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Ranked Set Sampling and the Line Intercept Method: A More Efficient Procedure
Author(s) -
Muttlak H. A.,
McDonald L. L.
Publication year - 1992
Publication title -
biometrical journal
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.108
H-Index - 63
eISSN - 1521-4036
pISSN - 0323-3847
DOI - 10.1002/bimj.4710340307
Subject(s) - simple random sample , statistics , mathematics , estimator , sampling (signal processing) , sampling design , cluster sampling , systematic sampling , multistage sampling , population , computer science , demography , filter (signal processing) , sociology , computer vision
Ranked set sampling is a method which may be used to increase the efficiency of the estimator of the mean of a population. Ranked set sampling with size biased probability of selection (i.e., the items are selected with probability proportion to its size) is combined with the line intercept method to increase the efficency of estimating cover, density and total amount of some variable of interest (e.g. biomass). A two‐stage sampling plan is suggested with line intercept sampling in the first stage. Simple random sampling and ranked set sampling are compared in the second stage to show that the unbiased estimators of density, cover and total amount of some variable of interest based on ranked set sampling have smaller variances than the usual unbiased estimator based on simple random sampling. Efficiency is increased by reducing the number of items which are measured on a transect or by increasing the number of independent transects utilized in a study area. An application procedure is given for estimation of coverage, density and number of stems of mountain mahogany ( Cercocarpus montanus ) in a study area east of Laramie, Wyoming.