Merges and downloads 'SPSS' data from different International Large-Scale Assessments (ILSA), including: Trends in International Mathematics and Science Study (TIMSS), Progress in International Reading Literacy Study (PIRLS), and others.

Calculates point estimates and standard errors using replicate weights and plausible values for International Large-Scale Assessments (ILSA), including: means, proportions, quantiles, correlations, singlelevel regressions, and multilevel regressions.

In view of the analysis of the structural characteristics of the tripartite 
    network has been complete, however, there is still a lack of a unified 
    operation that can quickly obtain the corresponding characteristics of the 
    tripartite network. 
    To solve this insufficiency, 'ILSM' was designed for supporting calculating 
    such metrics of tripartite networks by functions of this R package.

Provides functionality to perform a likelihood-free method for estimating the parameters of complex models
    that results in a simulated sample from the posterior distribution of model parameters given targets. The method begins
    with a accept/reject approximate bayes computation (ABC) step applied to a sample of points from the prior distribution
    of model parameters. Accepted points result in model predictions that are within the initially specified tolerance
    intervals around the target points. The sample is iteratively updated by drawing additional points from a mixture of
    multivariate normal distributions, accepting points within tolerance intervals. As the algorithm proceeds, the
    acceptance intervals are narrowed. The algorithm returns a set of points and sampling weights that account for the
    adaptive sampling scheme. For more details see Rutter, Ozik, DeYoreo, and Collier (2018) <arXiv:1804.02090>.

Improve optical character recognition by binarizing images. The package focuses primarily on local adaptive thresholding algorithms. 
    In English, this means that it has the ability to turn a color or gray scale image into a black and white image. This is particularly useful
    as a preprocessing step for optical character recognition or handwritten text recognition.