Functions to access and test results from a linear model.

Consider linear regression model Y = Xb + error where the distribution function of errors is unknown, but errors are independent and symmetrically distributed. The package contains a function named LRMDE which takes Y and X as input and returns minimum distance estimator of parameter b in the model.

Tests whether the linear hypothesis of a model
    is correct specified using Dominguez-Lobato test. Also Ramsey's RESET (Regression Equation 
    Specification Error Test) test is implemented and Wald tests can be carried out. 
    Although RESET test is widely used to 
    test the linear hypothesis of a model, Dominguez and Lobato (2019) proposed a novel 
    approach that generalizes well known specification tests such as Ramsey's. This test 
    relies on wild-bootstrap; this package implements this approach to be 
    usable with any function that fits linear models and is compatible with 
    the update() function such as 'stats'::lm(), 'lfe'::felm() and 'forecast'::Arima(), 
    for ARMA (autoregressive–moving-average) models. 
    Also the package can handle custom statistics such as Cramer von Mises and Kolmogorov 
    Smirnov, described by the authors, and custom distributions such as Mammen (discrete 
    and continuous) and Rademacher.
    Manuel A. Dominguez & Ignacio N. Lobato (2019) <doi:10.1080/07474938.2019.1687116>.

Provides tools to help storing and handling case line list data. The 'linelist' class adds a tagging system to classical 'data.frame' objects to identify key epidemiological data such as dates of symptom onset, epidemiological case definition, age, gender or disease outcome. Once tagged, these variables can be seamlessly used in downstream analyses, making data pipelines more robust and reliable.

Provides tools for performing Bayesian inference on epidemiological 
  data to estimate the time-varying reproductive number and other related metrics.
  These methods were published in Li and White (2021) <doi:10.1371/journal.pcbi.1009210>.
  This package supports analyses based on aggregated case count data and individual line list 
  data, facilitating enhanced surveillance and intervention planning for infectious 
  diseases like COVID-19.