Joint dimension reduction and spatial clustering is conducted for
    Single-cell RNA sequencing and spatial transcriptomics data, and more details can be referred to 
    Wei Liu, Xu Liao, Yi Yang, Huazhen Lin, Joe Yeong, Xiang Zhou, Xingjie Shi and Jin Liu. (2022) <doi:10.1093/nar/gkac219>. It is not only computationally efficient and scalable to the sample size increment, but also is capable of choosing the smoothness parameter and the number of clusters as well.

Models the relationship between dose levels and responses in a pharmacological experiment using the 4 Parameter Logistic model. Traditional packages on dose-response modelling such as 'drc' and 'nplr' often draw errors due to convergence failure especially when data have outliers or non-logistic shapes. This package provides robust estimation methods that are less affected by outliers and other initialization methods that work well for data lacking logistic shapes. We provide the bounds on the parameters of the 4PL model that prevent parameter estimates from diverging or converging to zero and base their justification in a statistical principle. These methods are used as remedies to convergence failure problems.  Gadagkar, S. R. and Call, G. B. (2015) <doi:10.1016/j.vascn.2014.08.006> Ritz, C. and Baty, F. and Streibig, J. C. and Gerhard, D. (2015) <doi:10.1371/journal.pone.0146021>.

Decodes meshes and point cloud data encoded by the Draco mesh
    compression library from Google. Note that this is only designed for basic
    decoding and not intended as a full scale wrapping of the Draco library.

Statistical tests and test statistics to identify events in a
    dataset that are dragon kings (DKs). The statistical methods in this
    package were reviewed in Wheatley & Sornette (2015) <doi:10.2139/ssrn.2645709>.

These are data sets for the hit TV show, RuPaul's Drag Race. 
    Data right now include episode-level data, contestant-level data, and 
    episode-contestant-level data. This is a work in progress, and a love letter
    of a kind to RuPaul's Drag Race and the performers that have appeared on the show.
    This may not be the most productive use of my time, but I have tenure and what 
    are you going to do about it? I think there is at least some value in this package
    if it allows the show's fandom to learn more about the R programming language 
    around its contents.