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Rick WicklinJune 12, 2019 5

Leave-one-out statistics and a formula to update a matrix inverse

For linear regression models, there is a class of statistics that I call deletion diagnostics or leave-one-out statistics. These observation-wise statistics address the question, "If I delete the i_th observation and refit the model, what happens to the statistics for the model?" For example: The PRESS statistic is similar to

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Learn SAS | Programming Tips

Rick WicklinJune 10, 2019 16

5 reasons to use PROC FORMAT to recode variables in SAS

Recoding variables can be tedious, but it is often a necessary part of data analysis. Almost every SAS programmer has written a DATA step that uses IF-THEN/ELSE logic or the SELECT-WHEN statements to recode variables. Although creating a new variable is effective, it is also inefficient because you have to

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Data Visualization | Learn SAS | Programming Tips

Rick WicklinJune 5, 2019 2

Plot a family of curves in SAS

A family of curves is generated by an equation that has one or more parameters. To visualize the family, you might want to display a graph that overlays four of five curves that have different parameter values, as shown to the right. The graph shows members of a family of

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Data Visualization | Learn SAS | Programming Tips

Rick WicklinJune 3, 2019 5

Graph wide data and long data in SAS

Statistical programmers and analysts often use two kinds of rectangular data sets, popularly known as wide data and long data. Some analytical procedures require that the data be in wide form; others require long form. (The "long format" is sometimes called "narrow" or "tall" data.) Fortunately, the statistical graphics procedures

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Analytics | Programming Tips

Rick WicklinMay 28, 2019 2

The Theil-Sen robust estimator for simple linear regression

Modern statistical software provides many options for computing robust statistics. For example, SAS can compute robust univariate statistics by using PROC UNIVARIATE, robust linear regression by using PROC ROBUSTREG, and robust multivariate statistics such as robust principal component analysis. Much of the research on robust regression was conducted in the

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Analytics | Programming Tips

Rick WicklinMay 20, 2019 6

Critical values of the Kolmogorov-Smirnov test

Recently I wrote about how to compute the Kolmogorov D statistic, which is used to determine whether a sample has a particular distribution. One of the beautiful facts about modern computational statistics is that if you can compute a statistic, you can use simulation to estimate the sampling distribution of

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Learn SAS | Programming Tips

Rick WicklinMay 13, 2019 0

Write to a SAS data set from inside a SAS/IML loop

In SAS/IML programs, a common task is to write values in a matrix to a SAS data set. For some programs, the values you want to write are in a matrix and you use the CREATE FROM/APPEND FROM syntax to create the data set, as follows: proc iml; X =

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Analytics | Programming Tips

Rick WicklinMay 8, 2019 3

Discrimination, accuracy, and stability in binary classifiers

At SAS Global Forum 2019, Daymond Ling presented an interesting discussion of binary classifiers in the financial industry. The discussion is motivated by a practical question: If you deploy a predictive model, how can you assess whether the model is no longer working well and needs to be replaced? Daymond

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Analytics | Programming Tips

Rick WicklinMay 6, 2019 1

How to simulate data from a generalized linear model

Here's a simulation tip: When you simulate a fixed-effect generalized linear regression model, don't add a random normal error to the linear predictor. Only the response variable should be random. This tip applies to models that apply a link function to a linear predictor, including logistic regression, Poisson regression, and

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Learn SAS | Programming Tips

Rick WicklinApril 29, 2019 4

The normal mixture distribution in SAS

Did you know that SAS provides built-in support for working with probability distributions that are finite mixtures of normal distributions? This article shows examples of using the "NormalMix" distribution in SAS and describes a trick that enables you to easily work with distributions that have many components. As with all

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