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Improved strategies for coverage estimation by using replicated line-intercept sampling
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AI
DOI：10.1007/s10651-007-0048-6.png)
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Abstract
En 中文
Coverage, i.e., the area covered by the target attribute in the study region, is a key parameter in many surveys. Coverage estimation is usually performed by adopting a replicated protocol based on line-intercept sampling coupled with a suitable linear homogeneous estimator. Since coverage is a parameter which may be interestingly represented as the integral of a suitable function, improved Monte Carlo strategies for implementing the replicated protocol are introduced in order to achieve estimators with small variance rates. In addition, new specific theoretical results on Monte Carlo integration methods are given to deal with the integrand functions arising in the special coverage estimation setting.
Keywords:
coverage estimation
replicated designs
linear homogeneous estimator
Monte Carlo integration
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