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Rick WicklinMay 26, 2021 1

The running median as a time series smoother

When data contain outliers, medians estimate the center of the data better than means do. In general, robust estimates of location and sale are preferred over classical moment-based estimates when the data contain outliers or are from a heavy-tailed distribution. Thus, instead of using the mean and standard deviation of

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Analytics | Learn SAS

Rick WicklinMay 17, 2021 0

Standardized regression coefficients in PROC GLIMMIX

I previously wrote about how to understand standardized regression coefficients in PROC REG in SAS. You can obtain the standardized estimates by using the STB option on the MODEL statement in PROC REG. Several readers have written to ask whether I could write a similar article about the STDCOEF option

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Analytics | Learn SAS | Programming Tips

Rick WicklinMay 12, 2021 2

Nonstandard ways to standardize variables

You can standardize a numerical variable by subtracting a location parameter from each observation and then dividing by a scale parameter. Often, the parameters depend on the data that you are standardizing. For example, the most common way to standardize a variable is to subtract the sample mean and divide

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Analytics | Learn SAS

Rick WicklinMay 3, 2021 0

Examples of using the Hoeffding D statistic

A previous article discusses the definition of the Hoeffding D statistic and how to compute it in SAS. The letter D stands for "dependence." Unlike the Pearson correlation, which measures linear relationships, the Hoeffding D statistic tests whether two random variables are independent. Dependent variables have a Hoeffding D statistic

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Analytics | Programming Tips

Rick WicklinApril 28, 2021 1

Compute the Hoeffding D statistic in SAS

There are many statistics that measure whether two continuous random variables are independent or whether they are related to each other in some way. The most well-known statistic is Pearson's correlation, which is a parametric measure of the linear relationship between two variables. A related measure is Spearman's rank correlation,

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Analytics | Learn SAS

Rick WicklinApril 21, 2021 0

Compute bivariate ranks

Ranking is a fundamental concept in statistics. Ranks of univariate data are used by statisticians to estimate statistics such as percentiles (quantiles) and empirical distributions. A more advanced use is to compute various rank-based measures of correlation or association between pairs of variables. For example, ranks are used to compute

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Analytics | Learn SAS

Rick WicklinApril 19, 2021 5

Compute tied ranks

The ranks of a set of data values are used in many nonparametric statistics and statistical tests. When you request a statistic or nonparametric test in SAS, the procedure will automatically compute the ranks that are needed. However, sometimes it is useful to know how to compute the ranks yourself.

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Analytics | Programming Tips

Rick WicklinApril 7, 2021 2

Double integrals by using Monte Carlo methods

As mentioned in my article about Monte Carlo estimate of (one-dimensional) integrals, one of the advantages of Monte Carlo integration is that you can perform multivariate integrals on complicated regions. This article demonstrates how to use SAS to obtain a Monte Carlo estimate of a double integral over rectangular and

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Analytics | Programming Tips

Rick WicklinApril 5, 2021 2

Sample size for the Monte Carlo estimate of an integral

A previous article shows how to use Monte Carlo simulation to estimate a one-dimensional integral on a finite interval. A larger random sample will (on average) result in an estimate that is closer to the true value of the integral than a smaller sample. This article shows how you can

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Analytics | Programming Tips

Rick WicklinMarch 31, 2021 5

Estimate an integral by using Monte Carlo simulation

Numerical integration is important in many areas of applied mathematics and statistics. For one-dimensional integrals on the interval (a, b), SAS software provides two important tools for numerical integration: For common univariate probability distributions, you can use the CDF function to integrate the density, thus obtaining the probability that a

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