Non-statistical utilities used by the software developed by the Statnet Project. They may also be of use to others.

A graphical user interface for cross-sectional network modeling 
    with the 'statnet' software suite <https://github.com/statnet>.

Get programmatic access to data from the Czech public
    budgeting and accounting database, Státní pokladna
    <https://monitor.statnipokladna.gov.cz/>.

Statistical performance measures used in the econometric literature to evaluate conditional covariance/correlation matrix estimates (MSE, MAE, Euclidean distance, Frobenius distance, Stein distance, asymmetric loss function, eigenvalue loss function and the loss function defined in Eq. (4.6) of Engle et al. (2016) <doi:10.2139/ssrn.2814555>). Additionally, compute Eq. (3.1) and (4.2) of Li et al. (2016) <doi:10.1080/07350015.2015.1092975> to compare the factor loading matrix. The statistical performance measures implemented have been previously used in, for instance, Laurent et al. (2012) <doi:10.1002/jae.1248>,  Amendola et al. (2015) <doi:10.1002/for.2322> and  Becker et al. (2015) <doi:10.1016/j.ijforecast.2013.11.007>.

A small collection of data on graduate statistics programs from the United States.

Implements confidence interval and sample size methods that are especially
    useful in psychological research but are also useful in educational, social science, 
    business, and biological research. This package includes more than 100 confidence 
    interval functions and more than 80 sample size functions for 1-group, 2-group, 
    paired-samples, and multiple-group designs and for a variety of parameters including 
    means, medians, proportions, slopes, standardized mean differences, standardized 
    linear contrasts of means, and several measures of correlation and association. The 
    sample size functions can be used to approximate the sample size needed to estimate
    a parameter or function of parameters with desired confidence interval precision or 
    to perform a variety of hypothesis tests (directional two-sided, equivalence, 
    superiority, noninferiority) with desired power. For details about these methods see: 
    Statistical Methods for Psychologists, Volumes 1 – 4, <https://dgbonett.sites.ucsc.edu/>.