Weakly Associated Vectors (WAVE) Sampling

Spatial data are generally auto-correlated, meaning that if two units selected are close to each other, then it is likely that they share the same properties. For this reason, when sampling in the population it is often needed that the sample is well spread over space. A new method to draw a sample from a population with spatial coordinates is proposed. This method is called wave (Weakly Associated Vectors) sampling. It uses the less correlated vector to a spatial weights matrix to update the inclusion probabilities vector into a sample. For more details see Raphaël Jauslin and Yves Tillé (2019) .


Reference manual

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0.1.1 by Raphaël Jauslin, a year ago


Report a bug at https://github.com/RJauslin/WaveSampling/issues

Browse source code at https://github.com/cran/WaveSampling

Authors: Raphaël Jauslin [aut, cre] , Yves Tillé [aut]

Documentation:   PDF Manual  

GPL (>= 2) license

Imports Rcpp

Depends on Matrix

Suggests knitr, rmarkdown, ggplot2, ggvoronoi, sampling, BalancedSampling, sp, sf, stats

Linking to RcppArmadillo, Rcpp

Imported by SpotSampling.

See at CRAN