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.

It fits scale mixture of skew-normal linear mixed models using either an expectation–maximization (EM) type algorithm or its accelerated version (Damped Anderson Acceleration with Epsilon Monotonicity, DAAREM), including some possibilities for modeling the within-subject dependence. Details can be found in Schumacher, Lachos and Matos (2021) <doi:10.1002/sim.8870>.

Provide data generation and estimation tools for the multivariate scale mixtures of normal 
             presented in Lange and Sinsheimer (1993) <doi:10.2307/1390698>, the multivariate scale 
             mixtures of skew-normal presented in Zeller, Lachos and Vilca (2011) 
             <doi:10.1080/02664760903406504>, the multivariate skew scale mixtures of normal 
             presented in Louredo, Zeller and Ferreira (2021) <doi:10.1007/s13571-021-00257-y>
             and the multivariate scale mixtures of skew-normal-Cauchy presented in Kahrari et al. (2020)
	     <doi:10.1080/03610918.2020.1804582>.