PARAMETRIC SEQUENTIAL SAMPLING BASED ON MULTISTAGE ESTIMATION OF THE NEGATIVE BINOMIAL PARAMETER K

An intensive survey of two farmer-managed corn and soybean fields in e astern Nebraska was conducted to investigate parametric sequential sam pling of weed seedling populations using a multistage procedure to est imate k of the negative binomial distribution, k is a nonspatial aggre gation parameter related to the variance at a given mean value. Mean w eed seedling density ranged from 0.18 to 3.11 plants 0.38 m(-2) (linea r meter of crop row) based on 806 sampling locations. The average valu e of k, derived from 200 multistage estimation procedures, ranged from 0.17 to 032. A sequential sampling plan was developed with the goal o f estimating the mean with a coefficient of variation (CV) of 10, 20, 30, and 40% of the sample mean. A sampling plan was also constructed t o estimate the mean within a specified distance H of the true mean (H( (x) over bar) = 0.10, 0.50 and 1.0 plants 0.38 m(-2)) with 80, 85, and 90% confidence. Estimating mean weed seedling density within a specif ied CV of the true mean CV((x) over bar) using parametric sequential s ampling techniques was superior to estimating the mean within a specif ied distance (H((x) over bar) of the true mean when considering the fr equency of sampling and probability of error, especially at intermedia te k values. At a k value of 0.32 and 0.25, the difference between the actual CV((x) over bar) obtained from sampling and the CV((x) over ba r) specified by the sampler was minimal. However, the accuracy of weed seedling density estimates was reduced with decreasing k values below 0.25, especially as the specified CV((x) over bar) increased.