the moments method, and maximum likelihood estimation uses the expectation-maximization algorithm. We performed some simulation studies to assess the recovery parameters and illustrate the model with a real data application related to body weight. The computational implementation of this work was included in the tpn package of the R software.

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Section: Introductionmentioning

confidence: 94%

Slash Truncation Positive Normal Distribution and Its Estimation Based on the EM Algorithm

2021

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“…Reference Olmos et al [10] also used this methodology to introduce the modified slashed half-normal distribution. Reference Olmos et al [11] recently introduced the confluent, hypergeometric slashed-Rayleigh distribution using the same methodology. The Maxwell distribution was first set out by Maxwell [12], and gave the distribution of velocities among the molecules of a gas.…”

Section: Introductionmentioning

confidence: 99%

A Power Maxwell Distribution with Heavy Tails and Applications

et al. 2020

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In this paper we introduce a distribution which is an extension of the power Maxwell distribution. This new distribution is constructed based on the quotient of two independent random variables, the distributions of which are the power Maxwell distribution and a function of the uniform distribution (0,1) respectively. Thus the result is a distribution with greater kurtosis than the power Maxwell. We study the general density of this distribution, and some properties, moments, asymmetry and kurtosis coefficients. Maximum likelihood and moments estimators are studied. We also develop the expectation–maximization algorithm to make a simulation study and present two applications to real data.

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Understanding the Time and Frequency Varying Characteristics of a Multipath Wireless Channel

Khuda

Farooq

Ebrahim

et al. 2021

Wireless Pers Commun

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Confluent hypergeometric slashed-Rayleigh distribution: Properties, estimation and applications

Cited by 3 publications

References 14 publications

Slash Truncation Positive Normal Distribution and Its Estimation Based on the EM Algorithm

Slash Truncation Positive Normal Distribution and Its Estimation Based on the EM Algorithm

A Power Maxwell Distribution with Heavy Tails and Applications

Understanding the Time and Frequency Varying Characteristics of a Multipath Wireless Channel

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