A Kalman Filter for a Poisson Series with Covariates and Laplace Approximation Integration

Abstract

A hierarchical model for a Poisson time series is introduced. The model allows the mean or rate of the Poisson variables to vary slowly in time; it is modeled as the exponential of an AR/1 process. In addition the rate is influenced by a covariate. The Laplace method is used to recursively update some model parameter estimates. Frankly heuristic methods are explored to estimate other of the underlying parameters. The methodology is checked against simulated data with encouraging results.

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Document Details

Document Type
Technical Report
Publication Date
Sep 01, 1991
Accession Number
ADA242960

Entities

People

  • Donald P. Gaver Jr.
  • Patricia A. Jacobs

Organizations

  • Naval Postgraduate School

Tags

Communities of Interest

  • Biomedical
  • Energy and Power Technologies
  • Ground and Sea Platforms

DTIC Thesaurus Topics

  • Business Administration
  • Computational Science
  • Data Science
  • Estimators
  • Heuristic Methods
  • Industrial Engineering
  • Kalman Filters
  • New York
  • Normal Distribution
  • Operations Research
  • Public Health
  • Random Variables
  • Simulations
  • Square Roots
  • Standards
  • Statistical Analysis
  • Statistics

Fields of Study

  • Mathematics

Readers

  • Adaptive Control and Estimation with Uncertainty in Dynamic Systems.
  • Calculus or Mathematical Analysis
  • Regression Analysis.