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Full-Text Articles in Physical Sciences and Mathematics
A Doubling Technique For The Power Method Transformations, Mohan D. Pant, Todd C. Headrick
A Doubling Technique For The Power Method Transformations, Mohan D. Pant, Todd C. Headrick
Mohan Dev Pant
Power method polynomials are used for simulating non-normal distributions with specified product moments or L-moments. The power method is capable of producing distributions with extreme values of skew (L-skew) and kurtosis (L-kurtosis). However, these distributions can be extremely peaked and thus not representative of real-world data. To obviate this problem, two families of distributions are introduced based on a doubling technique with symmetric standard normal and logistic power method distributions. The primary focus of the methodology is in the context of L-moment theory. As such, L-moment based systems of equations are derived for simulating univariate and multivariate non-normal distributions with …
An L-Moment-Based Analog For The Schmeiser-Deutsch Class Of Distributions, Todd C. Headrick, Mohan D. Pant
An L-Moment-Based Analog For The Schmeiser-Deutsch Class Of Distributions, Todd C. Headrick, Mohan D. Pant
Mohan Dev Pant
This paper characterizes the conventional moment-based Schmeiser-Deutsch (S-D) class of distributions through the method of L-moments. The system can be used in a variety of settings such as simulation or modeling various processes. A procedure is also described for simulating S-D distributions with specified L-moments and L-correlations. The Monte Carlo results presented in this study indicate that the estimates of L-skew, L-kurtosis, and L-correlation associated with the S-D class of distributions are substantially superior to their corresponding conventional product-moment estimators in terms of relative bias—most notably when sample sizes are small.
A Logistic L-Moment-Based Analog For The Tukey G-H, G, H, And H-H System Of Distributions, Todd C. Headrick, Mohan D. Pant
A Logistic L-Moment-Based Analog For The Tukey G-H, G, H, And H-H System Of Distributions, Todd C. Headrick, Mohan D. Pant
Mohan Dev Pant
This paper introduces a standard logistic L-moment-based system of distributions. The proposed system is an analog to the standard normal conventional moment-based Tukey g-h, g, h, and h-h system of distributions. The system also consists of four classes of distributions and is referred to as (i) asymmetric γ-κ, (ii) log-logistic γ, (iii) symmetric κ, and (iv) asymmetric κL-κR. The system can be used in a variety of settings such as simulation or modeling events—most notably when heavy-tailed distributions are of interest. A procedure is also described for simulating γ-κ, γ, κ, and κL-κR distributions with specified L-moments and L-correlations. The …
A Method For Simulating Nonnormal Distributions With Specified L-Skew, L-Kurtosis, And L-Correlation, Todd C. Headrick, Mohan D. Pant
A Method For Simulating Nonnormal Distributions With Specified L-Skew, L-Kurtosis, And L-Correlation, Todd C. Headrick, Mohan D. Pant
Mohan Dev Pant
This paper introduces two families of distributions referred to as the symmetric κ and asymmetric κL-κR distributions. The families are based on transformations of standard logistic pseudo-random deviates. The primary focus of the theoretical development is in the contexts of L-moments and the L-correlation. Also included is the development of a method for specifying distributions with controlled degrees of L-skew, L-kurtosis, and L-correlation. The method can be applied in a variety of settings such as Monte Carlo studies, simulation, or modeling events. It is also demonstrated that estimates of L-skew, L-kurtosis, and L-correlation are superior to conventional product-moment estimates of …
Simulating Non-Normal Distributions With Specified L-Moments And L-Correlations, Todd C. Headrick, Mohan D. Pant
Simulating Non-Normal Distributions With Specified L-Moments And L-Correlations, Todd C. Headrick, Mohan D. Pant
Mohan Dev Pant
This paper derives a procedure for simulating continuous non-normal distributions with specified L-moments and L-correlations in the context of power method polynomials of order three. It is demonstrated that the proposed procedure has computational advantages over the traditional product-moment procedure in terms of solving for intermediate correlations. Simulation results also demonstrate that the proposed L-moment-based procedure is an attractive alternative to the traditional procedure when distributions with more severe departures from normality are considered. Specifically, estimates of L-skew and L-kurtosis are superior to the conventional estimates of skew and kurtosis in terms of both relative bias and relative standard error. …
On The Order Statistics Of Standard Normal-Based Power Method Distributions, Todd C. Headrick, Mohan D. Pant
On The Order Statistics Of Standard Normal-Based Power Method Distributions, Todd C. Headrick, Mohan D. Pant
Mohan Dev Pant
This paper derives a procedure for determining the expectations of order statistics associated with the standard normal distribution (Z) and its powers of order three and five (Z^3 and Z^5). The procedure is demonstrated for sample sizes of n ≤ 9. It is shown that Z^3 and Z^5 have expectations of order statistics that are functions of the expectations for Z and can be expressed in terms of explicit elementary functions for sample sizes of n ≤ 5. For sample sizes of n = 6, 7 the expectations of the order statistics for Z, Z^3, and Z^5 only require a …
A Doubling Method For The Generalized Lambda Distribution, Todd C. Headrick, Mohan D. Pant
A Doubling Method For The Generalized Lambda Distribution, Todd C. Headrick, Mohan D. Pant
Mohan Dev Pant
This paper introduces a new family of generalized lambda distributions (GLDs) based on a method of doubling symmetric GLDs. The focus of the development is in the context of L-moments and L-correlation theory. As such, included is the development of a procedure for specifying double GLDs with controlled degrees of L-skew, L-kurtosis, and L-correlations. The procedure can be applied in a variety of settings such as modeling events and Monte Carlo or simulation studies. Further, it is demonstrated that estimates of L-skew, L-kurtosis, and L-correlation are substantially superior to conventional product-moment estimates of skew, kurtosis, and Pearson correlation in terms …
Characterizing Tukey H And Hh-Distributions Through L-Moments And The L-Correlation, Todd C. Headrick, Mohan D. Pant
Characterizing Tukey H And Hh-Distributions Through L-Moments And The L-Correlation, Todd C. Headrick, Mohan D. Pant
Mohan Dev Pant
This paper introduces the Tukey family of symmetric h and asymmetric hh-distributions in the contexts of univariate L-moments and the L-correlation. Included is the development of a procedure for specifying nonnormal distributions with controlled degrees of L-skew, L-kurtosis, and L-correlations. The procedure can be applied in a variety of settings such as modeling events (e.g., risk analysis, extreme events) and Monte Carlo or simulation studies. Further, it is demonstrated that estimates of L-skew, L-kurtosis, and L-correlation are substantially superior to conventional product-moment estimates of skew, kurtosis, and Pearson correlation in terms of both relative bias and efficiency when heavy-tailed distributions …