Continuous Forest Inventory, Partial Replacement of Samples and Multiple Regression
The theory of sampling populations on two occasions with partial replacement of units (SPR) is extended to use multiple regression estimates. It is shown that in general multiple are better than simple linear estimates and in many cases they are much more efficient. Formulae are derived for (1) best estimates of current averages and changes in these averages from first to second occasion and (2) standard errors of these estimates. An example is also given of its application to a sampling design in Continuous Forest Inventory (CFI).
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Document Type: Journal Article
Affiliations: Forest statistician, Canadian International Paper Co., Sun Life Bldg. Montreal, Canada
Publication date: 1965-12-01
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- 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.
2016 Impact Factor: 1.782 (Rank 17/64 in forestry)
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June 1, 2016 to Feb. 28, 2017
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