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Rick WicklinSeptember 21, 2020 0

Regression with inequality constraints on parameters

A previous article discussed how to solve regression problems in which the parameters are constrained to be a specified constant (such as B1 = 1) or are restricted to obey a linear equation such as B4 = –2*B2. In SAS, you can use the RESTRICT statement in PROC REG to

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Analytics | Programming Tips

Rick WicklinSeptember 16, 2020 1

Restricted least squares regression in SAS

A data analyst recently asked a question about restricted least square regression in SAS. Recall that a restricted regression puts linear constraints on the coefficients in the model. Examples include forcing a coefficient to be 1 or forcing two coefficients to equal each other. Each of these problems can be

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Analytics | Programming Tips

Rick WicklinSeptember 10, 2020 0

Iterative proportional fitting in SAS

I previously wrote about the RAS algorithm, which is a simple algorithm that performs matrix balancing. Matrix balancing refers to adjusting the cells of a frequency table to match known values of the row and column sums. Ideally, the balanced matrix will reflect the structural relationships in the original matrix.

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Analytics | Programming Tips

Rick WicklinSeptember 8, 2020 1

Matrix balancing: Update matrix cells to match row and column sums

Matrix balancing is an interesting problem that has a long history. Matrix balancing refers to adjusting the cells of a frequency table to match known values of the row and column sums. One of the early algorithms for matrix balancing is known as the RAS algorithm, but it is also

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Analytics | Data Visualization | Learn SAS

Rick WicklinJuly 1, 2020 4

Pooled, within-group, and between-group covariance matrices

A previous article discusses the pooled variance for two or groups of univariate data. The pooled variance is often used during a t test of two independent samples. For multivariate data, the analogous concept is the pooled covariance matrix, which is an average of the sample covariance matrices of the

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Analytics | Programming Tips

Rick WicklinJune 24, 2020 2

The Kolmogorov D distribution and exact critical values

If you have ever run a Kolmogorov-Smirnov test for normality, you have encountered the Kolmogorov D statistic. The Kolmogorov D statistic is used to assess whether a random sample was drawn from a specified distribution. Although it is frequently used to test for normality, the statistic is "distribution free" in

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Analytics

Rick WicklinJune 8, 2020 0

Interactions with spline effects in regression models

A SAS customer asked how to specify interaction effects between a classification variable and a spline effect in a SAS regression procedure. There are at least two ways to do this. If the SAS procedure supports the EFFECT statement, you can build the interaction term in the MODEL statement. For

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Analytics | Learn SAS

Rick WicklinJune 3, 2020 3

How to estimate the difference between percentiles

I recently read an article that describes ways to compute confidence intervals for the difference in a percentile between two groups. In Eaton, Moore, and MacKenzie (2019), the authors describe a problem in hydrology. The data are the sizes of pebbles (grains) in rivers at two different sites. The authors

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Analytics | Data Visualization

Rick WicklinMay 13, 2020 3

Find points where a regression curve has zero slope

This article shows how to find local maxima and maxima on a regression curve, which means finding points where the slope of the curve is zero. An example appears at the right, which shows locations where the loess smoother in a scatter plot has local minima and maxima. Except for

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Analytics | Programming Tips

Rick WicklinMay 11, 2020 0

Cubic spline interpolation in SAS

I recently showed how to use linear interpolation in SAS. Linear interpolation is a common way to interpolate between a set of planar points, but the interpolating function (the interpolant) is not smooth. If you want a smoother interpolant, you can use cubic spline interpolation. This article describes how to

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