The Rank Input Method and Probability Variation Guides.

Abstract

The rank input method allows a forecaster's subjective estimate to be quantified into a probability forecast. The forecaster's estimate can be a rank input, a probability of a single category, or a categorical forecast. With the rank input the forecaster ranks the synoptic situation--very bad to very good-- in relation to the element to be forecast, e.g., surface visibility. The transnormalized regression probability model is then used to calculate the probability of the specific event. Probability of a single category can be converted to probabilities for one or more different categories. A categorical forecast can be converted to probability forecasts. A validation during REFORGER 78 concluded that the method shows promise and that forecasters were able to produce a large number of probability forecasts with a few simple rankings of the synoptic situation. Probability variation guides are tables giving forecast probability values for various inputs. Plotted on a simple graph, all values for a given skill and climatology fall along a single curve in probability space. These curves make certain decision analysis theorems much simpler in form.

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Document Details

Document Type
Technical Report
Publication Date
Jul 01, 1980
Accession Number
ADA093196

Entities

People

  • Albert R. Boehm

Organizations

  • Air Force Technical Applications Center

Tags

Communities of Interest

  • Human Systems
  • Weapons Technologies

DTIC Thesaurus Topics

  • Air Force
  • Atmospheric Sciences
  • Climatology
  • Closed Loop Systems
  • Computer Programs
  • Computers
  • Control Systems
  • Databases
  • Discriminant Analysis
  • Equations
  • Frequency
  • Probability
  • Security
  • Standards
  • Training
  • Verification
  • Visibility

Fields of Study

  • Environmental science

Readers

  • Atmospheric Science/Meteorology
  • Regression Analysis.

Technology Areas

  • Space