Functions to aid in micro and macro economic analysis and handling of price and
    currency data. Includes extraction of relevant inflation and exchange rate data from World Bank
    API, data cleaning/parsing, and standardisation. Inflation adjustment
    calculations as found in Principles of Macroeconomics by Gregory Mankiw et al (2014). Current
    and historical end of day exchange rates for 171 currencies from the European Central Bank
    Statistical Data Warehouse (2020).

An implementation of the van Westendorp Price
    Sensitivity Meter in R, which is a survey-based approach
	to analyze consumer price preferences and sensitivity
    (van Westendorp 1976, isbn:9789283100386).

Implements the 'PRIDIT' (Principal Component Analysis applied to 
    'RIDITs') scoring system described in Brockett et al. (2002) 
    <doi:10.1111/1539-6975.00027>. Provides functions for ridit scoring 
    originally developed by Bross (1958) <doi:10.2307/2527727>, calculating 
    'PRIDIT' weights, and computing final 'PRIDIT' scores for multivariate 
    analysis of ordinal data.

Patient Rule Induction Method (PRIM) for bump hunting in high-dimensional data.

Implements a unified framework of parametric simplex method for a variety of sparse learning problems (e.g., Dantzig selector (for linear regression), sparse quantile regression, sparse support vector machines, and compressive sensing) combined with efficient hyper-parameter selection strategies. The core algorithm is implemented in C++ with Eigen3 support for portable high performance linear algebra. For more details about parametric simplex method, see Haotian Pang (2017) <https://papers.nips.cc/paper/6623-parametric-simplex-method-for-sparse-learning.pdf>.

Provides functions for working with primary
    event censored distributions and 'Stan' implementations for use in Bayesian
    modeling. Primary event censored distributions are useful for modeling
    delayed reporting scenarios in epidemiology and other fields (Charniga et
    al. (2024) <doi:10.48550/arXiv.2405.08841>). It also provides support for
    arbitrary delay distributions, a range of common primary distributions, and
    allows for truncation and secondary event censoring to be accounted for
    (Park et al. (2024) <doi:10.1101/2024.01.12.24301247>). A subset of
    common distributions also have analytical solutions implemented, allowing
    for faster computation. In addition, it provides multiple methods for
    fitting primary event censored distributions to data via optional
    dependencies.