Estimation and inference methods for the continuous threshold expectile regression.
    It can fit the continuous threshold expectile regression and test the existence of change point,
    for the paper, "Feipeng Zhang and Qunhua Li (2016). A continuous threshold expectile regression, submitted."

Identification and network inference of genetic loci associated
  with correlation changes in quantitative traits (called correlated trait loci, CTLs).
  Arends et al. (2016) <doi:10.21105/joss.00087>.

Estimation of Markov generator matrices from discrete-time observations. The implemented approaches comprise diagonal and weighted adjustment of matrix logarithm based candidate solutions as in Israel (2001) <doi:10.1111/1467-9965.00114> as well as a quasi-optimization approach. Moreover, the expectation-maximization algorithm and the Gibbs sampling approach of Bladt and Sorensen (2005) <doi:10.1111/j.1467-9868.2005.00508.x> are included.

Software to facilitates taking movement data in xyt format and pairing it with raster covariates within a continuous time Markov chain (CTMC) framework.  As described in Hanks et al. (2015) <DOI:10.1214/14-AOAS803> , this allows flexible modeling of movement in response to covariates (or covariate gradients) with model fitting possible within a Poisson GLM framework.

Computes effect sizes, standard errors, and confidence intervals
    for total, direct, and indirect effects in continuous-time mediation models
    as described in Pesigan, Russell, and Chow (2025) <doi:10.1037/met0000779>.

Implements the general template for collaborative targeted maximum likelihood estimation. It also provides several commonly used C-TMLE instantiation, like the vanilla/scalable variable-selection C-TMLE (Ju et al. (2017) <doi:10.1177/0962280217729845>) and the glmnet-C-TMLE algorithm (Ju et al. (2017) <arXiv:1706.10029>).

Implements a basis function or functional data analysis framework
             for several techniques of multivariate analysis in continuous-time 
             setting. Specifically, we introduced continuous-time analogues of
             several classical techniques of multivariate analysis, such as 
             principal component analysis, canonical correlation analysis, 
             Fisher linear discriminant analysis, K-means clustering, and so 
             on. Details are in Biplab Paul, Philip T. Reiss, Erjia Cui and Noemi Foa (2025) 
             "Continuous-time multivariate analysis" <doi: 10.1080/10618600.2024.2374570>.