Finds causal connections in precision data, finds lags and embeddings in time series, guides training of neural networks and other smooth models, evaluates their performance, gives a mathematically grounded answer to the over-training problem. Smooth regression is based on the Gamma test, which measures smoothness in a multivariate relationship. Causal relations are smooth, noise is not. 'sr' includes the Gamma test and search techniques that use it. References: Evans & Jones (2002) <doi:10.1098/rspa.2002.1010>, AJ Jones (2004) <doi:10.1007/s10287-003-0006-1>.
Version: 0.1.0 Depends: R (≥ 3.5.0) Imports: ggplot2, dplyr, progress, RANN, stats, vdiffr Suggests: knitr, magrittr, nnet, rmarkdown, testthat (≥ 3.0.0) Published: 2023-03-10 DOI: 10.32614/CRAN.package.sr Author: Wayne Haythorn [aut, cre], Antonia Jones [aut] (Principal creator of the Gamma test), Sam Kemp [ctb] (Wrote the original code for the Gamma test in R) Maintainer: Wayne Haythorn <support at smoothregression.com> BugReports: https://github.com/haythorn/sr/issues License: GPL (≥ 3) URL: https://smoothregression.com, https://github.com/haythorn/sr/ NeedsCompilation: no Language: en-US Materials: README NEWS CRAN checks: sr results Documentation: Downloads: Linking:Please use the canonical form https://CRAN.R-project.org/package=sr to link to this page.
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