Skip to main content

Variance Reduction for Sector Sampling

The full text article is temporarily unavailable.

We apologise for the inconvenience. Please try again later.

Variance reduction techniques used in Monte Carlo integration including control variates and importance sampling can use estimated or actual shapes of vegetated land areas to reduce the variance of estimators from sector sampling. The estimated shapes of forested areas could come from maps, aerial photos, or similar sources. Antithetic variates for variance reduction in Monte Carlo integration can be applied to sector sampling without using any estimated shape or map. Sector sampling selects as samples all trees or other vegetation of interest located in randomly chosen sectors that have a vertex at a common point located in the interior of a forested area. Each sector is associated with an angle of fixed magnitude emanating from the interior point. Sector orientation is based on a randomly selected azimuth originating at the interior point that is the vertex for each sector. This technique is well adapted to application on relatively small areas that have irregularly shaped boundaries. Sector sampling can be demonstrated to be unbiased. Unbiasedness holds with angle reduction for adjustment of sample size and with the variance reduction techniques that are proposed. The method is not restricted to application with trees because sector sampling methods could be applied just as well to other vegetation types or any other objects located in the land area of interest.
No References
No Citations
No Supplementary Data
No Article Media
No Metrics

Keywords: Monte Carlo integration; control variates; importance sampling; polar coordinates; vegetation sampling

Document Type: Research Article

Affiliations: Thomas B. Lynch, Professor, Department of Forestry, Room 008C Ag Hall, Oklahoma State University, Stillwater, OK 74078-6013—Phone: (405) 744-5447; [email protected], Fax: (405) 744-5437

Publication date: 01 June 2006

  • Access Key
  • Free content
  • Partial Free content
  • New content
  • Open access content
  • Partial Open access content
  • Subscribed content
  • Partial Subscribed content
  • Free trial content
Cookie Policy
X
Cookie Policy
Ingenta Connect website makes use of cookies so as to keep track of data that you have filled in. I am Happy with this Find out more