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 |