Strengthen your programming skills with tips and techniques from the experts
One of the first things I learned in SAS was how to use PROC PRINT to display parts of a data set. I usually do not need to see all the data, so my favorite way to use PROC PRINT is to use the OBS= data set option to display
In a previous article, I showed how to generate random points uniformly inside a d-dimensional sphere. In that article, I stated the following fact: If Y is drawn from the uncorrelated multivariate normal distribution, then S = Y / ||Y|| has the uniform distribution on the unit sphere. I was
Imagine an animal that is searching for food in a vast environment where food is scarce. If no prey is nearby, the animal's senses (such as smell and sight) are useless. In that case, a reasonable search strategy is a random walk. The animal can choose a random direction, walk/swim/fly
The inverse gamma distribution is a continuous probability distribution that is used in Bayesian analysis and in some statistical models. The inverse gamma distribution is closely related to the gamma distribution. For any probability distribution, it is essential to know how to compute four functions: the PDF function, which returns
Years ago, I wrote about how to compute the incomplete beta function in SAS. Recently, a SAS programmer asked about a similar function, called the incomplete gamma function. The incomplete gamma function is a "special function" that arises in applied math, physics, and statistics. You should not confuse the gamma
This is the third and last introductory article about how to bootstrap time series in SAS. In the first article, I presented the simple block bootstrap and discussed why bootstrapping a time series is more complicated than for regression models that assume independent errors. Briefly, when you perform residual resampling
As I discussed in a previous article, the simple block bootstrap is a way to perform a bootstrap analysis on a time series. The first step is to decompose the series into additive components: Y = Predicted + Residuals. You then choose a block length (L) that divides the total
On The DO Loop blog, I write about a diverse set of topics, including statistical data analysis, machine learning, statistical programming, data visualization, simulation, numerical analysis, and matrix computations. In a previous article, I presented some of my most popular blog posts from 2020. The most popular articles often deal
For ordinary least squares (OLS) regression, you can use a basic bootstrap of the residuals (called residual resampling) to perform a bootstrap analysis of the parameter estimates. This is possible because an assumption of OLS regression is that the residuals are independent. Therefore, you can reshuffle the residuals to get
Last year, I wrote more than 100 posts for The DO Loop blog. In previous years, the most popular articles were about SAS programming tips, statistical analysis, and data visualization. But not in 2020. In 2020, when the world was ravaged by the coronavirus pandemic, the most-read articles were related
