SAS supports more than 25 common probability distributions for the PDF, CDF, QUANTILE, and RAND functions. If you need a less-common distribution, you can implement new distributions by using Base SAS (specifically, PROC FCMP) or the SAS/IML language. On the SAS Support Communities, a SAS programmer asked how to implement the generalized extreme value (GEV) distribution in SAS. This article shows how to use PROC FCMP and PROC IML to implement functions for working with the GEV distribution. T...| The DO Loop
A previous article discusses Cohen's d statistic and how to compute it in SAS. For a two-sample independent design, Cohen's d estimates the standardized mean difference (SMD). Because Cohen's d is a biased statistic, the previous article also computes Hedges' g, which is an unbiased estimate of the SMD. Lastly, the article discusses how to estimate the standard error of the statistic. Today's article extends the analysis by showing how to compute a confidence interval (CI) for Cohen's d (and ...| The DO Loop
SAS provides procedures to fit common probability distributions to sample data. You can use PROC UNIVARIATE in Base SAS or PROC SEVERITY in SAS/ETS software to estimate the distribution parameters for approximately 20 common distributions, including normal, lognormal, beta, gamma, and Weibull. Since there are infinitely many distributions, you may eventually need to fit a distribution that SAS does not natively support. There are three often-used methods for fitting the parameters of a distri...| The DO Loop
I am a die-hard Survivor fan. I was born the year after the show came out, and since then I have tuned in for every single episode, with season 48 being no exception. However, I’ve noticed a trend: the players I think are most deserving of the million dollars never end up winning! As a data lover, I was curious about what the stats said. What qualities make a Survivor winner? Did the players with the best stats end up winning the game? And, most importantly, can a model predict who will wi...| SAS Users
Isotonic regression (also called monotonic regression) is a type of regression model that assumes that the response variable is a monotonic function of the explanatory variable(s).| The DO Loop
One of the most exciting features of SAS Viya Workbench is that the code editor includes a generative AI component called SAS Viya Copilot.| The DO Loop
A previous article discusses a formula for a confidence interval for R-square in a linear regression model (Olkin and Finn (1995) "Correlations redux", Psychological Bulletin) The formula is useful for large data sets, but should be used with caution for small samples.| The DO Loop
This article discusses how to scale a probability density curve so that it fits appropriately on a histogram, as shown in the graph to the right.| The DO Loop
