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Titolo: Saddlepoint approximations for statistical inference of PPP sample estimates
Autore: Magnussen, S;
 Indirizzi:
 Nat Resources Canada, Canadian Forestry Serv, Pacific Forestry Ctr, Victoria, BC V8Z 1M5, Canada Nat Resources Canada Victoria BC Canada V8Z 1M5 toria, BC V8Z 1M5, Canada
 Titolo Testata:
 SCANDINAVIAN JOURNAL OF FOREST RESEARCH
fascicolo: 2,
volume: 16,
anno: 2001,
pagine: 180  192
 SICI:
 02827581(2001)16:2<180:SAFSIO>2.0.ZU;22
 Fonte:
 ISI
 Lingua:
 ENG
 Soggetto:
 ASYMPTOTICS; VARIABLES; RATIO;
 Tipo documento:
 Article
 Natura:
 Periodico
 Settore Disciplinare:
 Agriculture,Biology & Environmental Sciences
 Citazioni:
 50
 Recensione:
 Indirizzi per estratti:
 Indirizzo: Magnussen, S Nat Resources Canada, Canadian Forestry Serv, Pacific Forestry Ctr, 506 W Burnside Rd, Victoria, BC V8Z 1M5, Canada Nat Resources Canada506 W Burnside Rd Victoria BC Canada V8Z 1M5



 Citazione:
 S. Magnussen, "Saddlepoint approximations for statistical inference of PPP sample estimates", SC J FOR R, 16(2), 2001, pp. 180192
Abstract
Sampling with probability proportional to predictions (PPP) can be very efficient: yet variance estimators for sample estimates rely on a firstorderTaylor series expansion which can be seriously biased for small sample sizes (n less than or equal to 10). Forestry application of sampling with PPP often involves volume estimation of a few trees selected with PPP. To improve estimates of sampling variance in these applications this study illustrates how saddlepoint approximations can produce estimates of standard deviations that are closer to benchmark values than current popular variance estimators. Confidence intervals based on the traditional variance estimator and a Student's tdistribution could be improved upon by using the variance efficient sample size minus one as the degree of freedom instead of simply sample size minus one. A bootstrap procedure adapted to PPP sampling produced variable and generally inferior results. For small samples (n < 10) estimating the PPP sampling variance via saddlepoints approximations appears worthwhile.
ASDD Area Sistemi Dipartimentali e Documentali, Università di Bologna, Catalogo delle riviste ed altri periodici
Documento generato il 04/12/20 alle ore 13:03:29