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Move beyond spreadsheets to data mining, forecasting, optimization – and more

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Rick WicklinOctober 8, 2010 4

My previous post on creating a random permutation started me thinking about word games. My wife loves to solve the daily Jumble® puzzle that runs in our local paper. The puzzle displays a string of letters like MLYBOS, and you attempt to unscramble the letters to make an ordinary word.

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Rick WicklinOctober 6, 2010 4

Generating random permutations

I recently read a paper that described a SAS macro to carry out a permutation test. The permutations were generated by PROC IML. (In fact, an internet search for the terms "SAS/IML" and "permutation test" gives dozens of papers in recent years.) The PROC IML code was not as efficient

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Rick WicklinOctober 5, 2010 2

Matrices, eigenvalues, Fibonacci, and the golden ratio

A previous post described a simple algorithm for generating Fibonacci numbers. It was noted that the ratio between adjacent terms in the Fibonacci sequence approaches the "Golden Ratio," 1.61803399.... This post explains why. In a discussion with my fellow blogger, David Smith, I made the comment "any two numbers (at

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Rick WicklinOctober 4, 2010 3

Reading SAS data sets

Often, the first step of a SAS/IML program is to use the USE, READ, and CLOSE statements to read data from a SAS data set into a vector or matrix. There are several ways to read data: Read variables into vectors of the same name. Read one or more variables

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Rick WicklinOctober 1, 2010 1

Using data to define hurricane season

In a previous blog post about hurricanes, I created a histogram of the occurrence of tropical cyclones in the Atlantic basin during the years 1988–2003. That histogram shows that the peak of hurricane activity occurs in the second week of September, but also that a majority of tropical storms occur

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Rick WicklinSeptember 29, 2010 7

Timing Performance: Looping versus LOC-ing

The SAS/IML language is a vector language, so statements that operate on a few long vectors run much faster than equivalent statements that involve many scalar quantities. For example, in a previous post, I asserted that the LOC function is much faster than writing a loop, for finding observations that

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Rick WicklinSeptember 28, 2010 0

Comparing cell phone use by age

The Junk Chart blog discusses a potential problem that can arise in grouped bar charts when the two groups have vastly different ranges. One possible solution (which is discussed at the Junk Chart sister blog, Numbers Rule Your World) is to present the data back-back in what is sometimes called

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Rick WicklinSeptember 27, 2010 23

Extending IML - Defining a Function Module

The SAS/IML run-time library contains hundreds of functions and subroutines that you can call to perform statistical analysis. There are also many functions in Base SAS software that you can call from SAS/IML programs. However, one day you might need to compute some quantity for which there is no prewritten

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Rick WicklinSeptember 24, 2010 1

When is the peak of hurricane season?

Visualizing the distribution of data is a primary task of data analysis. With all the hurricane activity in the Atlantic this year, I’ve been thinking about ways to visualize the historical distribution of hurricane activity. USA Today on Friday, August 13, 2010, announced that "the heart of hurricane season is

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Rick WicklinSeptember 22, 2010 7

Efficient Sampling

Recently, SAS Global Forum announced the call for papers for the 2011 conference to be held at Caesars Palace in Las Vegas. Since the conference is in Las Vegas, I’ve been thinking a lot about games of chance: blackjack, craps, roulette, and the like. You can analyze these games by

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