SOME TOPICS RELATED TO TRANSFORMATIONS, DISTRIBUTION FUNCTIONS AND STOCHASTIC PROCESSES

Abstract

This report is divided into four independent sections. Section 1 contains a theorem giving sufficient conditions for the asymptotic distribution of a standardized location-scale random variable to have the distribution of a power of the random variable, and examples showing that the conditions are not necessary. Section 2 gives illustrations of the problem of deciding whether or not one random variable is a transform of another; and, in each case in which a transformation of the one random variable into the other is assured, the set of all such transformations is investigated. Section 3 consists of an example of the notion of robustness of a test as well as a tentative general definition of the concept of robustness of a test, and a brief study of the Kolmogorov metric on the space of location-parameter distributions. Section 4 presents simple iterative solutions of special systems of differential-difference equations, in which the constant coefficient matrices are triangular and satisfy conditions sufficient to insure that the solutions involve only exponential terms or terms that are products of linear factors and exponential factors. These methods are applied to the simple stochastic epidemic and to the general stochastic epidemic.

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Document Details

Document Type
Technical Report
Publication Date
Nov 01, 1966
Accession Number
AD0651648

Entities

People

  • Norman C. Severo
  • Paul J. Schillo
  • Robert H. Rodine

Organizations

  • University at Buffalo

Tags

Communities of Interest

  • C4I
  • Energy and Power Technologies
  • Space

DTIC Thesaurus Topics

  • Air Force
  • Clearances
  • Coefficients
  • Data Science
  • Difference Equations
  • Differential Equations
  • Distribution Functions
  • Equations
  • Information Science
  • New York
  • Numbers
  • Partial Differential Equations
  • Probability
  • Random Variables
  • Real Numbers
  • Statistics
  • Stochastic Processes

Fields of Study

  • Mathematics

Readers

  • Business Analytics
  • Calculus or Mathematical Analysis
  • Statistical inference.

Technology Areas

  • Space