MSSA: R-Code, Tutorials, and References

M-SSA (Multivariate Smooth Sign Accuracy) provides a unified framework for solving general prediction problems while simultaneously accommodating specific, practically relevant research priorities and objectives. It is based on (fast) optimization criteria with unique solutions based on simple principles. It specializes on addressing the Accuracy-Smoothness dilemma in prediction. In contrast to MDFA, MSSA is a time-domain forecast approach that emphasizes not only MSE performances but also the signs: sign-accuracy and the mean duration between consecutive sign changes. 

 

MSSA-tutorial denotes a R-package of examples and use cases introducing to and illustrating the MSSA: it is hosted on a github repository. 

 

The method is explained in a series of articles: working paper versions are available through github. 

 

Click on the buttons below to either access (a description of) the MSSA tutorial project or to obtain background information.