Logistic function macro for SAS

Used in logistic regression, neural networks, and countless other applications, the logistic function is simple to understand yet can be quirky to calculate in SAS because of how SAS treats extreme values. First, let’s consider the value -1000: R…

What 5,728.986 miles look like…

Time Series as calendar heat maps + All of my running data since April 1, 2009 = Generated by the following code: #Sample Code based on example program at: source(file = “calendarHeat.R”) run<- read.csv(“log.csv”, header = TRUE, sep=”,”) sum(run$Distance) date <- c() for (i in 1: dim(run)[1]){ if(run$DistanceUnit[i]== ‘Kilometer’){ miles <- c(miles,run$Distance[i] * 0.62) } […]

Data Steps 2011-11-09 21:36:00

I have been following some of the recent talk going on the blogosphere about R and SAS.R vs SAS/SPSS in Corporations: A view from the other sideShe is correct that it is nearly impossible to get large organizations to give up their propietary software….