Search Results: simulation (475)

Reyk Mikles 0
Risikomanagement mit analytischen Methoden

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

Tobias Nittel 0
Industrie 4.0 braucht Big Data !!Analytics!!

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

Rick Wicklin 0
The whys and hows of simulating data

When I told a friend that the title of my new book is Simulating Data with SAS, she asked, “Why would anyone want to simulate data?”  To her, data are measured or surveyed. Data tell us how big, how often, and how many.  Data indicate people’s opinions about politics and

Mike Gilliland 0
Guest Blogger: Len Tashman previews Winter 2013 issue of Foresight

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

Rick Wicklin 0
Remove or keep: Which is faster?

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

Rick Wicklin 0
Constructing common covariance structures

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

Rick Wicklin 0
That distribution is quite PERT!

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

Shelly Goodin 0
SAS authors leaving for Las Vegas

This weekend, lots of SAS authors are going to Las Vegas. The draw is the Analytics 2012 conference. There, several of our authors will lead discussions, including keynote speaker Tim Rey (coauthor of the new SAS Press book Applied Data Mining for Forecasting Using SAS) and Gerhard Svolba (author of

Analytics
Dylan Sweetwood 0
SAS loves math: Kathy Lange

Math and analytics are back “in vogue,” says Kathy Lange, member of the Americas Business Analytics practice at SAS. Since she was little, Kathy has seen the world as one big math problem, and her devotion to mathematics is overwhelmingly clear in this lively interview. Read on below, and be

Dylan Sweetwood 0
SAS loves math: Christian Haxholdt

Christian Haxholdt, an analytics consultant in Global Professional Services and Delivery, has a passion for probability. Originally from Denmark, Christian is a former professor of statistics, and although he no longer teaches, he’s still an avid learner. Read on for his spirited interview, and be sure to check out the

Advanced Analytics | Analytics
Dylan Sweetwood 0
SAS loves math: Tonya Balan

A senior manager in the analytics product management group, Tonya Balan sees herself as a bridge between SAS customers and R&D, ensuring that SAS products stay relevant to the needs of the customer. With a background in statistics and experience as a college professor, Tonya shares her excellent advice and

0
The specifics of analytics in data quality

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

Analytics
Leo Sadovy 0
Having a strategy, versus being strategic

Clarence So, Chief Strategy Officer for Salesforce.com, opened last month’s Chief Strategy Officer Summit in San Francisco (by the IE Group) with a challenging statement: ‘Your strategy is nothing more than the sum of your tactics’.  I found this to be less than satisfactory as an explanation, but considering the

Rick Wicklin 0
The curious case of random eigenvalues

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

1 12 13 14 15 16