Please use this identifier to cite or link to this item: https://hdl.handle.net/10419/236832 
Authors: 
Year of Publication: 
2021
Citation: 
[Journal:] Statistics in Transition New Series [ISSN:] 2450-0291 [Volume:] 22 [Issue:] 2 [Publisher:] Exeley [Place:] New York [Year:] 2021 [Pages:] 143-154
Publisher: 
Exeley, New York
Abstract: 
Recent years have seen an intensive development in the field of spatial sampling methods, which generally focus on a balanced distribution of the sample in space. Adaptive sampling methods constitute another dynamic direction in the sampling theory. The issue raised in this article involves the combination of these directions. Five of the commonly known spatial sampling methods have been analysed. The experiment was designed to include statistical model in the sampling procedure. As in the case of adaptive methods, it serves to modify drawing probabilities during sampling. The necessary theory of this sampling modification has been developed and presented. An experiment using artificial data was conducted in order to analyse the efficiency of the model modification in comparison with the primary methods.
Subjects: 
spatial sampling
drawn-by-drawn sampling
kriging
employees distribution
Persistent Identifier of the first edition: 
Creative Commons License: 
cc-by-nc-nd Logo
Document Type: 
Article

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