R: Profile Estimation with Collocation Inference

ProfileObjective {CollocInfer}

R Documentation

Profile Estimation with Collocation Inference

Description

Profile estimation and objective functions for collocation estimation of parameters in continuous-time stochastic processes.

Usage

Profile.GausNewt(pars,times,data,coefs,lik,proc,in.meth="nlminb",
      control.in=NULL,active=1:length(pars),
      control=list(reltol=1e-6,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 `pars`. Assignment `allpars[active] = pars` is always made.
`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`	`lik` object defining the observation process.
`proc`	`proc` object defining the state process.
`in.meth`	Inner optimization function currently one of 'nlminb', 'MaxNR', 'optim' or 'house'. The last calls `SplineEst.NewtRaph`. This is fast but has poor convergence.
`control.in`	Control object for inner optimization function.
`sgn`	Is the minimizing (1) or maximizing (0)?
`active`	Incides indicating which parameters of `pars` should be estimated; defaults to all of them.
`oldpars`	Starting parameter values for the Q-function 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 outer-optimization?
`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 Newton-Raphson optimization. It should contain reltol Relative tollerance criterion for the gradient and improvement before termination. maxit Maximum number of iterations. maxtry Maximum number of halving-steps to try before declaring no improvement is possible. trace How much iteration history to output; 0 surpresses all output, a positive value outputs parameters and improvement at each iteration.

Details

Profile.GausNewt provides a simple implementation of Gauss-Newton 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 halving-steps 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