Provides a set of functions for conducting cognitive diagnostic computerized adaptive testing applications (Chen, 2009) <DOI:10.1007/s11336-009-9123-2>). It includes different item selection rules such us the global discrimination index (Kaplan, de la Torre, and Barrada (2015) <DOI:10.1177/0146621614554650>) and the nonparametric selection method (Chang, Chiu, and Tsai (2019) <DOI:10.1177/0146621618813113>), as well as several stopping rules. Functions for generating item banks and responses are also provided. To guide item bank calibration, model comparison at the item level can be conducted using the two-step likelihood ratio test statistic by Sorrel, de la Torre, Abad and Olea (2017) <DOI:10.1027/1614-2241/a000131>.

Allows users to seamlessly query several 'CDC PLACES' APIs (<https://data.cdc.gov/browse?q=PLACES%20&sortBy=relevance>)
    by geography, state, measure, and release year. This package also contains a
    function to explore the available measures for each release year.

Conditional distance correlation <doi:10.1080/01621459.2014.993081> is a novel conditional dependence measurement of two multivariate random variables given a confounding variable. This package provides conditional distance correlation, performs the conditional distance correlation sure independence screening procedure for ultrahigh dimensional data <https://www3.stat.sinica.edu.tw/statistica/J28N1/J28N114/J28N114.html>, and conducts conditional distance covariance test for conditional independence assumption of two multivariate variable.

Connect to the California Data Exchange Center (CDEC) 
    Web Service <http://cdec.water.ca.gov/>. 'CDEC' provides a centralized 
    database to store, process, and exchange real-time hydrologic information 
    gathered by various cooperators throughout California. The 'CDEC' Web Service 
    <http://cdec.water.ca.gov/dynamicapp/wsSensorData> provides a data download 
    service for accessing historical records.

Employs a two-parameter family of
    distributions for modelling random variables on the (0, 1) interval by
    applying the cumulative distribution function (cdf) of one parent
    distribution to the quantile function of another.