STRUCTURE INFERENCE AND STOCHASTIC GRAPHS,

Abstract

Population structures are considered, represented by finite graphs without parallel arrows in the same direction between any pair of nodes. In Chapter 1 are introduced various structure concepts, operations on graphs and matrices, relations between different structure properties, and some structure parameters. Chapter 2 describes various sampling schemes for extracting from a portion of a graph information about the whole graph. Inference from the observed structure to the population structure is discussed in Chapters 3 and 4. Examples are given to show how unbiased estimators of various structure parameters may be obtained. Chapter 5 shortly treats multi-stage sampling. Chapter 6 is devoted to stochastic graphs. Means and variances are given for some structure parameters under different assumptions about the stochastic graphs. (Author)

Document Details

Document Type
Technical Report
Publication Date
Jun 16, 1968
Accession Number
AD0687176

Entities

People

  • Ove Frank

Tags

DTIC Thesaurus Topics

  • Algorithms
  • Collecting Methods
  • Estimators
  • Sampling

Fields of Study

  • Mathematics

Readers

  • Business Analytics
  • Computational Linguistics
  • Statistical inference.

Technology Areas

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