nosof88protoalcove_opt {catlearn} | R Documentation |
Parameter optimization of proto-ALCOVE model with nosof88 CIRP
Description
Uses nosof88protoalcove
to find best-fitting parameters
for the ex-ALCOVE model for the nosof88
CIRP.
Usage
nosof88protoalcove_opt(recompute = FALSE)
Arguments
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. |
Details
This function is an archive of the optimization procedure used to
derive the best-fitting parameters for the
nosof88protoalcove
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 nosof88protoalcove_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).
Value
A vector containing the best-fitting values for c, phi, la, and lw, in
that order. See slpALCOVE
for an explanation of these
parameters.
Author(s)
Andy Wills
References
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.