Wrapper functions to model and extract various quantitative information from absorption spectra of chromophoric dissolved organic matter (CDOM).

Parallel coordinate plotting with resolutions for large data sets
 and missing values.

A wrapper for the 'CDRC' 'API' that returns data frames or 'sf' of 'CDRC' data. The 'API' web reference is:<https://api.cdrc.ac.uk/swagger/index.html>.

This is an implementation of constrained dual scaling for
    detecting response styles in categorical data, including utility functions. The
    procedure involves adding additional columns to the data matrix representing the
    boundaries between the rating categories. The resulting matrix is then doubled
    and analyzed by dual scaling. One-dimensional solutions are sought which provide
    optimal scores for the rating categories. These optimal scores are constrained
    to follow monotone quadratic splines. Clusters are introduced within which the
    response styles can vary. The type of response style present in a cluster can
    be diagnosed from the optimal scores for said cluster, and this can be used to
    construct an imputed version of the data set which adjusts for response styles.

Provides interface to the 'Copernicus Data Space Ecosystem' API 
    <https://dataspace.copernicus.eu/analyse/apis>, mainly for searching the catalog of available
    data from Copernicus Sentinel missions and obtaining the images for just the area of interest 
    based on selected spectral bands. The package uses the 'Sentinel Hub' REST API interface
    <https://dataspace.copernicus.eu/analyse/apis/sentinel-hub> that provides access to various 
    satellite imagery archives. It allows you to access raw satellite data, rendered images, 
    statistical analysis, and other features.

Deriving skill structures from skill assignment 
    data for courses (sets of learning objects).

Cuddy-Della valle index gives the degree of instability present in the data by accommodating the effect of a trend. The adjusted R squared value of the best fitted model is chosen. The index is obtained by multiplying the coefficient of variation with square root of one minus the adjusted R-squared value. This package has been developed using concept of Shankar et al. (2022)<doi:10.3389/fsufs.2023.1208898>.