It is sometimes necessary for researchers to simulate data with thousands of variables. It is easy to simulate thousands of uncorrelated variables, but more difficult to simulate thousands of correlated variables. For that, you can generate a correlation matrix that has special properties, such as a Toeplitz matrix or a

## Tag: **Statistical Programming**

A radial basis function is a scalar function that depends on the distance to some point, called the center point, c. One popular radial basis function is the Gaussian kernel φ(x; c) = exp(-||x – c||2 / (2 σ2)), which uses the squared distance from a vector x to the

Every day I’m shufflin'. Shufflin', shufflin'. -- "Party Rock Anthem," LMFAO The most popular way to mix a deck of cards is the riffle shuffle, which separates the deck into two pieces and interleaves the cards from each piece. Besides being popular with card players, the riffle shuffle is

Have you ever tried to type a movie title by using a TV remote control? Both Netflix and Amazon Video provide an interface (a virtual keyboard) that enables you to use the four arrow keys of a standard remote control to type letters. The letters are arranged in a regular

Given a rectangular grid with unit spacing, what is the expected distance between two random vertices, where distance is measured in the L1 metric? (Here "random" means "uniformly at random.") I recently needed this answer for some small grids, such as the one to the right, which is a 7 x 6

In the SAS/IML language, you can only concatenate vectors that have conforming dimensions. For example, to horizontally concatenate two vectors X and Y, the symbols X and Y must have the same number of rows. If not, the statement Z = X || Y will produce an error: ERROR: Matrices

A SAS programmer recently asked me how to compute a kernel regression in SAS. He had read my blog posts "What is loess regression" and "Loess regression in SAS/IML" and was trying to implement a kernel regression in SAS/IML as part of a larger analysis. This article explains how to

A SAS programmer recently asked how to interpret the "standardized regression coefficients" as computed by the STB option on the MODEL statement in PROC REG and other SAS regression procedures. The SAS documentation for the STB option states, "a standardized regression coefficient is computed by dividing a parameter estimate by

Video killed the radio star.... We can't rewind, we've gone too far. -- The Buggles (1979) "You kids have it easy," my father used to tell me. "When I was a kid, I didn't have all the conveniences you have today." He's right, and I could say the same

The SGPLOT procedure in SAS makes it easy to create graphs that overlay various groups in the data. Many statements support the GROUP= option, which specifies that the graph should overlay group information. For example, you can create side-by-side bar charts and box plots, and you can overlay multiple scatter

This article shows how to score (evaluate) a quantile regression model on new data. SAS supports several procedures for quantile regression, including the QUANTREG, QUANTSELECT, and HPQUANTSELECT procedures. The first two procedures do not support any of the modern methods for scoring regression models, so you must use the "missing

When you use a regression procedure in SAS that supports variable selection (GLMSELECT or QUANTSELECT), did you know that the procedures automatically produce a macro variable that contains the names of the selected variables? This article provides examples and details. A previous article provides an overview of the 'SELECT' procedures

This article describes how to obtain an initial guess for nonlinear regression models, especially nonlinear mixed models. The technique is to first fit a simpler fixed-effects model by replacing the random effects with their expected values. The parameter estimates for the fixed-effects model are often good initial guesses for the

When you fit nonlinear fixed-effect or mixed models, it is difficult to guess the model parameters that fit the data. Yet, most nonlinear regression procedures (such as PROC NLIN and PROC NLMIXED in SAS) require that you provide a good guess! If your guess is not good, the fitting algorithm,

A previous article provides an example of using the BOOTSTRAP statement in PROC TTEST to compute bootstrap estimates of statistics in a two-sample t test. The BOOTSTRAP statement is new in SAS/STAT 14.3 (SAS 9.4M5). However, you can perform the same bootstrap analysis in earlier releases of SAS by using

I recently recorded a short video about the new syntax for specifying and manipulating lists in SAS/IML 14.3. This is a video of my Super Demo at SAS Global Forum 2018. The new syntax supports dynamic arrays, associative arrays ("named lists"), and hierarchical data structures such as lists of lists.

A colleague and I recently discussed how to generate random permutations without encountering duplicates. Given a set of n items, there are n! permutations My colleague wants to generate k unique permutations at random from among the total of n!. Said differently, he wants to sample without replacement from the

Correlation is a statistic that measures how closely two variables are related to each other. The most popular definition of correlation is the Pearson product-moment correlation, which is a measurement of the linear relationship between two variables. Many textbooks stress the linear nature of the Pearson correlation and emphasize that

Suppose you want to find observations in multivariate data that are closest to a numerical target value. For example, for the students in the Sashelp.Class data set, you might want to find the students whose (Age, Height, Weight) values are closest to the triplet (13, 62, 100). The way to

About once a month I see a question on the SAS Support Communities that involves what I like to call "computations with combinations." A typical question asks how to find k values (from a set of p values) that maximize or minimize some function, such as "I have 5 variables,

Data analysts often fit a probability distribution to data. When you have access to the data, a common technique is to use maximum likelihood estimation (MLE) to compute the parameters of a distribution that are "most likely" to have produced the observed data. However, how can you fit a distribution

This article describes and implements a fast algorithm that estimates a median for very large samples. The traditional median estimate sorts a sample of size N and returns the middle value (when N is odd). The algorithm in this article uses Monte Carlo techniques to estimate the median much faster.

Your statistical software probably provides a function that computes quantiles of common probability distributions such as the normal, exponential, and beta distributions. Because there are infinitely many probability distributions, you might encounter a distribution for which a built-in quantile function is not implemented. No problem! This article shows how to

A popular way to use lists in the SAS/IML language is to pack together several related matrices into a single data structure that can be passed to a function. Imagine that you have written an algorithm that requires a dozen different parameters. Historically, you would have to pass those parameters

SAS/IML 14.3 (SAS 9.4M5) introduced a new syntax for creating lists and for assigning and extracting item in a list. Lists (introduced in SAS/IML 14.2) are data structures that are convenient for holding heterogeneous data. A single list can hold character matrices, numeric matrices, scalar values, and other lists, as

Last week I wrote about the 10 most popular articles from The DO Loop in 2017. My most popular articles tend to be about elementary statistics or SAS programming tips. Less popular are the articles about advanced statistical and programming techniques. However, these technical articles fill an important niche. Not

When you run an optimization, it is often not clear how to provide the optimization algorithm with an initial guess for the parameters. A good guess converges quickly to the optimal solution whereas a bad guess might diverge or require many iterations to converge. Many people use a default value

A statistical programmer read my article about the beta-binomial distribution and wanted to know how to compute the cumulative distribution (CDF) and the quantile function for this distribution. In general, if you know the PDF for a discrete distribution, you can also compute the CDF and quantile functions. This article

Did you know that a SAS/IML function can recover from a run-time error? You can specify how to handle run-time errors by using a programming technique that is similar to the modern "try-catch" technique, although the SAS/IML technique is an older implementation. Preventing errors versus handling errors In general, SAS/IML

Debugging is the bane of every programmer. SAS supports a DATA step debugger, but that debugger can't be used for debugging SAS/IML programs. In lieu of a formal debugger, many SAS/IML programmers resort to inserting multiple PRINT statements into a function definition. However, there is an easier way to query