Skip to main content

Comparison of Estimators for Rolling Samples Using Forest Inventory and Analysis Data

Buy Article:

$29.50 plus tax (Refund Policy)


The performance of three classes of weighted average estimators is studied for an annual inventory design similar to the Forest Inventory and Analysis program of the United States. The first class is based on an ARIMA(0,1,1) time series model. The equal weight, simple moving average is a member of this class. The second class is based on an ARIMA(0,2,2) time series model. The final class is based on a locally weighted least-squares regression prediction. The estimator properties were tested using a simulation population created from Forest Inventory and Analysis (FIA) data from northeastern Minnesota. Estimates of total volume per acre, on-growth volume per acre, mortality volume per acre, proportion of sawtimber acreage, proportion of poletimber acreage, and proportion of sapling acreage were calculated using several weighted average estimators in each year. These were compared to the simulation population, for which the true values are known, and an unbiased yearly estimator. When computing estimates, the ARIMA(0,1,1) based estimators produced the lowest root mean squared error of each of the three classes. However, in a few years the bias for some variables was high. The maximum percent increase between the estimator with the lowest root mean squared error and the simple moving average was 7.31%. Of all the estimators, the simple moving average performed well in terms of mean square error in virtually every situation. It tended to be best among the estimators tested if spatial variation was large and change was relatively small. It was not consistently best in terms of mean square error in the presence of moderate change and large spatial variation. For. Sci. 49(1):50–63.

Keywords: FIA; Rolling samples; annual inventory; environmental management; forest; forest management; forest resources; forestry; forestry research; forestry science; natural resource management; natural resources; panel survey; weighted average

Document Type: Miscellaneous

Affiliations: 1: Department of Statistics, Colorado State University, Fort Collins, Colorado, 80523, Phone: (970) 491-6014; Fax: (970) 491-7895 2: Rocky Mountain Research Station, USDA Forest Service, 2150 Centre Ave., Bldg A, Suite 361, Fort Collins, Colorado, 80526,

Publication date: February 1, 2003

More about this publication?
  • Forest Science is a peer-reviewed journal publishing fundamental and applied research that explores all aspects of natural and social sciences as they apply to the function and management of the forested ecosystems of the world. Topics include silviculture, forest management, biometrics, economics, entomology & pathology, fire & fuels management, forest ecology, genetics & tree improvement, geospatial technologies, harvesting & utilization, landscape ecology, operations research, forest policy, physiology, recreation, social sciences, soils & hydrology, and wildlife management.
    Forest Science is published bimonthly in February, April, June, August, October, and December.

    Also published by SAF:
    Journal of Forestry
    Other SAF Publications
  • Submit a Paper
  • Membership Information
  • Author Guidelines
  • Ingenta Connect is not responsible for the content or availability of external websites

Access Key

Free Content
Free content
New Content
New content
Open Access Content
Open access content
Subscribed Content
Subscribed content
Free Trial Content
Free trial content
Cookie Policy
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