sr-package

sr: Smooth Regression - The Gamma Test and Tools

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) tools:::Rd_expr_doi("10.1098/rspa.2002.1010") , AJ Jones (2004) tools:::Rd_expr_doi("10.1007/s10287-003-0006-1") . package

See Also

Useful links:

• https://smoothregression.com
• https://github.com/haythorn/sr/
• Report bugs at https://github.com/haythorn/sr/issues

Author(s)

Maintainer : Wayne Haythorn support@smoothregression.com

Authors:

• Antonia Jones (Principal creator of the Gamma test)

Other contributors:

• Sam Kemp (Wrote the original code for the Gamma test in R) [contributor]