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| The REG Procedure |
The REG procedure is efficient for ordinary regression; however, requests for optional features can greatly increase the amount of time required.
The major computational expense in the regression analysis is the collection of the crossproducts matrix. For p variables and n observations, the time required is proportional to np2. For each model run, PROC REG needs time roughly proportional to k3, where k is the number of regressors in the model. Add an additional nk2 for one of the R, CLM, or CLI options and another nk2 for the INFLUENCE option.
Most of the memory that PROC REG needs to solve large problems is used for crossproducts matrices. PROC REG requires 4p2 bytes for the main crossproducts matrix plus 4k2 bytes for the largest model. If several output data sets are requested, memory is also needed for buffers.
See the "Input Data Sets" section for information on how to use TYPE=SSCP data sets to reduce computing time.
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