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README.Rmd
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README.Rmd
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---
output: github_document
---
<!-- README.md is generated from README.Rmd. Please edit that file -->
```{r setup, include = FALSE}
knitr::opts_chunk$set(
collapse = TRUE,
comment = "#>",
fig.path = "man/figures/README-",
out.width = "100%"
)
```
# Spbsampling
An [R](https://www.r-project.org) package for *spatially balanced sampling*.
The **Spbsampling** package provides functions to draw *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).
For details regarding the implemented sampling designs, you may want to look at the references section.
The implementation has been done in C++ through the use of **Rcpp** and **RcppArmadillo**.
Authors: Francesco Pantalone, Roberto Benedetti, Federica Piersimoni.
Maintainer: Francesco Pantalone.
## Installation
You can install the released version of Spbsampling from [CRAN](https://CRAN.R-project.org)
```{r, eval = FALSE}
install.packages("Spbsampling")
```
## 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. https://doi.org/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. https://doi.org/10.1002/bimj.201600194
Benedetti R, Piersimoni F (2017). Fast Selection of Spatially Balanced Samples. *arXiv*. https://arxiv.org/abs/1710.09116
## License
GPL-3