Rick Wicklin, PhD, is a distinguished researcher in computational statistics at SAS and is a principal developer of SAS/IML software. His areas of expertise include computational statistics, simulation, statistical graphics, and modern methods in statistical data analysis. Rick is author of the books Statistical Programming with SAS/IML Software and Simulating Data with SAS.
I've written many articles about bootstrapping in SAS, including several about bootstrapping in regression models. Many of the articles use a very general bootstrap method that can bootstrap almost any statistic that SAS can compute. The method uses PROC SURVEYSELECT to generate B bootstrap samples from the data, uses the
It has been more than a decade since SAS 9.3 changed the default ODS destination from the old LISTING destination to more modern destinations such as HTML. One of the advantages of modern output destinations is support for Unicode symbols, superscripts, subscripts, and for formatting text by using boldface, italics,
In ordinary least squares regression, there is an explicit formula for the confidence limit of the predicted mean. That is, for any observed value of the explanatory variables, you can create a 95% confidence interval (CI) for the predicted response. This formula assumes that the model is correctly specified and
A SAS programmer wanted to use PROC SGPLOT in SAS to visualize a regression model. The programmer wanted to visualize confidence limits for the predicted mean at certain values of the explanatory variable. This article shows two options for adding confidence limits to a scatter plot. You can use a
The acceptance-rejection method (sometimes called rejection sampling) is a method that enables you to generate a random sample from an arbitrary distribution by using only the probability density function (PDF). This is in contrast to the inverse CDF method, which uses the cumulative distribution function (CDF) to generate a random
There are dozens of common probability distributions for a continuous univariate random variable. Familiar examples include the normal, exponential, uniform, gamma, and beta distributions. Where did these distributions come from? Well, some mathematician needed a model for a stochastic process and wrote down the equation for the distribution, typically by
Let X be any rectangular matrix. What is the trace of the crossproducts matrix, X'*X? Interestingly, you do not need to form the crossproducts matrix to compute the answer! It turns out that tr(X'*X) equals the sum of the squared elements of X. Theorem: For any matrix, X, the trace
In a previous article, I discussed the Wilcoxon signed rank test, which is a nonparametric test for the location of the median. The Wikipedia article about the signed rank test mentions a variation of the test due to Pratt (1959). Whereas the standard Wilcoxon test excludes values that equal μ0
Wilcoxon's signed rank test is a popular nonparametric alternative to a paired t test. In a paired t test, you analyze measurements for subjects before and after some treatment or intervention. You analyze the difference in the measurements for each subject, and test whether the mean difference is significantly different
A previous article discusses standardized coefficients in linear regression models and shows how to compute standardized regression coefficients in SAS by using the STB option on the MODEL statement in PROC REG. It also discusses how to interpret a standardized regression coefficient. Recently, a SAS user wanted to know how
A previous article shows an example of a Markov chain model and computes the probability that the system ends up in a terminal state (called an absorbing state). As explained previously, you can often compute exact probabilities for questions about Markov chains. Nevertheless, it can be useful to know how
A previous article shows how to model the probabilities in a discrete-time Markov chain by using a Markov transition matrix. A Markov chain is a discrete-time stochastic process for which the current state of the system determines the probability of the next state. In this process, the probabilities for transitioning
Given a set of N points in k-dimensional space, can you find the location that minimizes the sum of the distances to the points? The location that minimizes the distances is called the geometric median of the points. For univariate data, the "points" are merely a set of numbers $${p_1,
While writing an article about labeling a polygon by using the centroid, I almost made a false claim about the centroid. I almost claimed that that the centroid is the point in a polygon that minimizes the sum of the distances to the vertices. It is not. The point that
A colleague asked how to compute the barycentric coordinates of a point inside a triangle. Given a triangle in the plane with vertices p1, p2, and p3, every point in the triangle can be represented as a convex combination of the vertices: c1*p1 + c2*p2 + c3*p3, where c1,c2,c3 ≥
Part of the power of the SAS ODS system is the ability to visualize data by using ODS templates. An ODS template describes how to render data as a table or as a graph. A lot of papers and documentation have been written about how to define a custom template
While writing an article about Toeplitz matrices, I saw an interesting fact about the eigenvalues of tridiagonal Toeplitz matrices on Nick Higham's blog. Recall that a Toeplitz matrix is a banded matrix that is constant along each diagonal. A tridiagonal Toeplitz matrix is zero except for the main diagonal, the
A Toeplitz matrix is a banded matrix. You can construct it by specifying the parameters that are constant along each diagonal, including sub- and super-diagonals. For a square N x N matrix, there is one main diagonal, N-1 sub-diagonals, and N-1 super-diagonals, for a total of 2N-1 parameters. In statistics and applied
A previous article explains the Spearman rank correlation, which is a robust cousin to the more familiar Pearson correlation. I've also discussed why you might want to use rank correlation, and how to interpret the strength of a rank correlation. This article gives a short example that helps you to
Since the COVID-19 pandemic began, video presentations and webcasts have become a regular routine for many of us. On days that I will be using my webcam, I wear a solid-color shirt. If I don't plan to be on camera, I can wear a pinstripe Oxford shirt. Why the difference?
Real-world data often exhibits extreme skewness. It is not unusual to have data span many orders of magnitude. Classic examples are the distributions of incomes (impoverished and billionaires) and population sizes (small countries and populous nations). The readership of books and blog posts show a similar distribution, which is sometimes
Labeling objects in graphs can be difficult. SAS has a long history of providing support for labeling markers in scatter plots and for labeling regions on a map. This article discusses how the SGPLOT procedure decides where to put a label for a polygon. It discusses the advantages and disadvantages
SAS supports many ways to compute the rank of a numeric variable and to handle tied values. However, sometimes I need to rank the values in a character categorical variable. For example, the values {"Male", "Female", "Male"} have ranks {2, 1, 2} because, in alphabetical order, "Female" is the first-ranked
A previous article defines the silhouette statistic (Rousseeuw, 1987) and shows how to use it to identify observations in a cluster analysis that are potentially misclassified. The article provides many graphs, including the silhouette plot, which is a bar chart or histogram that displays the distribution of the silhouette statistic
Assigning observations into clusters can be challenging. One challenge is deciding how many clusters are in the data. Another is identifying which observations are potentially misclassified because they are on the boundary between two different clusters. Ralph Abbey's 2019 paper ("How to Evaluate Different Clustering Results") is a good way
A lot of programmers have been impressed by the ability of ChatGPT, GPT-4, and Bing Chat to write computer programs. Recently, I wrote an article that discusses an elementary programming assignment, called FizzBuzz, which is sometimes used as part of a hiring process to assess a candidate's basic knowledge of
Recently, I learned about an elementary programming assignment called the FizzBuzz program. Some companies use this assignment for the first round of interviews with potential programmers. A competent programmer can write FizzBuzz in 5-10 minutes, which leaves plenty of time to discuss other topics. If an applicant can't complete the
In SAS, you can approximate the exponential of a matrix by using the EXPMATRIX function in SAS IML software. This article discusses the exponential of a matrix: what it is, how to compute it, why it is useful, and why you should think of it as a linear map that
In a previous article, I showed how to overlay a density estimate on a histogram by using the Graph Template Language (GTL). However, a SAS programmer asked how to overlay a curve on a histogram when the curve is not a density estimate. In this case, the vertical axis for
When the SAS statistical graphics (SG) procedures were designed in the early 2000s, a goal was to create a comprehensive Graph Template Language (GTL) and leverage the GTL by using SG procedures that perform common tasks easily without having to write any GTL. This project was hugely successful, and "ODS
