As I wrote in my previous post, a SAS customer noticed that he was getting some duplicate values when he used the RAND function to generate a large number of random uniform values on the interval [0,1]. He wanted to know if this result indicates a bug in the RAND
Tossing dice is a simple and familiar process, yet it can illustrate deep and counterintuitive aspects of random numbers. For example, if you toss four identical six-sided dice, what is the probability that the faces are all distinct, as shown to the left? Many people would guess that the probability
Mit welchen IT-Innovationen können Finanzdienstleister Ihre größten Herausforderungen (Regulierung, Risikoanalyse, Unternehmensarchitektur) nachhaltig unterstützen? Hier sehe ich vor allem: Schlanker werden durch Industrialisierung, indem die zahllosen Silostrukturen abgebaut werden, die eine integrierte Steuerung behindern! Die Industrialisierung dieser Strukturen - ähnlich der Plattformstrategien in der Automobilindustrie - führen zu enormen Effizienzgewinnen, einer
Echtzeit? Den Algo-Tradern wird das jetzt ein Lächeln auf die Lippen zaubern. Natürlich rede ich in diesem Zusammenhang nicht über Milli- oder Mikrosekunden, aber über Antwortzeiten die für einen Fachanwender akzeptabel sind, um interaktiv mit einer analytischen Applikation zu arbeiten. In diesem Fall darf sich nämlich eine solche Anwendung schon
Schnell erkennen, schnell handeln und schnell vorankommen bietet schon einige Vorteile. Aber wir sollten uns davor schützen, schnell in die falsche Richtung zu rennen. Mir fällt hierzu das Bild des Marathonläufers ein, der in führender Position die falsche Abzweigung nimmt. Das Attribut „schnell“ alleine reicht also nicht aus. Intelligenz ist
A SAS customer asks: How do I use SAS to generate multiple samples of size N from a multivariate normal distribution? Suppose that you want to simulate k samples (each with N observations) from a multivariate normal distribution with a given mean vector and covariance matrix. Because all of the
There is something for everyone at SAS Global Forum 2013. I like to attend presentations in the Statistics and Data Analysis track and talk with SAS customers in the SAS Support and Demo Area. But one activity that I enjoy the most is to stroll through the poster area and
Editor Len Tashman's Preview of Foresight Foresight has always presented its methods-based articles as either tutorials, which introduce and illustrate a methodology in nontechnical language, or as case studies, with a focus on the practical issues and challenges in generating forecasts. We lead off this issue with two practical issues articles. First, Stephan
A while ago I saw a blog post on how to simulate Bernoulli outcomes when the probability of generating a 1 (success) varies from observation to observation. I've done this often in SAS, both in the DATA step and in the SAS/IML language. For example, when simulating data that satisfied
I am pleased to announce that this year at SAS Global Forum 2013 (San Francisco, April 27 to May 1, 2013) I am giving a free hands-on workshop (HOW) entitled "Getting Started with the SAS/IML Language." If you are not familiar with the very popular Hands-On Workshop series at SAS
It's the start of a new year. Have you made a resolution to be a better data analyst? A better SAS statistical programmer? To learn more about multivariate statistics? What better way to start the New Year than to read (or re-read!) the top 12 articles for statistical programmers from
In a recent article on efficient simulation from a truncated distribution, I wrote some SAS/IML code that used the LOC function to find and exclude observations that satisfy some criterion. Some readers came up with an alternative algorithm that uses the REMOVE function instead of subscripts. I remarked in a
I recently encountered a SUGI30 paper by Chuck Kincaid entitled "Guidelines for Selecting the Covariance Structure in Mixed Model Analysis." I think Kincaid does a good job of describing some common covariance structures that are used in mixed models. One of the many uses for SAS/IML is as a language
There are a lot of useful probability distributions that are not featured in standard statistical textbooks. Some of them have distinctive names. In the past year I have had contact with SAS customers who use the Tweedie distribution, the slash distribution, and the PERT distribution. Often these distributions are used
It's not too early to think about what presentations and pre-conference training to attend while at SAS Global Forum 2012. Tutorials are an extra-fee that is only available as additions to a conference registration. But you can get a deal: Registration package 3 includes your choice of one Sunday Pre-Conference Tutorial.
Congratulations to all of these winners in the MWSUG Best Contibuted Papers! I hope you have all submitted your papers to the 2013 SAS Global Forum. The deadline for submissions ends soon! Here's a list that I know you have all been waiting for:
I was recently flipping through Ross' Simulation (2006, 4th Edition) and saw the following exercise: Let N be the minimum number of draws from a uniform distribution [until the sum of the variates]exceeds 1. What is the expected value of N? Write a simulation to estimate the expected value. For
If you use a word three times, it's yours. -Unknown When I was a child, my mother used to encourage me to increase my vocabulary by saying, "If you use a word three times, it's yours for life." I believe that the same saying holds for programming techniques: Use a
This article is an excerpt from my forthcoming book Simulating Data with SAS. Not every matrix with 1 on the diagonal and off-diagonal elements in the range [–1, 1] is a valid correlation matrix. A correlation matrix has a special property known as positive semidefiniteness. All correlation matrices are positive
I've been working on a new book about Simulating Data with SAS. In researching the chapter on simulation of multivariate data, I've noticed that the probability density function (PDF) of multivariate distributions is often specified in a matrix form. Consequently, the multivariate density can usually be computed by using the
We just published Gerhard Svolba’s Data Quality for Analytics Using SAS. When I first heard about it, I thought we’d have a tome covering such topics as standardizing data, cleaning it up, removing duplicates, and so on. However, as Gerhard says in his Introduction, “There are many aspects of data
I've been a fan of statistical simulation and other kinds of computer experimentation for many years. For me, simulation is a good way to understand how the world of statistics works, and to formulate and test conjectures. Last week, while investigating the efficiency of the power method for finding dominant
The April 2012 issue of ORMS Today contains a piece on "How analytics enhance the guest experience at Walt Disney World," by Pete Buczkowski and Hai Chu. While many of us are used to forecasting just one or two things (such as unit sales or revenue), Pete and Hai illustrate
I blog about a lot of topics, but the following five categories represent some of my favorite subjects. Judging by the number of readers and comments, these articles have struck a chord with SAS users. If you haven't read them, check them out. (If you HAVE read them, some are
The birthday matching problem is a classic problem in probability theory. The part of it that people tend to remember is that in a room of 23 people, there is greater than 50% chance that two people in the room share a birthday. But the birthday matching problem is also
The topic of cluster groups comes up often. By cluster group I am referring to the feature in bar charts where the group values are displayed side by side. With SAS 9.3, SG Procedures support stack or cluster grouping for Bar Charts and overlay or cluster grouping for all other
In a previous post I showed how to implement Stewart's (1980) algorithm for generating random orthogonal matrices in SAS/IML software. By using the algorithm, it is easy to generate a random matrix that contains a specified set of eigenvalues. If D = diag(λ1, ..., λp) is a diagonal matrix and
Because I am writing a new book about simulating data in SAS, I have been doing a lot of reading and research about how to simulate various quantities. Random integers? Check! Random univariate samples? Check! Random multivariate samples? Check! Recently I've been researching how to generate random matrices. I've blogged
SAS Global Forum 2012 is right around the corner. If you will be in Orlando, too, be sure to say hello! If you have ideas for improving SAS/IML software or you would like to discuss my blog, please visit me during my hours at the SAS/IML booth in the Demo
After my post on detecting outliers in multivariate data in SAS by using the MCD method, Peter Flom commented "when there are a bunch of dimensions, every data point is an outlier" and remarked on the curse of dimensionality. What he meant is that most points in a high-dimensional cloud
