Man pages for qle
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 |
| 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 |
| globalSearch | Find new global evaluatino point |
| krige | Kriging the sample means of statistics |
| 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... |
| nextLOCsample | Generate a random sample of points |
| OPT | QLE estimation results of the normal model |
| optStat | Optimal subset selection 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 |
| qle-package | Simulation-Based Quasi-Likelihood 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 |
| traceQIconstr | Find a new local evaluation point |
| traceQIsamp | Finding a new evaluation point |
| updateCovModels | Update covariance models |
