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QUADRAT SAMPLING AND THE ESTIMATION OF NEYMAN TYPE A AND THOMAS DISTRIBUTIONAL PARAMETERS 1
Author(s) -
Gleeson A. C.,
Douglas J. B.
Publication year - 1975
Publication title -
australian journal of statistics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.434
H-Index - 41
eISSN - 1467-842X
pISSN - 0004-9581
DOI - 10.1111/j.1467-842x.1975.tb00946.x
Subject(s) - quadrat , statistics , cluster sampling , sampling (signal processing) , mathematics , cluster (spacecraft) , estimation , sample size determination , cluster size , econometrics , geography , computer science , ecology , demography , engineering , population , biology , telecommunications , transect , electronic structure , physics , systems engineering , quantum mechanics , sociology , detector , programming language
Summary Computer simulation is employed to investigate the effects of quadrat size, sampling and estimation method, and cluster spread, density and size when estimating Neyman Type A and Thomas distributional parameters from quadrat samples. Results obtained indicate that quadrat size and cluster spread affect the estimates. Use of first order standard errors in selecting suitable quadrat sizes is discussed. Where clusters have non‐zero spread, the usual situation in practice, cluster density is generally overestimated and cluster size underestimated, which suggests the need for development of modified estimation procedures.