Now showing items 1-4 of 4

    • Characterizing Log-Logistic (LL) Distributions through Methods of Percentiles and L-Moments 

      Pant, Mohan (HIKARI LtdDepartment of Curriculum and Instruction, University of Texas at Arlington, January 25)
      The main purpose of this paper is to characterize the log-logistic (LL) distributions through the methods of percentiles and L-moments and contrast with the method of (product) moments. The method of (product) moments ...
    • An L-Moment Based Characterization of the Family of Dagum Distributions 

      Pant, Mohan; Headrick, Todd C. (Scienpress Ltd.Department of Curriculum and Instruction, The University of Texas at Arlington, 2013)
      This paper introduces a method for simulating univariate and multivariate Dagum distributions through the method of 𝐿-moments and 𝐿-correlations. A method is developed for characterizing non-normal Dagum distributions ...
    • A Method for Simulating Burr Type III and Type XII Distributions through 𝐿-Moments and 𝐿-Correlations 

      Pant, Mohan; Headrick, Todd C. (Hindawi Publishing CorporationDepartment of Curriculum and Instruction, The University of Texas at Arlington, 2013)
      This paper derives the Burr Type III and Type XII family of distributions in the contexts of univariate 𝐿-moments and the 𝐿- correlations. Included is the development of a procedure for specifying nonnormal distributions ...
    • Simulating Uniform- and Triangular- Based Double Power Method Distributions 

      Pant, Mohan; Headrick, Todd C. (Scienpress LtdDepartment of Curriculum & Instruction, The University of Texas at Arlington, 2017)
      Power method (PM) polynomials have been used for simulating non-normal distributions in a variety of settings such as toxicology research, price risk, business-cycle features, microarray analysis, computer adaptive ...