Some Theory for the Application of the Moving Average Estimator in Forest Surveys
Authors: Devin S. Johnson1; Michael S. Williams2
Source: Forest Science, Volume 50, Number 5, October 2004 , pp. 672-681(10)
Abstract:
The Forest Inventory and Analysis (FIA) and National Resources Inventory programs are two examples of large-scale survey programs that are in the process of moving from periodic surveys, where data for an area are collected once every 10–15 years, to annual surveys, where a smaller sample of the data is collected every year. Each yearly sample can be referred to as a panel, and yearly estimates can be made with the data in each panel. With the change from periodic to annual surveys, there has been a substantial amount of discussion related to combining the data from the individual panels into a single estimator with an acceptably small mean square error. Numerous methods, each with certain advantages and disadvantages, have been proposed and tested. Testing with FIA data suggests that, in terms of mean square error, the equally weighted moving average estimator is often as good as or better than other estimators when making estimates for individual counties or small groups of counties. This favorable performance is due to the relatively small sample sizes in these situations. One area of research that has not been addressed is the performance of the moving average estimator when the sampling design deviates from its original protocol. Factors that cannot be controlled, such as weather, budgets, and politics, can alter the original sampling design. The purpose of this article is to propose and derive estimators that accommodate these factors and give some guidelines on how to handle these situations when they occur. FOR. SCI. 50(5):672–681.Keywords: Panel surveys; moving average; variance estimator; environmental management; forest; forest management; forest resources; forestry; forestry research; forestry science; natural resources; natural resource management
Document Type: Regular article
Affiliations: 1: Department of Mathematical Sciences University of Alaska Fairbanks Fairbanks AK 99775 2: Rocky Mountain Research Station USDA Forest Service 2150 A Centre Ave., Suite 361 Fort Collins CO 80526 Phone: (970) 295-5974;, Fax: (970) 295-5959, Email: mswilliams@fs.fed.us
