A model-independent adaptive sequential sampling technique based on response nonlinearity estimation

2019 ◽  
Vol 61 (3) ◽  
pp. 1051-1069 ◽  
Author(s):  
Andrea Garbo ◽  
Brian J. German
1979 ◽  
Vol 13 (5) ◽  
pp. 609-610
Author(s):  
Allen Hoffman ◽  
Roger Sperling ◽  
John Polasek ◽  
Jerry Bullin

1958 ◽  
Vol 90 (6) ◽  
pp. 331-338 ◽  
Author(s):  
W. G. H. Ives ◽  
R. M. Prentice

Sequential sampling methods have been developed for population surveys of a number of forest insects (4, 6, 7, 9). These methods permit rapid classification of populations into broad infestation classes with predetermined accuracy and a minimum of sampling, and are useful for mapping and recording widespread infestations.The method of assessing egg populations of the larch sawfly, Pristiphora erichsonii (Htg.), developed by Ives (3) for intensive population studies, was not suitable for surveys because of the large sample size required. A sequential plan for the larch sawfly using hypothetical infestation classes was briefly reviewed by Ives (2). This plan is modified in the present paper in accordance with new data that have accumulated from observations on plots in the Whiteshell Forest Reserve and other stands in Manitoba and Saskatchewan.


1954 ◽  
Vol 32 (4) ◽  
pp. 302-313 ◽  
Author(s):  
R. F. Morris

The object in extensive spruce budworm egg surveys is to classify the infestation as light, moderate, or severe, at a large number of sampling points. The sequential plan, having no fixed sample size, was tested in 1953. It proved very useful, particularly in eliminating superfluous sampling at points where the infestation was definitely light or definitely severe. Curves showing operating characteristics and average sample numbers in relation to population mean permitted an appraisal of the plan in advance of the field test. Field parties were provided with simple tabulations prepared from the acceptance and rejection lines. With an expenditure of 1300 man-days, more than 1000 points were classified in northern New Brunswick.


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