The DO Loop
Statistical programming in SAS with an emphasis on SAS/IML programs
Recently I wrote about numerical analysis problem: the accurate computation of log(1+x) when x is close to 0. A naive computation of log(1+x) loses accuracy if you call the LOG function, which is why the SAS language provides the built-in LOG1PX for this computation. In addition, I showed that you
SAS supports a special function for the accurate evaluation of log(1+x) when x is near 0. The LOG1PX function is useful because a naive computation of log(1+x) loses accuracy when x is near 0. This article demonstrates two general approximation techniques that are often used in numerical analysis: the Taylor
The documentation for Python's SciPy package provides a table that concisely summarizes functions that are associated with continuous probability distributions. This article provides a similar table for SAS functions. For more information on the CDF, PDF, quantile, and random-variate functions, see "Four essential functions for statistical programmers." SAS functions for