Skip to main content

Prediction Bias and Response Surface Curvature

Buy Article:

$29.50 plus tax (Refund Policy)

Abstract:

Many functions used for forestry applications have response surfaces that have curvature. Depending on the degree of curvature, predictions made with these functions can be biased when the inputs to these functions have unbiased random errors. An approximation is presented for calculating the bias in prediction when there are unbiased but random errors in the inputs of the function. Examples of some fairly simple functions used in forestry are shown to provide highly biased predictions in typical applications. For. Sci. 37(3):755-765.

Keywords: Errors in predictors

Document Type: Journal Article

Affiliations: Associate Professor of Forest Biometrics, 110 Mumford Hall, Department of Forestry, 1301 W. Gregory Drive, University of Illinois, Urbana, IL 61801

Publication date: August 1, 1991

More about this publication?
  • Membership Information
  • ingentaconnect is not responsible for the content or availability of external websites
saf/fs/1991/00000037/00000003/art00004
dcterms_title,dcterms_description,pub_keyword
6
5
20
40
5

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
X
Cookie Policy
ingentaconnect 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