ProfileObjective {CollocInfer}  R Documentation 
Profile Estimation with Collocation Inference
Description
Profile estimation and objective functions for collocation estimation of parameters in continuoustime stochastic processes.
Usage
Profile.GausNewt(pars,times,data,coefs,lik,proc,in.meth="nlminb",
control.in=NULL,active=1:length(pars),
control=list(reltol=1e6,maxit=50,maxtry=15,trace=1))
ProfileSSE(pars,allpars,times,data,coefs,lik,proc,in.meth='nlminb',
control.in=NULL,active=1:length(pars),dcdp=NULL,oldpars=NULL,
use.nls=TRUE,sgn=1)
ProfileErr(pars,allpars,times,data,coefs,lik,proc,in.meth = "house",
control.in=NULL,sgn=1,active=1:length(allpars))
ProfileDP(pars,allpars,times,data,coefs,lik,proc,in.meth = "house",
control.in=NULL,sgn=1,sumlik=1,active=1:length(allpars))
ProfileList(pars,allpars,times,data,coefs,lik,proc,in.meth = "house",
control.in=NULL,sgn=1,active=1:length(allpars))
Arguments
pars 
Initial values of parameters to be estimated processes. 
allpars 
Full parameter vector including 
times 
Vector observation times for the data. 
data 
Matrix of observed data values. 
coefs 
Vector giving the current estimate of the coefficients in the spline. 
lik 

proc 

in.meth 
Inner optimization function currently one of 'nlminb', 'MaxNR', 'optim' or 'house'. The last calls 
control.in 
Control object for inner optimization function. 
sgn 
Is the minimizing (1) or maximizing (0)? 
active 
Incides indicating which parameters of 
oldpars 
Starting parameter values for the Qfunction in the EM algorithm. 
dcdp 
Estimate for the gradient of the optimized coefficients with respect to parameters; used internally. 
use.nls 
In ProfileSSE, is 'nls' being used in the outeroptimization? 
sumlik 
In ProfileDP and ProfileDP.AllPar; should the gradient be given for each observation, or summed over them? 
control 
A list giving control parameters for NewtonRaphson optimization. It should contain

Details
Profile.GausNewt
provides a simple implementation of GaussNewton optimization and may
not result in optimized values that are as good as other optimizers in R
.
When Profile.GausNewt
is not being used, ProfileSEE
and ProfileERR
create the
following temporary files:
counter.tmpThe number of halvingsteps taken on the current optimization step.
curcoefs.tmpThe current estimates of the coefficients.
optcoefs.tmpThe optimal estimates of the coefficients in the iteration history.
These need to be removed manually when the optimization is finished. optcoefs.tmp
will contain
the optimal value of coefs
for plotting the estimated trajectories.
Value
Profile.GausNewt 
Output of a simple GausNewton iteration to optimizing the objective function when the observation likelihood takes the form of a sum of squared errors. Returns a list with the following elements:

ProfileSSE 
Output for the outer optimization when the observation likelihood is given by squared error. This is a list with the following elements

ProfileErr 
The outer optimization criterion in the general case: the value of the observation likelihood at the profiled
estimates of 
ProfileDP 
The derivative of 
ProfileList 
Returns the results of ProfileErr and ProfileDP as a list with elements 
See Also
outeropt
, Profile.LS
, Profile.multinorm
, LS.setup
, multinorm.setup