Mathematica vs. R

In brief

This repository has example projects, code, and documents for comparing
Mathematica with
R.

Mission statement

The development in this code repository aims to provide a collection
of relatively simple but non-trivial example projects that illustrate
the use of Mathematica and R in different statistical, machine
learning, scientific, and software engineering programming activities.

Each of the projects has implementations and documents made with both
Mathematica and R -- hopefully that would allow comparison and
knowledge transfer.

License matters

All code files and executable documents are with the license GPL 3.0.
For details see http://www.gnu.org/licenses/ .

All documents are with the license Creative Commons Attribution 4.0
International (CC BY 4.0). For details see
https://creativecommons.org/licenses/by/4.0/ .

Projects organization

Each project has an introductory page (README.md) that lists the
project goals, concrete steps, and links to documents and scripts with
full explanations and code.

Generally, an introductory page would also have sections with comparison
observations and development history.

Each project (generally) has two directories named "Mathematica" and
"R" that have corresponding documents and code.

Since Mathematica ships with R some projects would have only a
Mathematica-centric exposition of combining Mathematica and R
outputs into one Mathematica notebook.

Some projects have only Mathematica parts or only R parts. This is because
there are no equivalent counter-parts.

There is an attempt the corresponding Mathematica and R codes to be
very close in structure and steps flow. Often enough the structure and
flow would be different because each programming language would make certain
particular techniques easier to apply or because of certain language idioms.

Where to begin

This presentation,
"Mathematica vs. R"
given at the
Wolfram Technology Conference 2015
is probably a good start.

This presentation, "Mathematica vs. R–Advanced Use Cases"
was given at
Wolfram Technology Conference 2016. Here are recorded videos:

• YouTube : https://www.youtube.com/watch?v=NKpeOKxCUl4 .

• Wolfram Research : http://www.wolfram.com/broadcast/video.php?v=1745 .

As a warm-up of how to do the comparison see this mind-map (which is
made for Mathematica users):

Projects overview

Abbreviations table

Abbreviation	Definition		Abbreviation	Definition
ARL	Association rules learning		NA	numerical analysis
BofW	bag of words (model)		NLP	natural language processing
Cl	(machine learning) classification		Opt	optimization
DA	data analysis		Outl	outliers
DIng	data ingestion		Par	parallel computing
Distr	distributions of variables		QR	quantile regression
DWrang	data wrangling		Rgr	regression
GoF	goodness of fit		RLink	Mathematica's RLink
Gr	graphs		ROC	receiver operating characteristic
HPC	High Performance Computing		Sim	simulation(s)
Img	image processing		Str	strings patterns and manipulation
IUI	interactive user interface(s)		TS	time series
LSA	latent semantic analysis		Vis	visualization
MF	matrix factorization(s)

Projects overview table

In the following table the projects in italics are partially completed --
they have only a Mathematica or an R part.

Project	ARL	BofW	Cl	DA	DIng	Distr	DWrang	GoF	Gr	Img	IUI	Rgr	LSA	MF	NA	NLP	Opt	Outl	Par	QR	RLink	ROC	Sim	Str	TS	Vis
BrowsingDataWithChernoffFaces				X	X	X	X											X								X
DataWrangling				X	X		X																			X
DeepLearningExamples				X	X		X																			X
DistributionExtractionAFromGaussianNoisedMixture						X		X									X
HandwrittenDigitsClassificationByMatrixFactorization			X		X					X			X	X					X							X
ODEsWithSeasonalities											X				X								X			X
ProgressiveJackpotModeling						X																	X
ProgressiveMachineLearning			X		X																	X
RegressionWithROC			X									X										X				X
StatementsSaliencyInPodcasts		X			X						X					X								X
TextAnalysisOfTrumpTweets	X	X	X	X	X		X														X			X		X
TimeSeriesAnalysisWithQuantileRegression				X	X													X		X					X	X

Future projects

The future projects are listed in order of their completion time
proximity -- the highest in the list would be committed the soonest.

• Personal banking data obfuscation

• Independent Component Analysis (ICA) programming and basic applications

• Prefix trees (tries) programming and basic applications

• High Performance Computing (HPC) projects -- Spark, H2O, etc.

• Comparison of PCA, NNMF, and ICA over image de-noising

• Informal verification of time series co-dependency

• Functional parsers programming and basic applications

• Recommendation engines

• Lebesgue numerical integration

• Conversational engines

Mathematica's RLink

For more information about Mathematica's RLink
see

• the YouTube video "RLink: Linking Mathematica and R",

• the set-up web page guide Setting up RLink for Mathematica.