Get 20M+ Full-Text Papers For Less Than $1.50/day. Start a 14-Day Trial for You or Your Team.

Learn More →

Adaptive Sampling DesignsBasic Ideas

Adaptive Sampling Designs: Basic Ideas [In this chapter we consider the problem of estimating such quantities as the number of objects, the total biomass, or total ground cover in a finite population from a sample. Various traditional methods of sampling such as sampling with or without replacement, inverse sampling, and unequal probability sampling are often inadequate when the population is rare but clustered. We briefly introduce the idea of adaptive sampling that includes a variety of so-called adaptive methods. For example, adaptive cluster sampling allows us to sample the rest of a cluster when one is located. We can also have adaptive allocation in stratified sampling where the initial observations in the strata determine the allocation of future observations.] http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png

Adaptive Sampling DesignsBasic Ideas

Download PDF
10 pages

Loading next page...
 
/lp/springer-journals/adaptive-sampling-designs-basic-ideas-9bzhPFkdq9
Publisher
Springer Berlin Heidelberg
Copyright
© The Author(s) 2013
ISBN
978-3-642-33656-0
Pages
1 –10
DOI
10.1007/978-3-642-33657-7_1
Publisher site
See Chapter on Publisher Site

Abstract

[In this chapter we consider the problem of estimating such quantities as the number of objects, the total biomass, or total ground cover in a finite population from a sample. Various traditional methods of sampling such as sampling with or without replacement, inverse sampling, and unequal probability sampling are often inadequate when the population is rare but clustered. We briefly introduce the idea of adaptive sampling that includes a variety of so-called adaptive methods. For example, adaptive cluster sampling allows us to sample the rest of a cluster when one is located. We can also have adaptive allocation in stratified sampling where the initial observations in the strata determine the allocation of future observations.]

Published: Oct 23, 2012

Keywords: Adaptive sampling; Adaptive cluster sampling; Adaptive cluster double sampling; Unequal probability sampling; Adaptive allocation; Stratified sampling

There are no references for this article.