Linear Models, Statistical Information, and Statistical Inference.

Abstract

Research on linear models and statistical information and inference is described. Chapter I deals with parametric augmentations and error structures under which certain simple least squares and analysis of variance procedures are also best. Chapter 2 develops efficient methods for the analysis of variance of balanced complete experimental data on a digital computer. Chapter 3 considers linear spaces and unbiased estimation with application to the mixed linear model. Chapter 4 deals with questions in statistical information theory and related measures of information. Chapter 5 presents a general discussion by O. Kempthorne on implications of theories of inference to applied statistics. (Author)

Document Details

Document Type
Technical Report
Publication Date
May 01, 1971
Accession Number
AD0728653

Entities

People

  • Abel G. Mexas
  • G. Zyskind
  • Justus Seely
  • O. Kempthorne
  • P. Papaioannou

Organizations

  • Iowa State University

Tags

DTIC Thesaurus Topics

  • Analysis Of Variance
  • Computers
  • Computing-Related Activities
  • Data Science
  • Digital Computers
  • Experimental Data
  • Information Science
  • Information Theory
  • Interdisciplinary Science
  • Mathematics
  • Statistical Inference
  • Statistics

Fields of Study

  • Mathematics

Readers

  • Business Analytics
  • Regression Analysis.
  • Statistical inference.

Technology Areas

  • AI & ML
  • AI & ML - Bayesian Inference
  • Space