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We’re Making Movies
Well, more like voice-over PowerPoint presentations. As you know, we’ve put some focus on producing short videos that highlight various aspects of the analytical software this year, and we’ve got a new batch for you. The idea is to expose you to new capabilities and useful applications without your having to invest a lot of time. Please let us know what you think about them.
I am just back from NESUG (NorthEast SAS Users Group) in Baltimore where I enjoyed talking to the audiences at my two presentations and two demos, as well as to the audience at the Spotlight on SAS panel discussion. That ends the regional conferences for the year, which I hope some of you attended. I also hope you benefited from (and subscribed to) this newsletter! Best wishes to those readers in the Northeast who were affected by Hurricane Sandy.
Maura
Senior R&D Director, Statistical Applications
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Video Portal for Information about SAS® Analytical Software »
Check out this growing video portal for short presentations that range from what's new in recent releases, to applications of new procedures such as PROC FMM for mixture models, to new features in SAS/ETS®, to working with SAS® Simulation Studio. More presentations are on their way.
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Ambassador Kit for SAS/STAT® 12.1 Now Ready »
You can use the ambassador kit to promote the use of the latest version of SAS/STAT® software in your organization. This zip file includes the same PowerPoint presentation seen on the video portal, notes for the presentation, a single-page handout that describes the new capabilities, and the associated SAS® Global Forum paper from the 2012 conference.
We're starting to see a good number of sites updating to the 12.1 releases of the analytical products (available in the same installation as SAS 9.3M2) and hope to see that continue. Remember, while Base SAS® remains at 9.3, and the latest version is 9.3M2 (for the latest maintenance release), SAS/STAT is updated from SAS/STAT 9.3 to SAS/STAT 12.1
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New Web Example on Fitting Zero-Inflated Count Data Models with PROC GENMOD »
This example shows you how to fit zero-inflated Poisson and negative binomial models to count data. It also discusses several graphs that are useful for descriptive and diagnostic purposes, and it also shows you how to compute the estimated probabilities and the relative frequencies of the observed counts and generate comparative plots. Note that the new FMM procedure for finite mixture models also provides both these models and the hurdle model.
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Using the EFFECT Statement in SAS/STAT® Linear Modeling Procedures »
The EFFECT statement enables you to construct special collections of columns for design matrices. These collections are called constructed effects to distinguish them from the usual model effects that are formed from continuous or classification variables. You can define an effect such as a spline, polynomial, lag, or multimember classification effect and use that in your MODEL statement. This video provides you with the basics of using the EFFECT statement.
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Monitoring the Variation in Your Multivariate Process: An Introduction to the MVP Procedures »
Complex processes in modern manufacturing and business environments can generate hundreds and even thousands of process measurements that vary over time. Early detection of process instability is critical for avoiding costly failures and minimizing risk. When the process measurements are correlated, multivariate statistical process monitoring methods are appropriate. Three new procedures in SAS/QC® 12.1, the MVPMODEL, MVPMONITOR, and MVPDIAGNOSE procedures, implement methods that are based on a principal components approach to process monitoring, which was developed in the field of chemometrics. They provide T
2 and SPE charts, which are multivariate summaries of process variation. An example from social media sentiment analysis illustrates how the procedures work together and demonstrates the power of the methods for discovering and diagnosing unusual variation.
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Specify Colors in SAS® Statistical Graphics Procedures »
This article from Rick Wicklin's The Do Loop blog shows how to use color names and RGB colors to specify colors in the SAS statistical graphics procedures, such as PROC SGPLOT. It gathers together color resources in a single location, so you might want to bookmark this article for future reference.
Another interesting post from Wicklin’s blog has to do with acceptance-rejection simulation. Wicklin discusses how to simulate data from a truncated Poisson distribution.
You might also be interested in returning multiple values from a SAS/IML® function.
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SAS Global Forum 2013 »
It’s never too early to plan for SAS Global Forum 2013, which is being held in San Francisco from April 28 to May 1. We’ll be teaching the following statistical tutorials on Sunday, April 28:
- Modeling Categorical Response Data … Maura Stokes
- Model Selection with SAS/STAT Software … Funda Gunes
- Introduction to the MCMC Procedure in SAS/STAT Software …. Fang Chen
- Creating Statistical Graphics in SAS …. Warren Kuhfeld
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Pearson goodness of fit test when parameters are estimated »
The Pearson goodness of fit test provides a test of the fit of a distribution or model to the observed values of a variable. The test compares the expected values from the distribution or model to the observed values. For a categorical variable, the comparison is done at each of its levels, but the fit to a continuous variable can also be tested if it is categorized. The Pearson test statistic is approximately chi-square distributed with k-1 degrees of freedom, where k is the number of categories. However, when parameters of the fitting distribution or model must be estimated, the degrees of freedom of the test statistic must be decreased by the number of estimated parameters. This example shows how to proceed.
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