Provides tools to easily access and analyze Canadian Election Study data.
    The package simplifies the process of downloading, cleaning, and using 'CES' datasets
    for political science research and analysis. The Canadian Election Study ('CES')
    has been conducted during federal elections since 1965, surveying Canadians
    on their political preferences, engagement, and demographics. Data is accessed
    from multiple sources including the 'Borealis' Data repository 
    <https://borealisdata.ca/> and the official 'Canadian Election Study' website 
    <https://ces-eec.arts.ubc.ca/>. This package is not officially affiliated 
    with the Canadian Election Study, 'Borealis' Data, or the University of British 
    Columbia, and users should cite the original data sources in their work.

Implementation of the Cluster Estimated Standard Errors (CESE) proposed in Jackson (2020) <DOI:10.1017/pan.2019.38> to compute clustered standard errors of linear coefficients in regression models with grouped data.

Collection of perceptually uniform colour maps made by Peter Kovesi
    (2015) "Good Colour Maps: How to Design Them" <arXiv:1509.03700> 
    at the Centre for Exploration Targeting (CET).

Ceteris Paribus Profiles (What-If Plots) are designed to present model 
    responses around selected points in a feature space. 
    For example around a single prediction for an interesting observation. 
    Plots are designed to work in a model-agnostic fashion, they are working 
    for any predictive Machine Learning model and allow for model comparisons.
    Ceteris Paribus Plots supplement the Break Down Plots from 'breakDown' package.

Analysis of configuration frequencies for simple and repeated measures, multiple-samples CFA, hierarchical CFA, bootstrap CFA, functional CFA, Kieser-Victor CFA, and Lindner's test using a conventional and an accelerated algorithm.

Cellular cooperation compromises the plating efficiency-based 
    analysis of clonogenic survival data. This tool provides functions that 
    enable a robust analysis of colony formation assay (CFA) data in presence 
    or absence of cellular cooperation. 
    The implemented method has been described 
    in Brix et al. (2020). (Brix, N., Samaga, D., Hennel, R. et al. 
    "The clonogenic assay: robustness of plating efficiency-based analysis is 
    strongly compromised by cellular cooperation." Radiat Oncol 15, 248 (2020).
    <doi:10.1186/s13014-020-01697-y>)
        Power regression for parameter estimation, calculation of survival
    fractions, uncertainty analysis and plotting functions are provided.