The maximum likelihood estimation (MLE) of the count data models along with standard error of the estimates and Akaike information model section criterion are provided. The functions allow to compute the MLE for the following distributions such as the Bell distribution, the Borel distribution, the Poisson distribution, zero inflated Bell distribution, zero inflated Bell Touchard distribution, zero inflated Poisson distribution, zero one inflated Bell distribution and zero one inflated Poisson distribution. Moreover, the probability mass function (PMF), distribution function (CDF), quantile function (QF) and random numbers generation of the Bell Touchard and zero inflated Bell Touchard distribution are also provided.

A simple countdown timer for slides and HTML documents
    written in 'R Markdown' or 'Quarto'. Integrates fully into 'Shiny'
    apps. Countdown to something amazing.

Implements the estimation and inference methods for counterfactual analysis described in Chernozhukov, Fernandez-Val and Melly (2013) <DOI:10.3982/ECTA10582> "Inference on Counterfactual Distributions," Econometrica, 81(6). The counterfactual distributions considered are the result of changing either the marginal distribution of covariates related to the outcome variable of interest, or the conditional distribution of the outcome given the covariates. They can be applied to estimate quantile treatment effects and wage decompositions.

Modular and unified R6-based interface for counterfactual explanation methods.
    The following methods are currently implemented: Burghmans et al. (2022) <doi:10.48550/arXiv.2104.07411>, 
    Dandl et al. (2020) <doi:10.1007/978-3-030-58112-1_31> and Wexler et al. (2019) <doi:10.1109/TVCG.2019.2934619>.
    Optional extensions allow these methods to be applied to a variety of models and use cases.
    Once generated, the counterfactuals can be analyzed and visualized by provided functionalities.

Randomization-Based Inference for customized experiments.
  Computes Fisher-Exact P-Values alongside null randomization 
  distributions. Retrieves counternull sets and generates counternull 
  distributions. Computes Fisher Intervals and Fisher-Adjusted P-Values. 
  Package includes visualization of randomization distributions and Fisher 
  Intervals. Users can input custom test statistics and their own methods for 
  randomization. 
  Rosenthal and Rubin (1994) <doi:10.1111/j.1467-9280.1994.tb00281.x>.