Title: Complex sample survey estimation in static state-space
Author: Czaplewski, Raymond L.
Source: Gen. Tech. Rep. RMRS-GTR-239. Fort Collins, CO: U.S. Department of Agriculture, Forest Service, Rocky Mountain Research Station. 124 p.
Station ID: GTR-RMRS-239
Description: Increased use of remotely sensed data is a key strategy adopted by the Forest Inventory and Analysis Program. However, multiple sensor technologies require complex sampling units and sampling designs. The Recursive Restriction Estimator (RRE) accommodates this complexity. It is a design-consistent Empirical Best Linear Unbiased Prediction for the state-vector, which contains all sufficient statistics for the sampled population. RRE reduces a complex estimator into a sequence of simpler estimators. Also included are model-based pseudo-estimators and multivariate Taylor series approximations for covariance matrices. Together, these provide a unifi ed approach to detailed estimation in large, complex sample surveys.
Keywords: FIA, sampling, recursive, Pythagorean regression, EBLUP, remote sensing
View and Print this Publication (1.63 MB)
- We recommend that you also print this page and attach it to the printout of the article, to retain the full citation information.
- This article was written and prepared by U.S. Government employees on official time, and is therefore in the public domain.
- You may send email to email@example.com to request a hard copy of this publication. (Please specify exactly
which publication you are requesting and your mailing address.)
Get the latest version of the Adobe Acrobat reader or Acrobat Reader for Windows with Search and Accessibility
Czaplewski, Raymond L. 2010. Complex sample survey estimation in static state-space. Gen. Tech. Rep. RMRS-GTR-239. Fort Collins, CO: U.S. Department of Agriculture, Forest Service, Rocky Mountain Research Station. 124 p..