Nearest Neighbor Bias -- A simple example

Autores/as

  • Kim Iles Kim Iles & Associates, Nanaimo, B.C., Canada

Palabras clave:

nearest neighbor, bias

Resumen

This is a short research note with an illustrative example describing the bias inherent in the nearest neighbor method.  MCFNS 2(1):18-19.

Biografía del autor/a

  • Kim Iles, Kim Iles & Associates, Nanaimo, B.C., Canada
    Kim Iles is an expert in sampling and forest inventory and inventor of many new statistical estimators. He got his B.S. in Forest Management and M.Sc. in Forest Biometrics, from Oregon State University, and Ph.D. Forest Biometrics, from University of British Columbia in 1979. He was the Biometrician and Head of Growth and Yield Dept., MacMillan Bloedel Ltd., Nanaimo, B.C. for 12 years until 1991 and a consultant since then. He is the author of a textbook on Forest Inventory (now in second printing), and he was the principle inventory design consultant for the British Columbia Provincial Inventory design (this inventory covered an area of 100,000,000 hectares). Kim's specialties of Variable Plot Sampling and 3P sampling are the dominant inventory systems used in the North America. He has taught inventory techniques to several thousand professional cruisers on 3 continents, and is the major contributor to the Cruising and Inventory Newsletter published by John Bell Associates. He has been a member of several committees of national standing, and has developed and introduced a number of innovations in cruising systems in North America. /p

Referencias

Iles, K. 2009. Total-Balancing an inventory: A method for unbiased inventories using highly biased non-sample data at variable scales. MCFNS [Online]. 1(1): 10-13.

Cochran, W. G. 1977. Sampling Techniques. 3d ed. New York: John Wiley and Sons. 428p. See section 6.15.

International Journal of Mathematical and Computational Forstry and Natural-Resource Sciences

Descargas

Publicado

2010-02-18

Número

Vol. 2 Núm. 1: MCFNS February 28, 2010

Sección

Sampling and Natural Resource Inventories

Licencia

Authors who publish with this journal agree to the following terms:
    1. Authors grant the journal right of first publication, with the work simultaneously licensed under a Creative Commons Attribution License that allows others to share the work with an acknowledgement of the work's authorship and initial publication in this journal.

    1. Authors are able to enter into separate, additional contractual arrangements for the non-exclusive distribution of the journal's published version of the work (e.g., post it to an institutional repository or publish it in a book), with an acknowledgement of its initial publication in this journal.

    1. Authors are permitted and encouraged to post their work online (e.g., in institutional repositories or on their website) following the publication by the journal, as it can lead to productive exchanges, as well as earlier and greater citation of published work (See The Effect of Open Access).

Cómo citar

Nearest Neighbor Bias -- A simple example. (2010). Mathematical and Computational Forestry & Natural-Resource Sciences (MCFNS), 2(1), Pages: 18-19 (2). https://www.tmp.17921125833755a190e36a5857.temporary.link/index.php/Journal/article/view/MCFNS.2-18

Artículos similares

También puede Iniciar una búsqueda de similitud avanzada para este artículo.

Artículos más leídos del mismo autor/a