Start value for optimization routine, taken to be an object of class
paras. Default value of NULL means to start with
Lindsey(y,n), which theoretically should be the maximum
likelihood estimate
method
String giving which optimization method to use. Default
of Nelder means to use optim() with the Nelder-Mead
method; the other supported option is nlm
printing
Boolean, with TRUE meaning to print information as the
optimization progresses and default FALSE meaning to print
nothing
give_fit
Boolean, with default FALSE meaning to return
the maximum likelihood estimate in the form of a paras
object, and TRUE meaning to return a two-element list, the
first being the output of nlm() or optim() and the
second being the MLE
...
Further arguments passed to the optimization routine. In
particular, note that hessian=TRUE is useful in conjunction
with give_fit=TRUE
Details
Function optimizer() is the user-friendly version: it is a wrapper for
optimizer_samesum() and optimizer_differsums(); it
dispatches according to whether the rowsums are identical or not.
These functions are slow because they need to evaluate NormC()
repeatedly, which is expensive.
Function optimizer_samesum() nominally produces the same output
as Lindsey(), but is more computationally intensive.
Author(s)
Robin K. S. Hankin
See Also
Lindsey
Examples
data(voting)
p1 <- Lindsey(voting,voting_tally)
p2 <- optimizer(voting,voting_tally,start=p1)
theta(p1) - theta(p2) # Should be zero
## Not run:
data(pollen)
p1 <- optimizer(pollen)
p2 <- Lindsey(pollen)
theta(p1) - theta(p2) # Isn't zero...numerical scruff...
## End(Not run)
Results
R version 3.3.1 (2016-06-21) -- "Bug in Your Hair"
Copyright (C) 2016 The R Foundation for Statistical Computing
Platform: x86_64-pc-linux-gnu (64-bit)
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Type 'license()' or 'licence()' for distribution details.
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Type 'contributors()' for more information and
'citation()' on how to cite R or R packages in publications.
Type 'demo()' for some demos, 'help()' for on-line help, or
'help.start()' for an HTML browser interface to help.
Type 'q()' to quit R.
> library(MM)
Loading required package: magic
Loading required package: abind
Loading required package: partitions
Loading required package: emulator
Loading required package: mvtnorm
Loading required package: Oarray
> png(filename="/home/ddbj/snapshot/RGM3/R_CC/result/MM/optimizer.Rd_%03d_medium.png", width=480, height=480)
> ### Name: optimizer
> ### Title: Maximum likelihood estimator for the MM
> ### Aliases: optimizer optimizer_allsamesum optimizer_differsums
>
> ### ** Examples
>
> data(voting)
> p1 <- Lindsey(voting,voting_tally)
> p2 <- optimizer(voting,voting_tally,start=p1)
>
> theta(p1) - theta(p2) # Should be zero
Lib Con Lab
Lib 0 0 0
Con 0 0 0
Lab 0 0 0
>
> ## Not run:
> ##D data(pollen)
> ##D p1 <- optimizer(pollen)
> ##D p2 <- Lindsey(pollen)
> ##D theta(p1) - theta(p2) # Isn't zero...numerical scruff...
> ## End(Not run)
>
>
>
>
>
>
> dev.off()
null device
1
>