Prior Information and Bias in Sequential Observation.

A. Klinger

Expert InsightsPublished 1967

The application of discrete sequential filtering to the estimation of an unknown vector imbedded in nonstationary uncorrelated noise, when observations depend linearly on the unknown vector in a time-varying manner. This situation occurs in trajectory observations close to earth. The paper shows how incorrect a priori information can introduce bias into the sequential estimates. If the prior knowledge is meager and the consequence of bias in the first few estimates is important, there are valid reasons for neglecting all prior data. Three possible approaches are suggested: using the prior data and the bias equation given; neglecting prior data; and calculating "prior" data based on the observations. 6 pp. Ref.

Document Details

  • Copyright: RAND Corporation
  • Availability: Web Only
  • Year: 1967
  • Pages: 6
  • Document Number: P-3655

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Klinger, A., Prior Information and Bias in Sequential Observation. Santa Monica, CA: RAND Corporation, 1967. https://www.rand.org/pubs/papers/P3655.html.
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