R Package: PARSE
  • Author: Lulu Wang, Wen Zhou, and Jennifer Hoeting
  • Maintainer : Lulu Wang
  • Reference: L. Wang, W. Zhou and J. Hoeting (2017). Identification of pairwise informative features for cluster analysis.
  • Download link : CRAN, Github

R Package: HDtest
  • Author: Meng Cao, Tong He, and Wen Zhou
  • Maintainer : Meng Cao
  • Reference:
    • J. Chang, W. Zhou, L. Wang, and W.-X. Zhou (2017). Comparing large covariance matrices under weak conditions on the dependence structure and its application to gene clustering, Biometrics 2017, 73, 31-41. (website, pdf)
    • J. Chang, C. Zheng, W.-X. Zhou, and W. Zhou (2017). Simulation-based hypothesis testing of high dimensional means under covariance heterogeneity, Biometrics 2017, DOI: 10.1111/biom.12695. (website, pdf)
    • J. Chang, Q. Yao, and W. Zhou (2017). Testing for high-dimensional white noise using maximum cross correlations, Biometrika 2017, 104, 111-127. (website, pdf)
  • Download link : CRAN, Github (updated 08/22/2018)

R Package: MAPTest
  • Author: Meng Cao and Wen Zhou
  • Maintainer : Meng Cao
  • Reference: M. Cao, W. Zhou, J.F. Breidt, and G. Peers (2018). Large scale maximum average power multiple inference on time-course count data with application to RNA-Seq analysis.
  • Download link : Github

R Package: CESME
  • Author: Lulu Wang and Wen Zhou
  • Maintainer : Lulu Wang
  • Reference: L. Wang, L. Zhang, W. Zhou, and H. Zou (2018). CESME: Cluster analysis with latent semiparametric mixture models.
  • Download link : Github