3 packages on CRAN
A methodology that makes use of the factor structure of large dimensional panels to understand the nature of nonstationarity inherent in data. This is referred to as PANIC, Panel Analysis of Nonstationarity in Idiosyncratic and Common Components. PANIC (2004)<doi:10.1111/j.1468-0262.2004.00528.x> includes valid pooling methods that allow panel tests to be constructed. PANIC (2004) can detect whether the nonstationarity in a series is pervasive, or variable specific, or both. PANIC (2010) <doi:10.1017/s0266466609990478> includes two new tests on the idiosyncratic component that estimates the pooled autoregressive coefficient and sample moment, respectively. The PANIC model approximates the number of factors based on Bai and Ng (2002) <doi:10.1111/1468-0262.00273>.
Interface to a large number of classification and regression techniques, including machine-readable parameter descriptions. There is also an experimental extension for survival analysis, clustering and general, example-specific cost-sensitive learning. Generic resampling, including cross-validation, bootstrapping and subsampling. Hyperparameter tuning with modern optimization techniques, for single- and multi-objective problems. Filter and wrapper methods for feature selection. Extension of basic learners with additional operations common in machine learning, also allowing for easy nested resampling. Most operations can be parallelized.
Specify, build, trade, and analyse quantitative financial trading strategies.