Tag: Statistical Programming

Rick Wicklin 21
Four essential functions for statistical programmers

Normal, Poisson, exponential—these and other "named" distributions are used daily by statisticians for modeling and analysis. There are four operations that are used often when you work with statistical distributions. In SAS software, the operations are available by using the following four functions, which are essential for every statistical programmer

Rick Wicklin 8
Optimizing? Two hints for specifying derivatives

I previously wrote about using SAS/IML for nonlinear optimization, and demonstrated optimization by maximizing a likelihood function. Many well-known optimization algorithms require derivative information during the optimization, including the conjugate gradient method (implemented in the NLPCG subroutine) and the Newton-Raphson method (implemented in the NLPNRA method). You should specify analytic

Rick Wicklin 38
Maximum likelihood estimation in SAS/IML

A popular use of SAS/IML software is to optimize functions of several variables. One statistical application of optimization is estimating parameters that optimize the maximum likelihood function. This post gives a simple example for maximum likelihood estimation (MLE): fitting a parametric density estimate to data. Which density curve fits the

Rick Wicklin 4
Distances between words

When you misspell a word on your mobile device or in a word-processing program, the software might "autocorrect" your mistake. This can lead to some funny mistakes, such as the following: I hate Twitter's autocorrect, although changing "extreme couponing" to "extreme coupling" did make THAT tweet more interesting. [@AnnMariaStat] When

Rick Wicklin 8
A math puzzle solution

I previously wrote about an intriguing math puzzle that involves 5-digit numbers with certain properties. This post presents my solution in the SAS/IML language. It is easy to generate all 5-digit perfect squares, but the remainder of the problem involves looking at the digits of the squares. For this reason,

Rick Wicklin 0
Evaluate polynomials efficiently by using Horner's scheme

Polynomials are used often in data analysis. Low-order polynomials are used in regression to model the relationship between variables. Polynomials are used in numerical analysis for numerical integration and Taylor series approximations. It is therefore important to be able to evaluate polynomials in an efficient manner. My favorite evaluation technique

Rick Wicklin 7
Storing and loading modules

You can extend the capability of the SAS/IML language by writing modules. A module is a user-defined function. You can define a module by using the START and FINISH statements. Many people, including myself, define modules at the top of the SAS/IML program in which they are used. You can

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