Methods include converting series of event names to strings, finding common patterns
    in a group of strings, discovering featured patterns when comparing two groups of strings as well
    as the number and starting position of each pattern in each string, obtaining transition matrix, 
    computing transition entropy, statistically comparing the difference between two groups of strings,
    and clustering string groups. Event names can be any action names or labels such as events in log
    files or areas of interest (AOIs) in eye tracking research.

Alternative implementations of some base R functions, including sort, order, and match.  Functions are simplified but can be faster or have other advantages.

Computational resources for test proposed by Gibbons, Ross, Shanken (1989)<DOI:10.2307/1913625>.
	It also has the functions for the power analysis and the choice of the optimal level of significance.
	The optimal level is determined by minimizing the expected loss from hypothesis testing.

Simulation and analysis of graded response data with different types of estimators. Also, an interactive shiny application is provided with graphics for characteristic and information curves. Samejima (2018) <doi:10.1007/978-1-4757-2691-6_5>.

Statistical testing procedures for detecting
  GxE (gene-environment) interactions. The main focus lies on
  GRSxE interaction tests that aim at detecting GxE interactions
  through GRS (genetic risk scores). Moreover, a novel testing
  procedure based on bagging and OOB (out-of-bag) predictions is
  implemented for incorporating all available observations at
  both GRS construction and GxE testing (Lau et al., 2023,
  <doi:10.1038/s41598-023-28172-4>).

Functions to generate and analyze data for psychology experiments based on the General Recognition Theory.

Offers functions for the comparison of Gutenberg-Richter 
	b-values. Several functions in GRTo are helpful for the assessment of the
	quality of seismicity catalogs.

River hydrograph separation and daily runoff time series analysis. Provides
  various filters to separate baseflow and quickflow. Implements advanced separation 
  technique by Rets et al. (2022) <doi:10.1134/S0097807822010146> which involves 
  meteorological data to reveal genetic components of the runoff: ground, rain, thaw 
  and spring (seasonal thaw). High-performance C++17 computation, annually aggregated 
  variables, statistical testing and numerous plotting functions for high-quality 
  visualization.