Tag: Statistical Programming

Analytics | Learn SAS
Rick Wicklin 0
Principal component regression in SAS

A common question on discussion forums is how to compute a principal component regression in SAS. One reason people give for wanting to run a principal component regression is that the explanatory variables in the model are highly correlated which each other, a condition known as multicollinearity. Although principal component

Data Visualization | Learn SAS
Rick Wicklin 0
The path of zip codes

Toe bone connected to the foot bone, Foot bone connected to the leg bone, Leg bone connected to the knee bone,...              — American Spiritual, "Dem Bones" Last week I read an interesting article on Robert Kosara's data visualization blog. Kosara connected the geographic centers of the US zip codes in

Analytics | Programming Tips
Rick Wicklin 0
Quadratic optimization in SAS

At SAS Global Forum last week, I saw a poster that used SAS/IML to optimized a quadratic objective function that arises in financial portfolio management (Xia, Eberhardt, and Kastin, 2017). The authors used the Newton-Raphson optimizer (NLPNRA routine) in SAS/IML to optimize a hypothetical portfolio of assets. The Newton-Raphson algorithm

Programming Tips
Rick Wicklin 0
Print tables in SAS/IML

One of the advantages of the new mixed-type tables in SAS/IML 14.2 (released with SAS 9.4m4) is the greatly enhanced printing functionality. You can control which rows and columns are printed, specify formats for individual columns, and even use templates to completely customize how tables are printed. Printing a table

Advanced Analytics
Rick Wicklin 0
Loess regression in SAS/IML

A previous post discusses how the loess regression algorithm is implemented in SAS. The LOESS procedure in SAS/STAT software provides the data analyst with options to control the loess algorithm and fit nonparametric smoothing curves through points in a scatter plot. Although PROC LOESS satisfies 99.99% of SAS users who

Rick Wicklin 0
Simulate data from a generalized Gaussian distribution

Although statisticians often assume normally distributed errors, there are important processes for which the error distribution has a heavy tail. A well-known heavy-tailed distribution is the t distribution, but the t distribution is unsuitable for some applications because it does not have finite moments (means, variance,...) for small parameter values.

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