Draws systematic samples from a population that follows linear trend. The function returns a matrix comprising of the required samples as its column vectors. The samples produced are highly efficient and the inter sampling variance is minimum. The scheme will be useful in various field like Bioinformatics where the samples are expensive and must be precise in reflecting the population by possessing least sampling variance.

CUR/CX decomposition factorizes a matrix into two factor matrices and Multidimensional CX Decomposition factorizes a tensor into a core tensor and some factor matrices. See the reference section of GitHub README.md <https://github.com/rikenbit/ccTensor>, for details of the methods.

A simple interface for multivariate correlation analysis that unifies various classical
  statistical procedures including t-tests, tests in univariate and multivariate linear models,
  parametric and nonparametric tests for correlation, Kruskal-Wallis tests, common approximate
  versions of Wilcoxon rank-sum and signed rank tests, chi-squared tests of independence, score
  tests of particular hypotheses in generalized linear models, canonical correlation analysis and
  linear discriminant analysis.

Implements the uniform scaled beta distribution and
  the continuous convolution kernel density estimator.

Automated assessment and selection of weighting factors for accurate quantification using linear calibration curve. 
 In addition, a 'shiny' App is provided, allowing users to analyze their data using an interactive graphical user interface, without any programming requirements.

Duplicated music data (pre-processed and formatted) for entity resolution. The total size of the data set is 9763. There are respective gold standard records that are labeled and can be considered as a unique identifier.

Supplies higher-order coordinatized data specification and fluid transform operators that include pivot and anti-pivot as special cases. 
    The methodology is describe in 'Zumel', 2018, "Fluid data reshaping with 'cdata'", <https://winvector.github.io/FluidData/FluidDataReshapingWithCdata.html> , <DOI:10.5281/zenodo.1173299> .
    This package introduces the idea of explicit control table specification of data transforms.
    Works on in-memory data or on remote data using 'rquery' and 'SQL' database interfaces.