Systematic fit of hundreds of theoretical univariate distributions to empirical data via maximum likelihood estimation. Fits are reported and summarized by a data.frame, a csv file or a 'shiny' app (here with additional features like visual representation of fits). All output formats provide assessment of goodness-of-fit by the following methods: Kolmogorov-Smirnov test, Shapiro-Wilks test, Anderson-Darling test.

Extends the fitdist() (from 'fitdistrplus') adding the Anderson-Darling ad.test() (from 'ADGofTest') and Kolmogorov Smirnov Test ks.test() inside, trying the distributions from 'stats' package by default and offering a second function which uses mixed distributions to fit, this distributions are split with unsupervised learning, with Mclust() function (from 'mclust').

Wrapper for computing parameters for univariate distributions using MLE. It creates an object that stores d, p, q, r functions as well as parameters and statistics for diagnostics. Currently supports automated fitting from base and actuar packages. A manually fitting distribution fitting function is included to support directly specifying parameters for any distribution from ancillary packages.

An easy package for scraping and processing Australia Rules Football (AFL)
    data. 'fitzRoy' provides a range of functions for accessing publicly available data 
    from 'AFL Tables' <https://afltables.com/afl/afl_index.html>, 'Footy Wire' <https://www.footywire.com> and
    'The Squiggle' <https://squiggle.com.au>. Further functions allow for easy processing, 
    cleaning and transformation of this data into formats that can be used for analysis.

Datasets and code published by the data journalism website 
    'FiveThirtyEight' available at <https://github.com/fivethirtyeight/data>. 
    Note that while we received guidance from editors at 'FiveThirtyEight', this 
    package is not officially published by 'FiveThirtyEight'.

For functions that take and return vectors (or scalars), this package provides 8 algorithms for finding fixed point vectors (vectors for which the inputs and outputs to the function are the same vector). These algorithms include Anderson (1965) acceleration <doi:10.1145/321296.321305>, epsilon extrapolation methods (Wynn 1962 <doi:10.2307/2004051>) and minimal polynomial methods (Cabay and Jackson 1976 <doi:10.1137/0713060>).