Fast tools for unequal probability sampling in multi-dimensional spaces, implemented in Rust for high performance.
    The package offers a wide range of methods, including Sampford (Sampford, 1967, <doi:10.1093/biomet/54.3-4.499>) and correlated Poisson sampling (Bondesson and Thorburn, 2008, <doi:10.1111/j.1467-9469.2008.00596.x>), pivotal sampling (Deville and Tillé, 1998, <doi:10.1093/biomet/91.4.893>), and balanced sampling such as the cube method (Deville and Tillé, 2004, <doi:10.1093/biomet/91.4.893>) to ensure auxiliary totals are respected.
    Spatially balanced approaches, including the local pivotal method (Grafström et al., 2012, <doi:10.1111/j.1541-0420.2011.01699.x>), spatially correlated Poisson sampling (Grafström, 2012, <doi:10.1016/j.jspi.2011.07.003>), and locally correlated Poisson sampling (Prentius, 2024, <doi:10.1002/env.2832>), provide efficient designs when the target variable is linked to auxiliary information.

Provides tools for response surface analysis, using a comparative framework that identifies best-fitting solutions across 37 families of polynomials. Many of these tools are based upon and extend the 'RSA' package, by testing a larger scope of polynomials (+27 families), more diverse response surface probing techniques (+acceleration points), more plots (+line of congruence, +line of incongruence, both with extrema), and other useful functions for exporting results.

The 'SaTScan'(TM) <https://www.satscan.org> software uses spatial and 
	space-time scan statistics to detect and evaluate spatial and space-time clusters. 
	With the 'rsatscan' package, you can run the external 'SaTScan' software from 
	within R using R data formats. To successfully select appropriate parameter 
	settings within 'rsatscan', you must first learn 'SaTScan'.

Package to Handle R Requests from R Service Bus Applications with JSON Payloads in a generic way.
    The incoming request is encoded as a string (character vector of length one) containing 
    the JSON file passed through by the client.