Provides the function to calculate the kernel-lasso expansion, Z-score, and max-min-scale standardization.It can increase the dimension of existed dataset and remove abundant features by lasso. Z Dai, L Jiayi, T Gong, C Wang (2021) <doi:10.1088/1742-6596/1955/1/012047>.

Detects classical candlestick patterns and structure-based chart
    patterns from open, high, low, close, and volume (OHLCV) time series and
    provides reusable stock-screening workflows. Built-in detectors include
    single- and multi-candle patterns, trend structures such as double bottoms
    and ascending triangles, and a configurable "golden pit" recovery setup.
    Includes a unified API to run pattern scans across one or many symbols.
    Methods are informed by Nison (2001, ISBN:9780735201811) "Japanese
    Candlestick Charting Techniques" and Bulkowski (2021,
    ISBN:9781119739685) "Encyclopedia of Chart Patterns".

A 'shiny' application for forensic kinship testing, based on
    the 'pedsuite' R packages. 'KLINK' is closely aligned with the (non-R)
    software 'Familias' and 'FamLink', but offers several unique features,
    including visualisations and automated report generation. The
    calculation of likelihood ratios supports pairs of linked markers, and
    all common mutation models. The program is described in Vigeland and
    Gilfillan (2026) <doi:10.1016/j.fsigen.2026.103578>.

A comprehensive set of geostatistical, visual,
    and analytical methods, in conjunction with the expanded version of the
    acclaimed J.E. Klovan's mining dataset, are included in 'klovan'. This makes the
    package an excellent learning resource for Principal Component Analysis (PCA),
    Factor Analysis (FA), kriging, and other geostatistical techniques. Originally
    published in the 1976 book 'Geological Factor Analysis', the included mining
    dataset was assembled by Professor J. E. Klovan of the University of Calgary.
    Being one of the first applications of FA in the geosciences, this dataset has
    significant historical importance. As a well-regarded and published dataset, it
    is an excellent resource for demonstrating the capabilities of PCA, FA, kriging,
    and other geostatistical techniques in geosciences. For those interested in
    these methods, the 'klovan' datasets provide a valuable and illustrative resource.
    Note that some methods require the 'RGeostats' package. Please refer to the
    README or Additional_repositories for installation instructions. This material is
    based upon research in the Materials Data Science for Stockpile Stewardship Center
    of Excellence (MDS3-COE), and supported by the Department of Energy's National
    Nuclear Security Administration under Award Number DE-NA0004104.