The level-dependent cross-validation method is implemented
        for the selection of thresholding
        value in wavelet shrinkage. This procedure is implemented
        by coupling a conventional cross validation with an
        imputation method due to a limitation of data length,
        a power of 2. It can be easily applied to classical
        leave-one-out and k-fold cross validation.
        Since the procedure is computationally fast,
        a level-dependent cross validation can be performed for
        wavelet shrinkage of various data such as a data
        with correlated errors.

Tools that allow developers to write functions for
    cross-validation with minimal programming effort and assist
    users with model selection.

An object-oriented modeling language for disciplined
    convex programming (DCP) as described in Fu, Narasimhan, and Boyd
    (2020, <doi:10.18637/jss.v094.i14>). It allows the user to
    formulate convex optimization problems in a natural way following
    mathematical convention and DCP rules. The system analyzes the
    problem, verifies its convexity, converts it into a canonical
    form, and hands it off to an appropriate solver to obtain the
    solution. This version uses the S7 object system for improved
    performance and maintainability.

A flexible and robust joint test of the single nucleotide polymorphism (SNP) main effect and genotype-by-treatment interaction effect for continuous and binary endpoints. Two analytic procedures, Cauchy weighted joint test (CWOT) and adaptively weighted joint test (AWOT), are proposed to accurately calculate the joint test p-value. The proposed methods are evaluated through extensive simulations under various scenarios. The results show that the proposed AWOT and CWOT control type I error well and outperform existing methods in detecting the most interesting signal patterns in pharmacogenetics (PGx) association studies. For reference, see Hong Zhang, Devan Mehrotra and Judong Shen (2022) <doi:10.13140/RG.2.2.28323.53280>.