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gettingtothebottom (version 2.0)

Getting to the Bottom, A Package for Learning Optimization Methods

Description

Getting to the Bottom is a companion package for the "Getting to the Bottom" optimization methods series at Statisticsviews.com. The package contains data and code to reproduce the examples in the articles.

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Version

Install

install.packages('gettingtothebottom')

Monthly Downloads

1

Version

2.0

License

CC BY-NC-SA 3.0

Maintainer

Jocelyn Chi

Last Published

March 11th, 2014

Functions in gettingtothebottom (2.0)

plot_solutionpaths

MM Algorithm - Plot results of solutionpaths function
plot_nnm

MM Algorithm - Plot NNM
plot_nnm_truth

MM Algorithm - Plotting the True Signal
plot_spect

MM Algorithm - Plotting the Spectroscopic Signal
plot_solpaths_error

MM Algorithm - Function for plotting the imputed values against the truth for minimum error solution
plot_loss

Gradient Descent Algorithm - Plotting the Loss Function
makeLambdaseq

MM Algorithm - Function for making sequence of lambdas for solution paths
makeOmega

MM Algorithm - Generate Omega
baltimoreyouth

Baltimore Youth Indicators - 2010 and 2011
plot_nnm_obj

MM Algorithm - Plot NNM Objective
generate_nnm

Generate random nonnegative mixture components
plot_softhreshold

MM Algorithm - Plot the Softhreshold Function
testmatrix

MM Algorithm - Generate Test Matrix
example.alpha

Gradient Descent Algorithm - Plots Depicting Gradient Descent Results in Example 1 Using Different Choices for the Step Size
movieratings

Movie ratings database derived from data from IMDB.com
plot_nnm_reconstruction

MM Algorithm - Plotting the Reconstruction
plot_gradient

Gradient Descent Algorithm - Plotting the Gradient Function
plot_nnm_coef

MM Algorithm - Plotting the NNMLS regression coefficients
plot_iterates

Gradient Descent Algorithm - Plotting the Iterates
matrixcomplete

MM Algorithm - Matrix Completion
example.quadratic.approx

Gradient Descent Algorithm - Plots Depicting How Different Choices of Alpha Result in Differing Quadratic Approximations
gdescent

Gradient Descent Algorithm
makeZ

MM Algorithm - Make Z
nnls_mm

Nonnegative Least Squares via MM
makeY

MM Algorithm - Make Y
solutionpaths

MM Algorithm - Find the best fit lambda for a given problem based on an initial guess for lambda
init.lambda

MM Algorithm - Initial lambda
gettingtothebottom

gettingtothebottom
moviebudgets

Movie ratings and budget database derived from data from IMDB.com
softhreshold

MM Algorithm - Softhreshold Function
diff_norm

MM Algorithm - Normed Difference