Spbsampling: Spatially balanced sampling designs
In Spbsampling: Spatially Balanced Sampling
Spbsampling R Documentation
Spatially balanced sampling designs
Description
Selection of spatially balanced samples. In particular, the implemented
sampling designs allow to select probability samples well spread over the
population of interest, in any dimension and using any distance function
(e.g. Euclidean distance, Manhattan distance). The implementation has been
done in C++ through the use of Rcpp and RcppArmadillo.
Author(s)
Francesco Pantalone, Roberto Benedetti, Federica Piersimoni
Maintainer: Francesco Pantalone pantalone.fra@gmail.com
References
Pantalone F, Benedetti R, Piersimoni F (2022). An R Package for
Spatially Balanced Sampling. Journal of Statistical Software, Code Snippets,
103(2), 1-22.
<doi:10.18637/jss.v103.c02>
Benedetti R, Piersimoni F (2017). A spatially balanced design with
probability function proportional to the within sample distance.
Biometrical Journal, 59(5), 1067-1084.
doi: 10.1002/bimj.201600194
Benedetti R, Piersimoni F (2017). Fast Selection of Spatially Balanced Samples. arXiv.
https://arxiv.org/abs/1710.09116
Spbsampling documentation built on Aug. 24, 2022, 5:06 p.m.
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| Spbsampling | R Documentation |
Spatially balanced sampling designs
Description
Selection of spatially balanced samples. In particular, the implemented
sampling designs allow to select probability samples well spread over the
population of interest, in any dimension and using any distance function
(e.g. Euclidean distance, Manhattan distance). The implementation has been
done in C++ through the use of Rcpp and RcppArmadillo.
Author(s)
Francesco Pantalone, Roberto Benedetti, Federica Piersimoni
Maintainer: Francesco Pantalone pantalone.fra@gmail.com
References
Pantalone F, Benedetti R, Piersimoni F (2022). An R Package for Spatially Balanced Sampling. Journal of Statistical Software, Code Snippets, 103(2), 1-22. <doi:10.18637/jss.v103.c02>
Benedetti R, Piersimoni F (2017). A spatially balanced design with probability function proportional to the within sample distance. Biometrical Journal, 59(5), 1067-1084. doi: 10.1002/bimj.201600194
Benedetti R, Piersimoni F (2017). Fast Selection of Spatially Balanced Samples. arXiv. https://arxiv.org/abs/1710.09116
R Package Documentation
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Note that we can't provide technical support on individual packages. You should contact the package authors for that.
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