Simulation-Based Quasi-Likelihood Estimation


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Documentation for package ‘qle’ version 0.18

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qle-package Simulation-Based Quasi-Likelihood Estimation
checkMultRoot Assess plausibility of parameter estimates
covarTx Variance matrix approximation
crossValTx Prediction variances by cross-validation
estim Kriging prediction and numerical approximation of derivatives
extract Kriging the sample means of statistics
fitCov Covariance parameter estimation
fitSIRFk Estimation of covariance parameters
getDefaultOptions Print default options for optimization
getQLmodel Setup the quasi-likelihood approximation model all at once
jacobian Kriging prediction and numerical approximation of derivatives
mahalDist Mahalanobis distance of statistics
matclust Matern cluster process data
mm1q QLE estimation results of M/M/1 queue
multiDimLHS Multidimensional Latin Hypercube Sampling (LHS) generation
multiSearch A multistart version of local searches for parameter estimation
nextLOCsample Generate a random sample of points
OPT QLE estimation results of the normal model
optStat Optimal subset selection of statistics
predictKM Kriging the sample means of statistics
prefitCV Covariance parameter estimation for cross-validation
print.qle print results of class 'qle'
print.qleTest print 'qleTest' results
print.QSResult print results of class 'QSResult'
qle Simulated quasi-likelihood parameter estimation
qleTest Monte Carlo testing
QLmodel Construct the quasi-likelihood approximation model
qscoring Quasi-scoring iteration
qsd A normal model
quasiDeviance Quasi-deviance computation
reml Restricted maximum likelihood (REML)
searchMinimizer Minimize a criterion function
setCovModel Set a covariance model
setQLdata Setup of quasi-likelihood data for estimation
simQLdata Simulate the statistical model
Subset of statistics Optimal subset selection of statistics
updateCovModels Update covariance models
varKM Kriging the sample means of statistics