caa a22 4500 475762517 CHVBK 20180406123555.0 cr unu---uuuuu 170329e20000901xx s 000 0 eng 10.1023/A:1009675318046 doi (NATIONALLICENCE)springer-10.1023/A:1009675318046 Comparison of distribution function estimators for forestry applications following variable probability sampling [Elektronische Daten] [Stephen Stehman, Sophonie Nshinyabakobeje] Practical considerations often motivate employing variable probability sampling designs when estimating characteristics of forest populations. Three distribution function estimators, the Horvitz-Thompson estimator, a difference estimator, and a ratio estimator, are compared following variable probability sampling in which the inclusion probabilities are proportional to an auxiliary variable, X. Relative performance of the estimators is affected by several factors, including the distribution of the inclusion probabilities, the correlation (Ρ) between X and the response Y, and the position along the distribution function being estimated. Both the ratio and difference estimators are superior to the Horvitz-Thompson estimator. The difference estimator gains better precision than the ratio estimator toward the upper portion of the distribution function, but the ratio estimator is superior toward the lower end of the distribution function. The point along the distribution function at which the difference estimator becomes more precise than the ratio estimator depends on the sampling design, as well as the coefficient of variation of X and ρ. A simple confidence interval procedure provides close to nominal coverage for intervals constructed from both the difference and ratio estimators, with the exception that coverage may be poor for the lower tail of the distribution function when using the ratio estimator. Kluwer Academic Publishers, 2000 Chambers-Dunstan estimator nationallicence Poisson sampling nationallicence Rao-Kovar-Mantel estimator nationallicence systematic sampling nationallicence variable radius plot sampling nationallicence Stehman Stephen SUNY College of Environmental Science and Forestry, 320 Bray Hall, 13210, Syracuse, NY, USA aut Nshinyabakobeje Sophonie Biometrics Unit, Cornell University, 434 Warren Hall, 14583, Ithaca, NY, USA aut Environmental and Ecological Statistics Kluwer Academic Publishers 7/3(2000-09-01), 301-321 1352-8505 7:3<301 2000 7 10651 https://doi.org/10.1023/A:1009675318046 text/html Onlinezugriff via DOI 1 research-article jats NATIONALLICENCE 856 40 https://doi.org/10.1023/A:1009675318046 text/html Onlinezugriff via DOI NATIONALLICENCE 700 1- Stehman Stephen SUNY College of Environmental Science and Forestry, 320 Bray Hall, 13210, Syracuse, NY, USA aut NATIONALLICENCE 700 1- Nshinyabakobeje Sophonie Biometrics Unit, Cornell University, 434 Warren Hall, 14583, Ithaca, NY, USA aut NATIONALLICENCE 773 0- Environmental and Ecological Statistics Kluwer Academic Publishers 7/3(2000-09-01), 301-321 1352-8505 7:3<301 2000 7 10651 Metadata rights reserved Springer special CC-BY-NC licence nationallicence BK010053 XK010053 XK010000 NATIONALLICENCE NATIONALLICENCE NL-springer