Calibration of thresholds of control charts such as
    CUSUM charts based on past data, taking estimation error into account.

A new reduced-rank LDA method which works for high dimensional multi-class data.

Provides functions for coarse-to-fine spatial modeling (CFSM), enabling fast spatial prediction, regression, and uncertainty quantification. This method is suitable for moderate to large samples. For methodological details, see Murakami et al. (2026) <doi:10.1111/gean.70034> and related works on its generalized-linear <doi:10.48550/arXiv.2605.01157> and downscaling extensions.

Fast computation of the required sample size or the
    achieved power, for GWAS studies with different types of covariate
    effects and different types of covariate-gene dependency structure.
    For the detailed description of the methodology, see Zhang (2022)
    "Power and Sample Size Computation for Genetic Association Studies
     of Binary Traits: Accounting for Covariate Effects" <arXiv:2203.15641>.

Computes the effective range of a smoothing matrix, 
    which is a measure of the distance to which smoothing occurs. 
    This is motivated by the application of spatial splines for adjusting 
    for unmeasured spatial confounding in regression models, but the
    calculation of effective range can be applied to smoothing 
    matrices in other contexts. For algorithmic details, see Rainey and Keller
    (2024) "spconfShiny: an R Shiny application..." <doi:10.1371/journal.pone.0311440>
    and Keller and Szpiro (2020)
    "Selecting a Scale for Spatial Confounding Adjustment" <doi:10.1111/rssa.12556>.

Spatial coverage sampling and random sampling from compact
        geographical strata created by k-means. See Walvoort et al. (2010) 
        <doi:10.1016/j.cageo.2010.04.005> for details.

Provides a covariance estimator for multivariate normal
        data that is sparse and positive definite.  Implements the
        majorize-minimize algorithm described in Bien, J., and
        Tibshirani, R. (2011), "Sparse Estimation of a Covariance
        Matrix," Biometrika. 98(4). 807--820.