inventory of fine woody debris (FWD); however, the sampling protocols involve tallying only the number of FWD pieces by size … class that intersect a sampling transect with no measure of actual size. The line intersect estimator used with those …

Carlo, Latin hypercube sampling with constrained Monte Carlo, and generalized likelihood uncertainty estimation), and …

-effective methods of sampling; how to track individuals and the importance of ethics and data management and analysis. Panel studies …

complex sampling. It begins by looking at sampling in general withspecific focus on complex sampling and weighting. For the … estimation of bias and standard error under simple randomsampling and complex sampling. Three con dence intervals are discussed …

characteristics basedon sampled flow data from single-stage Bernoulli sampling, and two-stage sampling will be addressed. An …, estimation of traffic characteristic acrossthe network and sampling allocation problem is studied. The proposed approaches are …

Systematic sampling is easy, efficient, and widely used, though it is not generally recognized that a systematic sample … of them determine which estimators are unbiased, when using the sampling design as the basis for inference. We describe … selection. When the population size is known at the outset, systematic sampling with unrestricted selection is most likely the …

Binomial sampling based on the proportion of samples infested was investigated for estimating mean densities of citrus … parameters adequately described a validation data set from a sampling plan consisting of 192 samples. Projections indicated the … fitted parameters would apply to sampling plans with as few as 48 samples, but reducing sample size resulted in an increase …

. Projections indicated that a sampling plan consisting of 10 trees and eight flush shoots per tree would provide density estimates … presence-absence sampling plan with a fixed precision level was developed and can be used to provide a quick estimation of D …

both simple random and cluster sampling. The BRR estimate of variance is the sum of variances and covariances of unit …-level kNN estimates in the area of interest. In Monte Carlo simulations of simple random and cluster sampling from seven … and Monte Carlo sampling variances was good both for population and for small-area totals. The modified BRR estimator is …