Modeling Episodic Time Series.

Abstract

A particular form of filtered Poisson process is suggested for modeling time series data tht contain episodes, i.e. large, exponentially decaying excursions away from baseline values of the series. The properties of this process are derived and the principle of conditional least squares estimation is used to obtain consistent, asymptotically normal estimators of the average excursion heights and the decay rate parameter. The method is illustrated using hormone levels data. (Author)

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Document Details

Document Type
Technical Report
Publication Date
Oct 01, 1982
Accession Number
ADA129729

Entities

People

  • H. Joseph Newton

Organizations

  • Texas A&M University

Tags

Communities of Interest

  • Materials and Manufacturing Processes

DTIC Thesaurus Topics

  • Covariance
  • Data Science
  • Data Sets
  • Delta Functions
  • Estimators
  • Information Science
  • Intensity
  • Intervals
  • Military Research
  • Random Variables
  • Security
  • Stationary
  • Statistics
  • Stochastic Processes
  • Time Intervals
  • Time Series Analysis
  • Universities

Fields of Study

  • Mathematics

Readers

  • Coastal Oceanography
  • Statistical inference.