inneropt.DDE: Inner optimization for estmating coefficients given...

Description Usage Arguments Details Value Author(s)

Description

Estmates spline coefficients given parameters for DDE models.

Usage

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inneropt.DDE(data, times, pars, beta, coefs, lik, proc, in.meth = "nlminb",
  control.in = list(), basisvals, fdobj0)

Arguments

data

Matrix of observed data values.

times

Vector observation times for the data.

pars

Initial values of parameters to be estimated processes.

beta

Initial values of the contribution of lags for the delay.

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', 'optim', or 'trustOptim'.

control.in

Control object for inner optimization function.

basisvals

Values of the collocation basis to be used. This should be a basis object from the fda package.

fdobj0

A functional data object fitted with the history part of the data.

Details

This minimizes the objective function for DDE models defined by the addition of the lik and proc objectives with respect to the coefficients. A number of generic optimization routines can be used and some experimentation is recommended.

Value

A list with elements

coefs

A matrix giving he optimized coefficients.

res

The results of the inner optimization function.

Author(s)

Ziqian Zhou


gpDDE documentation built on May 2, 2019, 1:09 p.m.