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Advanced Analytics | Learn SAS | Programming Tips

Rick WicklinAugust 17, 2020 2

Estimate a power curve in parallel in SAS Viya

I recently showed how to use simulation to estimate the power of a statistical hypothesis test. The example (a two-sample t test for the difference of means) is a simple SAS/IML module that is very fast. Fast is good because often you want to perform a sequence of simulations over

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Advanced Analytics | Machine Learning | Programming Tips

Rick WicklinJuly 23, 2020 11

Fit a multivariate Gaussian mixture model by using the expectation-maximization (EM) algorithm

Last month a SAS programmer asked how to fit a multivariate Gaussian mixture model in SAS. For univariate data, you can use the FMM Procedure, which fits a large variety of finite mixture models. If your company is using SAS Viya, you can use the MBC or GMM procedures, which

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Advanced Analytics | Programming Tips

Rick WicklinJuly 15, 2020 1

How to evaluate the multivariate normal log likelihood

The multivariate normal distribution is used frequently in multivariate statistics and machine learning. In many applications, you need to evaluate the log-likelihood function in order to compare how well different models fit the data. The log-likelihood for a vector x is the natural logarithm of the multivariate normal (MVN) density

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Advanced Analytics | Learn SAS | Programming Tips

Architecture of an MPP session in SAS Viya. The client calls an action, which can use multiple nodes and threads.

Rick WicklinJune 17, 2020 0

Write a CAS data table by using the iml action

A previous article shows how to use the iml action to read a CAS data table into an IML matrix. This article shows how to write a CAS table from data in an IML matrix. You can read an overview of the iml action, which was introduced in SAS Viya

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Advanced Analytics | Learn SAS | Programming Tips

Rick WicklinJune 15, 2020 5

Read a CAS data table by using the iml action

A previous article compares a SAS/IML program that runs in PROC IML to the same program that runs in the iml action. (You can read an overview of the iml action.) The example in the previous article was very simple and did not read or write data. This article compares

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Advanced Analytics | Machine Learning

Rick WicklinJune 1, 2020 0

The Kullback–Leibler divergence between continuous probability distributions

In a previous article, I discussed the definition of the Kullback-Leibler (K-L) divergence between two discrete probability distributions. For completeness, this article shows how to compute the Kullback-Leibler divergence between two continuous distributions. When f and g are discrete distributions, the K-L divergence is the sum of f(x)*log(f(x)/g(x)) over all

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Advanced Analytics | Machine Learning

Rick WicklinMay 28, 2020 1

Minimizing the Kullback–Leibler divergence

The Kullback–Leibler divergence is a measure of dissimilarity between two probability distributions. An application in machine learning is to measure how distributions in a parametric family differ from a data distribution. This article shows that if you minimize the Kullback–Leibler divergence over a set of parameters, you can find a

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Advanced Analytics | Machine Learning

Rick WicklinMay 26, 2020 0

The Kullback–Leibler divergence between discrete probability distributions

If you have been learning about machine learning or mathematical statistics, you might have heard about the Kullback–Leibler divergence. The Kullback–Leibler divergence is a measure of dissimilarity between two probability distributions. It measures how much one distribution differs from a reference distribution. This article explains the Kullback–Leibler divergence and shows

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Advanced Analytics | Data Visualization | Programming Tips

Rick WicklinMarch 9, 2020 2

ROC curves for a binormal sample

In a previous article, I discussed the binormal model for a binary classification problem. This model assumes a set of scores that are normally distributed for each population, and the mean of the scores for the Negative population is less than the mean of scores for the Positive population. I

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Advanced Analytics | Data Visualization

Rick WicklinJanuary 15, 2020 8

The moment-ratio diagram

In my book Simulating Data with SAS, I show how to use a graphical tool, called the moment-ratio diagram, to characterize and compare continuous probability distributions based on their skewness and kurtosis (Wicklin, 2013, Chapter 16). The idea behind the moment-ratio diagram is that skewness and kurtosis are essential for

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