Random Time Processes.

Abstract

Spline estimates of probability density functions were considered and the asymptotic bias and variance of these estimates were determined. Bispectral estimates were employed as a means of getting information about aspects of the nonlinear transfer of energy in turbulence. The behavior of k-dimensional kernel density (probability) estimates and the asymptotic behavior of partial sums of dependent random variables were examined. The relationship between long-range dependence and non-Gaussian structure of the limiting distributions was determined in some cases.

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Document Details

Document Type
Technical Report
Publication Date
May 01, 1981
Accession Number
ADA099045

Entities

People

  • Murray Rosenblatt

Organizations

  • University of California, San Diego

Tags

Communities of Interest

  • Energy and Power Technologies

DTIC Thesaurus Topics

  • Asymptotic Normality
  • Brownian Motion
  • California
  • Data Science
  • Energy
  • Energy Transfer
  • Information Science
  • Mathematics
  • Military Research
  • Multivariate Analysis
  • Probability
  • Probability Density Functions
  • Random Variables
  • Sequences
  • Stationary
  • Stationary Processes
  • Statistics

Readers

  • Statistical inference.