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Evaluation of mapped-plot variance estimators across a range of partial nonresponse in a post-stratified national forest inventory / James A. Westfall in Canadian Journal of Forest Research, Vol 52 n° 2 (February 2022)  

Public [article]  inCanadian Journal of Forest Research > Vol 52 n° 2 (February 2022) . - pp 280 - 285 Titre : Evaluation of mapped-plot variance estimators across a range of partial nonresponse in a post-stratified national forest inventory Type de document : Article/Communication Auteurs : James A. Westfall, Auteur ; Andrew J. Lister, Auteur ; Charles T. Scott, Auteur Année de publication : 2022 Article en page(s) : pp 280 - 285 Note générale : bibliographie NB Note technique et non pas article de recherche Langues : Français (fre) Anglais (eng) Descripteur : [Termes IGN] erreur systématique [Termes IGN] estimation statistique [Termes IGN] inventaire forestier (techniques et méthodes) [Termes IGN] placette d'échantillonnage [Termes IGN] variance [Vedettes matières IGN] Inventaire forestier Résumé : (auteur) When conducting a forest inventory, sometimes portions of plots cannot be measured due to inaccessibility. Two primary methods have been presented to account for partial nonresponse in the estimation phase: (i) use a ratio-to-size estimator or (ii) apply an adjustment factor to all plot observations in proportion to the missing area. Both approaches provide identical estimates of the population mean, but the estimates of variance differ when partial nonresponse is present. The performance of variance estimators was examined for a range of population forest area and partial nonresponse proportions in the sample. The ratio-to-size variance estimator performed unbiasedly with respect to simulation results, but the adjustment factor variance estimates were biased, with magnitude and direction dependent upon the forest area proportion and amount of partial nonresponse. The bias is relatively small when the partial nonresponse is small, which is often the case; however, the ratio-to-size method is preferred to ensure accurate variance estimation for a wide range of circumstances. Numéro de notice : A2022-312 Affiliation des auteurs : non IGN Autre URL associée : Draft Thématique : FORET/MATHEMATIQUE Nature : Article DOI : 10.1139/cjfr-2021-0159 Date de publication en ligne : 10/08/2021 En ligne : https://doi.org/10.1139/cjfr-2021-0159 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=100409 [article]