qle-package | Simulation-Based Quasi-Likelihood Estimation |
checkMultRoot | Inspect estimated parameters |
covarTx | Variance matrix approximation |
crossValTx | Prediction variances by cross-validation |
estim | Kriging prediction and estimation of derivatives |
extract | Kriging the sample means of statistics |
fitCov | Fitting covariance models by REML estimation |
fitSIRFk | Estimation of covariance parameters |
getDefaultOptions | Print default options for optimization |
getQLmodel | Setup the quasi-likelihood estimation model |
jacobian | Kriging prediction and estimation of derivatives |
mahalDist | Mahalanobis distance of statistics |
matclust | Matern cluster process data |
multiDimLHS | Multidimensional Latin Hypercube Sampling (LHS) generation |
nextLOCsample | Generate a random sample of points |
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 quasi-likelihood approximation |
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 | Set quasi-likelihood (QL) data |
simQLdata | Simulate the statistical model |
updateCovModels | Update covariance models |
varKM | Kriging the sample means of statistics |