A New Odd F-Weibull Distribution: Properties and Application of the Monthly Nigerian Naira to British Pound Exchange Rate Data

Ishaq, Aliyu Ismail; Usman, A.; Tasi'u, M.; Suleiman, Aminu; Ahmad, Adnan

doi:10.1109/icdabi56818.2022.10041527

Cited by 7 publications

(7 citation statements)

References 14 publications

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“…Different versions of ∆(G(x)) might produce a new class of continuous distributions, albeit this is dependent on the limits of a random variable T. Many researchers regarded [44] technique to studying diverse families of distributions. For instance, [47] introduced Odd F generalized class of distribution. Some properties and real-life applications of the novel Odd F-Weibull distribution are provided in [47].…”

Section: The Generalized Odd Maxwell-generated Family Of Distributionsmentioning

confidence: 99%

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The Generalized Odd Maxwell-Kumaraswamy Distribution: Its Properties and Applications

Ishaq,

Panitanarak,

Abiodun

et al. 2024

Contemp. Math.

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This study introduces a novel family of continuous probability distributions using Alzaatreh‘s technique to explore the Generalized Odd Maxwell-Generated (GOM-G) distribution family. Within the Generalized Odd Maxwell family, the GOM-Kumaraswamy distribution is presented as extended form of the Kumaraswamy distribution. The investigation thoroughly examines the cumulative distribution function, probability density function, hazard, and survival functions, as well as mixture representations of the Generalized Odd Maxwell-Kumaraswamy distribution. The suggested distribution's structural properties, including moments, skewness, kurtosis, probability-weighted moments, entropies, stress-strength models, and order statistics, are derived. Model parameters are estimated through the maximum likelihood method, and simulation studies evaluate the performance of maximum likelihood estimations using the quantile function. Employing two real-life datasets, goodness-of-fit measures such as Akaike Information Criterion (AIC), Corrected Akaike Information Criterion, Bayesian Information Criterion (BIC), Hannan-Quinn Information Criterion (HQIC), and chi-square goodness-of-fit tests demonstrate the adaptability and flexibility of the GOM-Kumaraswamy distribution against competing distributions, including Kumaraswamy-Kumaraswamy and Kumaraswamy-Burr III. The results reveal that the GOM-Kumaraswamy distribution exhibits the lowest AIC, CAIC, BIC, and HQIC values and the highest goodness-of-fit values compared to other models, suggesting its superiority as the preferred fit for both dataset forms. This proposed distribution contributes to practical applications, unveiling its potential significance in modeling real-world phenomena within the domains of hydrology and engineering.

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Section: The Generalized Odd Maxwell-generated Family Of Distributionsmentioning

confidence: 99%

“…For instance, [47] introduced Odd F generalized class of distribution. Some properties and real-life applications of the novel Odd F-Weibull distribution are provided in [47].…”

Section: The Generalized Odd Maxwell-generated Family Of Distributionsmentioning

confidence: 99%

The Generalized Odd Maxwell-Kumaraswamy Distribution: Its Properties and Applications

Ishaq,

Panitanarak,

Abiodun

et al. 2024

Contemp. Math.

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“…Suppose X is a random variable that follows log-Kumaraswamy distribution with pdf given in (13), then the moments of X are obtained as…”

Section: Momentsmentioning

confidence: 99%

“…Moreover, several new families of probability distributions have been introduced for modeling data in hydrology, medical science, engineering, insurance, and finance based on the Kumaraswamy distribution method, for instance, Kumaraswamy Weibull [12], Kumaraswamy generalized gamma [13], Kumaraswamy inverse Weibull [14], Kumaraswamy modified inverse Weibull [14], F-Weibull [15], Kumaraswamy Gumbel [16], Kumaraswamy log-logistic [17], Kumaraswamy exponentiated Pareto [18], Kumaraswamy modified Weibull [19], Kumaraswamy generalized Lomax [20], Kumaraswamy [21], Kumaraswamy half-Cauchy [22], Kumaraswamy generalized Rayleigh [23], Kumaraswamy skew-normal [24], Kumaraswamy inverse Weibull Poisson [25], odd beta prime-logistic distribution [26], Kumaraswamy Marshall-Olkin Fréchet [27], Kumaraswamy inverse flexible Weibull [28], Maxwell-exponential distribution [29], Kumaraswamy Laplace [30], extensions of the Gompertz and inverse Gaussian, Kumaraswamy Gompertz and Kumaraswamy inverse Gaussian distributions under the Kumaraswamy family of distributions [31], Kumaraswamy skew-t distribution [32], Kumaraswamy transmuted Pareto distribution [33], Kumaraswamy Marshall-Olkin log-logistic distribution [34], Kumaraswamy exponentiated Fréchet distribution [35], Kumaraswamy log-logistic Weibull distribution [36], Kumaraswamy alpha power inverted exponential distribution [37], Kumaraswamy Marshall-Olkin exponential distribution [38], odd beta prime Fréchet distribution [39], Kumaraswamy Inverted Topp-Leone distribution [40], log-Topp-Leone distribution [41], Kumaraswamy Harris generalized Kumaraswamy distribution [42], and generalized transmuted-Kumaraswamy distribution [43]. As studied in [44], Kumaraswamy's cumulative distribution function (cdf) with shape parameters α, β > 0 is given as…”

mentioning

confidence: 99%

Log-Kumaraswamy distribution: its features and applications

Ishaq,

Suleiman,

Daud

et al. 2023

Front. Appl. Math. Stat.

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This article aimed to present a new continuous probability density function for a non-negative random variable that serves as an alternative to some bounded domain distributions. The new distribution, termed the log-Kumaraswamy distribution, could faithfully be employed to compete with bounded and unbounded random processes. Some essential features of this distribution were studied, and the parameters of its estimates were obtained based on the maximum product of spacing, least squares, and weighted least squares procedures. The new distribution was proven to be better than traditional models in terms of flexibility and applicability to real-life data sets.

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“…A similar study was conducted to evaluate the chemical parameters of groundwater using six probability distributions, such as normal, log-normal, gamma, Weibull, logistic, and log-logistic distributions [33]. The following studies can be referred to for more probability distribution modeling works [34][35][36][37][38][39][40][41][42][43][44][45][46][47][48][49][50][51][52].…”

Section: Introductionmentioning

confidence: 99%

Tropically Adapted Passive Building: A Descriptive-Analytical Approach Using Multiple Linear Regression and Probability Models to Predict Indoor Temperature

Salleh,

Suleiman,

Daud

et al. 2023

Sustainability

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The quest for energy efficiency in buildings has placed a demand for designing and modeling energy-efficient buildings. In this study, the thermal energy performance of a tropically adapted passive building was investigated in the warm tropical climate of Malaysia. Two mock-up buildings were built to represent a “green”, made of clay brick double-glazed passive building and a conventional, made of concrete “red” building. The mean indoor temperature of the passive building was found to be always lower than that of the red building throughout the experiment during different weather constellations. Our research builds upon existing work in the field by combining multiple linear regression models and distribution models to provide a comprehensive analysis of the factors affecting the indoor temperature of a building. The results from the fitted multiple linear regression models indicate that walls and windows are critical components that considerably influence the indoor temperature of both passive buildings and red buildings, with the exception of passive buildings during the hot season, where the roof has a greater influence than the window. Furthermore, the goodness-of-fit test results of the mean indoor temperature revealed that the Fréchet and Logistic probability models fitted the experimental data in both cold and hot seasons. It is intended that the findings of this study would help tropical countries to devise comfortable, cost-effective passive buildings that are green and energy efficient to mitigate global warming.

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A New Odd F-Weibull Distribution: Properties and Application of the Monthly Nigerian Naira to British Pound Exchange Rate Data

Cited by 7 publications

References 14 publications

The Generalized Odd Maxwell-Kumaraswamy Distribution: Its Properties and Applications

The Generalized Odd Maxwell-Kumaraswamy Distribution: Its Properties and Applications

Log-Kumaraswamy distribution: its features and applications

Tropically Adapted Passive Building: A Descriptive-Analytical Approach Using Multiple Linear Regression and Probability Models to Predict Indoor Temperature

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