Learning Optimization and Machine Learning for Statistics

Getting to the Bottom accompanies the "Getting to the Bottom" optimization methods series at Statisticsviews.com. It contains data and code to reproduce the examples in the articles.


News

gettingtothebottom 3.2

  • Version 3.2: Reverted package to 2.0 state.

gettingtothebottom 3.1

  • Version 3.1: Added functions for the trend filtering example in the 'Getting to the Bottom of Regression Quantiles and Friends with Linear Programming' article.

gettingtothebottom 3.0

  • Functions added for the 'Getting to the Bottom of Quantile Regression with Linear Programming' article.

gettingtothebottom 2.0

  • Functions added for the 'Getting to the Bottom of Matrix Completion and Nonnegative Least Squares with the MM Algorithm' article.

gettingtothebottom 1.0

  • Package release. Functions for the 'Getting to the Bottom of Regression with Gradient Descent' article included.

Reference manual

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install.packages("gettingtothebottom")

3.2 by Jocelyn T. Chi, 3 years ago


http://jocelynchi.com/gettingtothebottom


Browse source code at https://github.com/cran/gettingtothebottom


Authors: Jocelyn T. Chi <jocelynchi@alum.berkeley.edu>


Documentation:   PDF Manual  


MIT + file LICENSE license


Depends on ggplot2, grid, Matrix


See at CRAN