1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
|
% Generated by roxygen2: do not edit by hand
% Please edit documentation in R/MxCompute.R
\name{mxComputeTryHard}
\alias{mxComputeTryHard}
\alias{MxComputeTryHard-class}
\title{Repeatedly attempt a compute plan until successful}
\usage{
mxComputeTryHard(
plan,
...,
freeSet = NA_character_,
verbose = 0L,
location = 1,
scale = 0.25,
maxRetries = 3L
)
}
\arguments{
\item{plan}{compute plan to optimize the model}
\item{...}{Not used. Forces remaining arguments to be specified by name.}
\item{freeSet}{names of matrices containing free variables}
\item{verbose}{integer. Level of run-time diagnostic output. Set to zero to disable}
\item{location}{location of the perturbation distribution}
\item{scale}{scale of the perturbation distribution}
\item{maxRetries}{maximum number of plan evaluations per invocation (including the first evaluation)}
}
\description{
The provided compute plan is run until the status code indicates
success (0 or 1). It gives up after a small number of retries.
}
\details{
Upon failure, start values are randomly perturbed. Currently only
the uniform distribution is implemented. The distribution is
parameterized by arguments \code{location} and \code{scale}. The
location parameter is the distribution's median. For the uniform
distribution, \code{scale} is the absolute difference between its
median and extrema (i.e., half the width of the rectangle). Each
start value is multiplied by a random draw and then added to a
random draw from a distribution with the same \code{scale} but
with a median of zero.
}
\references{
Shanno, D. F. (1985). On Broyden-Fletcher-Goldfarb-Shanno method. \emph{Journal of
Optimization Theory and Applications, 46}(1), 87-94.
}
\seealso{
\code{\link{mxTryHard}}
}
|
