Recursive Restriction Estimation

Recursive Restriction Estimation : An Alternative to Post- Stratification in Surveys of Land and Forest Cover

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Numerous government surveys of natural resources use Post-Stratifi cation to improve statistical effi ciency, where strata are defi ned by full-coverage, remotely sensed data and geopolitical boundaries. Recursive Restriction Estimation, which may be considered a special case of the static Kalman filter, is an attractive alternative. It decomposes a complex estimation problem into simple components that are sequentially processed. Compared to Post-Stratification, it more efficiently uses remotely sensed data, both continuous and categorical. It is less constrained by sample size, which is especially important with panel surveys. It produces a conditionally unbiased covariance matrix for the vector estimate of population totals without approximations or ad hoc assumptions. This facilitates variance estimates for non-linear pseudo-estimators. A robust sequential algorithm controls numerical errors inherent with Recursive Restriction Estimator, which can otherwise cause unreliable results. Analysis of residuals can detect other anomalies.
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Product details

  • Paperback | 36 pages
  • 215.9 x 279.4 x 2.03mm | 140.61g
  • Createspace
  • United States
  • English
  • black & white illustrations
  • 1507666179
  • 9781507666173