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: Conditional least squares estimation and design for continuous-time stochastic processes
  name:
    name part: Baker, Joshua Shoher.
    role:
      role term: creator
  name:
    name part: Feldman, Richard M.
    role:
      role term: degree committee member.
  name:
    name part: Longnecker, M. T.
    role:
      role term: degree committee member.
  name:
    name part: Matis, J. H.
    role:
      role term: degree committee member.
  name:
    name part: Newton, H. J.
    role:
      role term: degree committee member.
  name:
    name part: Wehrly, Thomas E.
    role:
      role term: degree supervisor.
  name:
    name part: Texas A & M University
    role:
      role term: degree granting institution.
  type of resource: text
  genre: bibliography
  genre: Academic theses
  origin info:
    place:
      place term: xx
    date issued: 1985
    issuance: monographic
  language:
    language term: eng
  physical description:
    form: print
    extent: viii, 166 leaves : illustrations ; 29 cm
  abstract: In this dissertation conditional least-squares estimation is applied to sampled continuous-time stochastic processes. The properties of estimators are studied through a theoretical development of their asymptotic behavior as well as an empirical study of their finite sample properties. A major portion of the theoretical study concentrates on the stochastic structure of the sampled process. Under two distinct observational schemes a complete analysis of the stochastic properties of the sampled process is given. This includes a development of the Markov property and stationarity for renewal sampled Markov processes. For the theoretical study of the asymptotic properties of the estimators, strong laws and central limit theorems for functions of the sampled process are presented. This asymptotic theory is derived under two general assumptions on the continuous-time process. They are: stationarity and asymptotic stationarity. Several methodological developments of conditional least-squares are included and explored. These developments involve generalizations to vector-valued processes, sequential estimation and applications to the alternate observational schemes. The theoretical development of conditional least-squares is a study of the asymptotic properties (consistency and asymptotic normality) of the estimators for the above-mentioned generalizations, including a specific study of the asymptotics for several types of observational schemes under renewal sampling. Finally a simulation study is used to explore finite sample properties of the estimator under various situations of interest.
  note: "Major subject: Statistics."
  note: Typescript (photocopy).
  note: Vita.
  note: Ph. D. Texas A & M University 1985
  note: Includes bibliographical references (leaves 157-162).
  subject:
    topic: Estimation theory
  subject:
    topic: Stochastic processes
  subject:
    topic: Major statistics
  identifier: http://proxy.library.tamu.edu/login
  identifier: https://hdl.handle.net/1969.1/DISSERTATIONS-439072
  related item:
    location:
      url: http://proxy.library.tamu.edu/login
  related item:
    location:
      url: https://hdl.handle.net/1969.1/DISSERTATIONS-439072
  record info:
    record content source: TXA
    record creation date: 870113
    record change date: 20220103135036.0
    record identifier: in00000415123
    language of cataloging:
      language term: eng