For a balanced design of experiments, this package calculates the sample size required to detect a certain standardized effect size, under a significance level. This package also provides three graphs; detectable standardized effect size vs power, sample size vs detectable standardized effect size, and sample size vs power, which show the mutual relationship between the sample size, power and the detectable standardized effect size. The detailed procedure is described in R. V. Lenth (2006-9) <https://homepage.divms.uiowa.edu/~rlenth/Power/>, Y. B. Lim (1998), M. A. Kastenbaum, D. G. Hoel and K. O. Bowman (1970) <doi:10.2307/2334851>, and Douglas C. Montgomery (2013, ISBN: 0849323312).

Statistical tools for Bayesian structure learning in undirected graphical models for continuous, ordinal/discrete/count, and mixed data. The package is implemented the recent improvements in the Bayesian graphical models' literature, including Mohammadi and Wit (2015) <doi:10.1214/14-BA889>, Mohammadi et al. (2021) <doi:10.1080/01621459.2021.1996377>, and Dobra and Mohammadi (2018) <doi:10.1214/18-AOAS1164>.

Interface to Local Data Bank ('Bank Danych Lokalnych' - 'bdl') API 
    <https://api.stat.gov.pl/Home/BdlApi?lang=en> with set of useful tools like 
    quick plotting and map generating using data from bank.

The main function generateDataset() processes a user-supplied .R file that 
  contains metadata parameters in order to generate actual data. The metadata parameters 
  have to be structured in the form of metadata objects, the format of which is 
  outlined in the package vignette. This approach allows to generate artificial data 
  in a transparent and reproducible manner.

Analyze differences among time series curves with p-value
        adjustment for multiple comparisons introduced in Oleson et al
        (2015) <DOI:10.1177/0962280215607411>.

Tools and workflow to choose design parameters in Bayesian adaptive single-arm phase II trial designs with binary endpoint (response, success) with possible stopping for efficacy and futility at interim analyses. Also contains routines to determine and visualize operating characteristics. See Kopp-Schneider et al. (2018) <doi:10.1002/bimj.201700209>.