STATISTICAL INFERENCE IN STOCHASTIC PROCESSES

Abstract

The following topics are the principal ones investigated under this grant: (1) Hypothesis testing for Poisson-like processes. (2) Hilbert space methods in time series analysis. (3) Limit distributions of branching processes. (4) Hausdorff dimension in stochastic processes. (5) Sufficient statistics for stochastic processes. (6) Absolute continuity and orthogonality of stochastic processes. (7) Subordination of stochastic processes. (8) Slowly varying functions in probability. (9) Mixture problems and the Glivenko- Cantelli Theorem. (10) Random power series.

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Document Details

Document Type
Technical Report
Publication Date
Jun 01, 1967
Accession Number
AD0659794

Entities

People

  • Howard G. Tucker

Organizations

  • University of California, Riverside

Tags

Communities of Interest

  • Materials and Manufacturing Processes

DTIC Thesaurus Topics

  • Computing-Related Activities
  • Continuity
  • Data Science
  • Hilbert Space
  • Information Science
  • Interdisciplinary Science
  • Mathematical Analysis
  • Military Research
  • North Carolina
  • Power Series
  • Probability
  • Statistical Inference
  • Statistics
  • Stochastic Processes
  • Time Series Analysis

Fields of Study

  • Mathematics

Readers

  • Mathematical Modeling and Probability Theory.
  • Statistical inference.

Technology Areas

  • AI & ML
  • AI & ML - Bayesian Inference
  • AI & ML - Machine Learning Algorithms
  • Space