Skip to Main Content
Missing data in forest ecology and management: advances in quantitative methods [Preface]Author(s): Tara Barrett; Matti. Maltomo
Source: Forest Ecology and Management. 572: 1-2.
Publication Series: Scientific Journal (JRNL)
Station: Pacific Northwest Research Station
PDF: View PDF (136.02 KB)
DescriptionIn recent years, substantial progress has been made for handling missing data issues for applications in forest ecology and management, particularly in the area of imputation techniques. A session on this topic was held at the XXlll IUFRO World Congress in Seoul, South Korea, on August 23-28, 2010, resulting in this special issue of six papers that address recent advances and applications in imputation methods and related modeling techniques. In this issue, the authors of the six papers explore recent advances in this emerging field.
- You may send email to email@example.com to request a hard copy of this publication.
- (Please specify exactly which publication you are requesting and your mailing address.)
- We recommend that you also print this page and attach it to the printout of the article, to retain the full citation information.
- This article was written and prepared by U.S. Government employees on official time, and is therefore in the public domain.
CitationBarrett, Tara; Maltomo, Matti. 2012. Missing data in forest ecology and management: advances in quantitative methods. Forest Ecology and Management. 572: 1-2.
Keywordsmost similar neighbors, spatial forest planning, small area estimation
- yaImpute: An R package for kNN imputation
- Estimating forest attribute parameters for small areas using nearest neighbors techniques
- Pseudo-CFI for industrial forest inventories
XML: View XML