farmtest: FarmTest: Factor Adjusted Robust Multiple Testing
In kbose28/farmtest: Factor Adjusted Robust Multiple Testing

This R package conducts multiple hypothesis testing of mean effects. It implements a robust procedure to estimate distribution parameters and accounts for strong dependence among coordinates via an approximate factor model. This method is particularly suitable for high-dimensional data when there are thousands of variables but only a small number of observations available. Moreover, the method is tailored to cases when the underlying distribution deviates from Gaussianity, which is commonly assumed in the literature. For detailed information on how to use and install see https://kbose28.github.io/FarmTest/. See the papers on the 'FarmTest' method, Fan et al.(2017) and Zhou at al.(2017), for detailed description of methods and further references.

Fan, J., Ke, Y., Sun, Q. and Zhou, W-X. (2017). "FARM-Test: Factor-adjusted robust multiple testing with false discovery control," https://arxiv.org/abs/1711.05386.

Zhou, W-X., Bose, K., Fan, J. and Liu, H. (2017). "A New Perspective on Robust M-Estimation: Finite Sample Theory and Applications to Dependence-Adjusted Multiple Testing," Annals of Statistics, to appear, https://arxiv.org/abs/1711.05381.

kbose28/farmtest documentation built on May 29, 2019, 3:01 a.m.