Description Usage Arguments Details Value Author(s) References

View source: R/nosof88exalcove_opt.R

Uses `nosof88exalcove`

to find best-fitting parameters for
the ex-ALCOVE model for the `nosof88`

CIRP.

1 | ```
nosof88exalcove_opt(recompute = FALSE)
``` |

`recompute` |
When set to TRUE, the function re-runs the optimization. When set to FALSE, the function returns a stored copy of the results of the optimization. |

This function is an archive of the optimization procedure used to
derive the best-fitting parameters for the `nosof88exalcove`

simulation; see Spicer et al. (2017) for a tutorial introduction to
the concept of simulation archives.

Optimization used the L-BFGS-B method from the `optim`

function of the standard R `stats`

package. The objective
function was sum of squared errors. Please inspect the source code for
further details (e.g. type `nosof88exalcove_opt`

). The
optimization was repeated for 16 different sets of starting values.

Where `recompute = TRUE`

, the function can take many hours to
run, depending on your system, and there is no progress bar. You can
use Task Manager (Windows) or equivalent if you want some kind of
visual feedback that the code is working hard. The code uses all the
processor cores on the local machine, so speed of execution is a
simple function of clock speed times processor cores. So, for example,
a 4 GHz i7 processor (8 virutal cores) will take a quarter of the time
to run this compared to a 2 GHz i5 processor (4 virtual cores).

A vector containing the best-fitting values for c, phi, la, and lw, in
that order. See `slpALCOVE`

for an explanation of these
parameters.

Andy Wills

Spicer, S., Jones, P.M., Inkster, A.B., Edmunds, C.E.R. & Wills,
A.J. (2017). Progress in learning theory through distributed
collaboration: Concepts, tools, and examples. *Manuscript in
preparation*.

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