The DO Loop
Statistical programming in SAS with an emphasis on SAS/IML programs
Many optimization problems in statistics and machine learning involve continuous parameters. For example, maximum likelihood estimation involves optimizing a log-likelihood function over a continuous domain, possibly with constraints. Recently, however, I had to solve an optimization problem for which the solution vector was a 0/1 binary variable. To solve the
In a matrix-vector language such as SAS/IML, it is useful to always remember that the fundamental objects are matrices and that all operations are designed to work on matrices. (And vectors, which are matrices that have only one row or one column.) By using matrix operations, you can often eliminate
A reader asked whether it is possible to find a bootstrap sample that has some desirable properties. I am using the term "bootstrap sample" to refer to the result of randomly resampling with replacement from a data set. Specifically, he wanted to find a bootstrap sample that has a specific