The various algorithms need different amounts of memory for working space. Let p be the number of parameters that are estimated, n be the number of observations that are used in the model estimation, and s be the size (in bytes) of the double data type.
For the simplex algorithm, the minimum working space (in bytes) that is needed is
![\[ (2np + 6n + 10p)s \]](images/statug_qreg0326.png)
For the interior point algorithm, the minimum working space (in bytes) that is needed is
![\[ (np + p^2 + 13n + 4p)s \]](images/statug_qreg0327.png)
For the smoothing algorithm, the minimum working space (in bytes) that is needed is
![\[ (np + p^2 + 6n + 4p)s \]](images/statug_qreg0328.png)
For the last two algorithms, if you want to use preprocessing, the following additional amount of working space (in bytes) is needed:
![\[ (np + 6n + 2p)s \]](images/statug_qreg0329.png)
If sufficient space is available, the input data set is kept in memory. Otherwise, the input data set is reread as necessary, and the execution time of the procedure increases substantially.