View source: R/shin92exalcove_opt.R
shin92exalcove_opt  R Documentation 
Uses shin92exalcove
to find bestfitting parameters for
the exALCOVE model for the shin92
CIRP.
shin92exalcove_opt(params = c(2, 1, 0.25, 0.75), recompute = FALSE, trace = 0)
params 
A vector containing the initial values for c, phi, la,
and lw, in that order. See 
recompute 
When set to TRUE, the function reruns the optimization (which takes about 25 minutes on a 2.4 GHz processor). When set to FALSE, the function returns a stored copy of the results of the optimization (which is instantaneous). 
trace 
Sets the level of tracing information (i.e. information
about the progress of the optimization), as defined by the

This function is an archive of the optimization procedure used to
derive the bestfitting parameters for the shin92exalcove
simulation; see Spicer et al. (2017) for a tutorial introduction to
the concept of simulation archives.
Optimization used the LBFGSB 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 shin92exalcove_opt
).
This function was run in 16 times from different starting points, using 8 threads on a Core i7 3.6 GHz processor. The default parameters of this function are those for the best fit from those 16 starting points. The 16 starting points were
pset < rbind(
c(2,1,.25,.25),c(2,1,.25,.75),c(2,1,.75,.25),c(2,1,.75,.75),
c(2,3,.25,.25),c(2,3,.25,.05),c(2,3,.75,.25),c(2,3,.75,.75),
c(8,1,.25,.25),c(8,1,.25,.75),c(8,1,.75,.25),c(8,1,.75,.75),
c(8,3,.25,.25),c(8,3,.25,.75),c(8,3,.75,.25),c(8,3,.75,.75)
)
not all of which converged successfully.
A vector containing the bestfitting 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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