TAILIEUCHUNG - Báo cáo lâm nghiệp: "About the benefits of poststratification in forest inventories"

Tuyển tập những bài báo cáo nghiên cứu khoa học hay nhất được đăng trên tạp chí JOURNAL OF FOREST SCIENCE đề tài: About the benefits of poststratification in forest inventories. | JOURNAL OF FOREST SCIENCE 53 2007 4 139-148 About the benefits of poststratification in forest inventories J. Saborowski1 J. Cancino2 1Faculty of Forest Sciences and Forest Ecology Georg-August University Gottingen Germany Facultad de Ciencias Forestales Universidad de Concepción Concepción Chile ABSTRACT A large virtual population is created based on the GIS data base of a forest district and inventory data. It serves as a population where large scale inventories with systematic and simple random poststratified estimators can be simulated and the gains in precision studied. Despite their selfweighting property systematic samples combined with poststratification can still be clearly more efficient than unstratified systematic samples the gain in precision being close to that resulting from poststratified over simple random samples. The poststratified variance estimator for the conditional variance given the within strata sample sizes served as a satisfying estimator in the case of systematic sampling. The differences between conditional and unconditional variance were negligible for all sample sizes analyzed. Keywords poststratification systematic sampling simple random sampling conditional variance Poststratification is well known as a means of increasing the precision of estimates in unstratified sampling by incorporating additional information about strata weights in the final estimator. In general stratification leads to more precise estimations than simple random sampling when relatively homogenous strata can be configured with large variability between strata. Poststratification involves assignment of units after selection of the sample. Compared to a priori stratification the variance of the poststratification estimator is increased by the randomness of the sample size in each stratum. If poststratification is combined with systematic sampling the gain in precision can be suspected to be small when the spatial distribution of strata leads to a nearly .

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