Posts Tagged ‘ Uncategorized ’

Gershgorin discs and the location of eigenvalues

May 22, 2019
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Gershgorin discs and the location of eigenvalues

The eigenvalues of a matrix are not easy to compute. It is remarkable, therefore, that with relatively simple mental arithmetic, you can obtain bounds for the eigenvalues of a matrix of any size. The bounds are provided by using a marvelous mathematical result known as Gershgorin's Disc Theorem. For certain

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Critical values of the Kolmogorov-Smirnov test

May 20, 2019
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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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What is Kolmogorov’s D statistic?

May 15, 2019
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What is Kolmogorov’s D statistic?

Have you ever run a statistical test to determine whether data are normally distributed? If so, you have probably used Kolmogorov's D statistic. Kolmogorov's D statistic (also called the Kolmogorov-Smirnov statistic) enables you to test whether the empirical distribution of data is different than a reference distribution. The reference distribution

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

May 13, 2019
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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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Discrimination, accuracy, and stability in binary classifiers

May 8, 2019
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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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How to simulate data from a generalized linear model

May 6, 2019
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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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Encodings of CLASS variables in SAS regression procedures: A cheat sheet

May 1, 2019
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SAS regression procedures support several parameterizations of classification variables. When a categorical variable is used as an explanatory variable in a regression model, the procedure generates dummy variables that are used to construct a design matrix for the model. The process of forming columns in a design matrix is called

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The normal mixture distribution in SAS

April 29, 2019
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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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