getQLmodel: Setup the quasi-likelihood approximation model all at once

In qle: Simulation-Based Quasi-Likelihood Estimation

Description

Initial setup of the quasi-likelihood approximation model

Usage

getQLmodel(runs, lb, ub, obs, X = NULL, useVar = TRUE,
  criterion = "qle", ...)

Arguments

runs	object of class simQL, simulation results from simQLdata
lb	lower bounds defining the (hyper)box of the parameter domain for QL estimation
ub	upper bounds defining the (hyper)box of the parameter domain for QL estimation
obs	numeric vector of observed statistics
X	matrix of sample locations (model parameters)
useVar	logical, TRUE (default), whether to use prediction variances of any kind
criterion	name of criterion function to be minimized for QL estimation (see qle)
...	arguments passed to fitSIRFk, setQLdata, setCovModel and QLmodel for REML estimation of all covariance models

Details

The function is a wrapper of simQLdata, QLmodel, fitSIRFk and thus sets up the quasi-likelihood approximation model all at once.

Value

Object of class QLmodel

Author(s)

M. Baaske

See Also

simQLdata, QLmodel, fitSIRFk

Examples

data(normal)

# simulate model at a minimum of required design points
sim <- simQLdata(sim=qsd$simfn,nsim=5,N=8,
			 method="maximinLHS",lb=qsd$lower,ub=qsd$upper)
	 
# true and error-free observation
obs <- structure(c("T1"=2,"T2"=1), class="simQL")

# construct QL approximation model
qsd <- getQLmodel(sim,qsd$lower,qsd$upper,obs,var.type="wcholMean")

qle documentation built on May 2, 2019, 9:55 a.m.