rdf-syntax-grammar
mods:
  schema location: http://www.loc.gov/mods/v3 http://www.loc.gov/standards/mods/v3/mods-3-2.xsd
  title info:
    title: From comparison density to two sample analysis
  name:
    name part: Parzen, Emanuel
    name part: 1929-2016
    role:
      role term: creator
    role:
      role term: author.
  name:
    name part: Texas A & M University
    name part: Department of Statistics,
    role:
      role term: issuing body.
  name:
    name part: United States
    name part: Army Research Office,
    role:
      role term: sponsoring body.
  name:
    name part: Texas A & M Research Foundation
  type of resource: text
  genre: bibliography
  origin info:
    place:
      place term: txu
    date issued: 1992
    issuance: monographic
  language:
    language term: eng
  physical description:
    form: print
    extent: 18 leaves ; 28 cm
  note: Emanuel Parzen.
  note: "May 1992."
  note: "Texas A & M Research Foundation, Project Number 5641."
  note: "Parzen (1979) argues that statistical data analysis should be defined as fitting probability models to data. This paper presents typical concepts and recent results of our modeling theory which emphasizes quantile domain functions, information measures, and comparison density estimation. Ultimate goals include: unify parametric and nonparametric inference for continuous and discrete data; demonstrate that mathematical statistical and data analytic approaches are both needed for statistical inference; stimulate exoteric methods (applicable by applied researchers) rather than esoteric methods (known only to a small group of mathematical statisticians); combine mathematical statistical and data analytic views to develop methods of statistical analysis which are based on assumptions (known model) which are tested in ways that provide insight how to model deviations of the data from the assumed model (and thus identify a "true" model as an "iterated" model)."--Leaf 1.
  note: Includes bibliographical references (leaf 18).
  note: Sponsored by the U.S. Army Research Office
  subject:
    topic: Parameter estimation
  subject:
    topic: Estimation theory
  subject:
    topic: Information measurement
  subject:
    topic: Goodness-of-fit tests
  subject:
    topic: Entropy (Information theory)
  subject:
    topic: Distribution (Probability theory)
  subject:
    topic: Statistical hypothesis testing
  subject:
    topic: Regression analysis
  subject:
    topic: Nonparametric statistics
  subject:
    topic: Mathematical statistics
  subject:
    topic: Statistics
    topic: Nonparametric inference
    topic: Density estimation
  subject:
    topic: Statistics
    topic: Nonparametric inference
    topic: Nonparametric regression
  subject:
    topic: Quantile functions
  subject:
    topic: Quantile density estimate
  subject:
    topic: Comparison density
  subject:
    topic: Maximum spacings parameter estimation
  subject:
    topic: Minimum information parameter estimation
  classification: QA276.A12 T4 no.169
  related item:
    title info:
      title: Technical report (Texas A & M University. Department of Statistics) ; no. 169
  record info:
    record content source: TXA
    record creation date: 180411
    record change date: 20191026063048.0
    record identifier: in00004016096
    language of cataloging:
      language term: eng