Man pages for mbaaske/qle
Simulation-Based Quasi-Likelihood Estimation

checkMultRootInspect estimated parameters
covarTxVariance matrix approximation
crossValTxPrediction variances by cross-validation
estimKriging prediction and estimation of derivatives
fitCovFitting covariance models by REML estimation
fitSIRFkEstimation of covariance parameters
getDefaultOptionsPrint default options for optimization
getQLmodelSetup the quasi-likelihood estimation model
krigeKriging the sample means of statistics
mahalDistMahalanobis distance of statistics
matclustMatern cluster process data
multiDimLHSMultidimensional Latin Hypercube Sampling (LHS) generation
multiSearchA multistart version of local searches for parameter...
nextLOCsampleGenerate a random sample of points
prefitCVCovariance parameter estimation for cross-validation
print.qleprint results of class 'qle'
print.qleTestprint 'qleTest' results
print.QSResultprint results of class 'QSResult'
qleSimulated quasi-likelihood parameter estimation
qle-packageSimulation-Based Quasi-Likelihood Estimation
qleTestMonte Carlo testing
QLmodelConstruct quasi-likelihood approximation
qscoringQuasi-scoring iteration
qsdA normal model
quasiDevianceQuasi-deviance computation
remlRestricted maximum likelihood (REML)
searchMinimizerMinimize a criterion function
setCovModelSet a covariance model
setQLdataSet quasi-likelihood (QL) data
simQLdataSimulate the statistical model
updateCovModelsUpdate covariance models
mbaaske/qle documentation built on Feb. 3, 2018, 11:02 a.m.