Thursday, March 13, 2014

Magical Wolfram Language

Examples of what can be done with the knowledge-based Wolfram Language..
Right from Blurring Faces in an Image to Hiding Secret Messages in Images, Make a You-Centric world map.. Do check out the complete list!!

http://www.wolfram.com/language/gallery/

Mathematical Character Curves

Check out to see how various shapes are represented through mathematical equations and inequalities..
We're glad to see that people have been enjoying our mathematical character curves!

http://blog.wolframalpha.com/2013/05/17/making-formulas-for-everything-from-pi-to-the-pink-panther-to-sir-isaac-newton/

Check out how you can play with your favorite cartoon characters using Wolfram Mathematica http://blog.wolframalpha.com/2014/03/11/they-choose-you-pikachu/

Wednesday, March 12, 2014

A Hack to Create Matrices in R, Matlab style!!

The Matlab syntax for creating matrices is pretty and convenient. Its R-counterpart is functional but not as pretty, plus the default is to specify the values column wise. Using meta-programming we can hack together a function that allows us to create matrices in a similar way as in Matlab. Read more at:

http://www.r-bloggers.com/a-hack-to-create-matrices-in-r-matlab-style/

Thursday, March 6, 2014

The Magical Mind of Persi Diaconis

When Diaconis first came to Stanford, he planned to keep his magic background a secret from his academic colleagues.. fearing they wouldn't take seriously a man of hocus-pocus who did research on card shuffling.
Then he stumbled upon a book that described an experiment by the French mathematician Paul Lévy, analyzing the phenomenon known as perfect shuffling - in which a standard deck of cards is carefully shuffled eight times and ends up returning precisely to its starting arrangement. Diaconis says. "I thought, If Paul Lévy can study perfect shuffling, I can say I study perfect shuffling. So I wrote up my work on perfect shuffling, and it got on the front page of The New York Times."

Forecasting weekly data

What would you do if the seasonal period is rather long and non-integer? For example, if you have a weekly data, ARIMA models do not tend to give good results. The simplest approach in such situation is a regression with ARIMA errors. Here is an example using weekly data on US finished motor gasoline products supplied (in thousands of barrels per day) from February 1991 to May 2005.

http://www.r-bloggers.com/forecasting-weekly-data/

Wednesday, March 5, 2014

Beauty is the First Test

"Beauty is the first test; there is no permanent place in the world for ugly mathematics."
- G. H. Hardy

Why Mathematics Is Beautiful and Why It Matters, here is an Huffington Post article.

http://www.huffingtonpost.com/david-h-bailey/why-mathematics-matters_b_4794617.html

No need for SPSS – Now beautiful output in R as well

Many social scientists don't want to move R as it doesn't give a simple table view, just like the SPSS output window. The articles below discuss ways to put the results of certain statistics in HTML tables in R. These tables can be saved to disk or, even better for quick inspection, shown in a web browser or viewer pane... and then R output will be atleast as beautiful as the SPSS output.

Tuesday, March 4, 2014

Photoshop via Clustering

"Do not believe anything: what artists really do is to hang around all day."
-Paco de Lucia
It seems clustering is the new way to Photoshop.. one gets different variations with different no. of clusters..
PS: Don't miss the video link in the end.

Oldies but Goldies: Some Classical Books on Statistical Graphics

The article below highlights some interesting things about three classical books on statistical graphics. The books are old but still relevant and together they give a sense of the development of exploratory graphics in general and the graphics system in R specifically as all three books were written at Bell Labs where the S-language was developed.

Monday, March 3, 2014

Movies and Statistics

It’s Oscars season again, so why shouldn't statisticians enjoy this movie fever...

Here is some number crunching with IMDb data, using R..
http://www.r-bloggers.com/predicting-movie-ratings-with-imdb-data-and-r/

Some tools on predicting Academy Awards..
http://onlinelibrary.wiley.com/doi/10.1111/j.1467-985X.2007.00518.x/abstract