A tool for bootstrapping new packages with useful defaults,
    including a test suite outline that passes checks and helpers for running
    tests, checking test coverage, building vignettes, and more. Package
    skeletons it creates are set up for pushing your package to
    'GitHub' and using other hosted services for building and test automation.

Functions for the Skellam distribution, including: density
    (pmf), cdf, quantiles and regression.

Creates static / animated / interactive visualisations embeddable
    in R Markdown documents. It implements an R-to-JavaScript transpiler and
    enables users to write JavaScript applications using the syntax of R.

An implementation of image processing effects that convert a photo into a line drawing image. 
    For details, please refer to Tsuda, H. (2020). sketcher: An R package for converting a photo into a sketch style image. 
    <doi:10.31234/osf.io/svmw5>.

Construct sketches of data via random subspace embeddings. 
  For more details, see the following papers.
  Lee, S. and Ng, S. (2022). "Least Squares Estimation Using Sketched Data with Heteroskedastic Errors," Proceedings of the 39th International Conference on Machine Learning (ICML22), 162:12498-12520.
  Lee, S. and Ng, S. (2020). "An Econometric Perspective on Algorithmic Subsampling," Annual Review of Economics, 12(1): 45–80.

Provides functions to create and manage research compendiums for data analysis. Research compendiums are a standard and intuitive folder structure for organizing the digital materials of a research project, which can significantly improve reproducibility. The package offers several compendium structure options that fit different research project as well as the ability of duplicating the folder structure of existing projects or implementing custom structures. It also simplifies the use of version control.

Functions are provided for the density function,
	     distribution function, quantiles and random number
	     generation for the skew hyperbolic
	     t-distribution. There are also functions that fit
	     the distribution to data. There are functions for the
	     mean, variance, skewness, kurtosis and mode of a given
	     distribution and to calculate moments of any order about
	     any centre. To assess goodness of fit, there are
	     functions to generate a Q-Q plot, a P-P plot and a tail plot.