Automated Uncertainty Analysis
![[R logo]](../../../doc/html/Rlogo.svg)
![[Up]](../../../doc/html/left.jpg)
![[Top]](../../../doc/html/up.jpg)
Documentation for package ‘ldt’ version 0.5.3
Help Pages
| adjust_indices_after_remove | Adjust Indices in a List |
| AIC.ldt.estim | Akaike Information Criterion |
| BIC.ldt.estim | Bayesian Information Criterion |
| boxCoxTransform | Box-Cox Transformation of Numeric Matrix |
| coef.ldt.estim | Extract Coefficients Matrix |
| coefs.table | Create Table of Coefficients |
| combine.search | Combine a List of 'ldt.search' Objects |
| data.berka | Berka and Sochorova (1993) Dataset for Loan Default |
| data.pcp | IMF's Primary Commodity Prices |
| data.wdi | Long-run Growth from World Development Indicator Dataset |
| endogenous | Extract Endogenous Variable(s) Data |
| eqList2Matrix | Convert a List of Equations to a Matrix |
| estim.bin | Estimate a Binary Choice Model |
| estim.binary.model.string | Get Model Name |
| estim.sur | Estimate a SUR Model |
| estim.varma | Estimate a VARMA Model |
| estim.varma.model.string | Get the Specification of an 'ldt.estim.varma' Model |
| exogenous | Extract Exogenous Variable(s) Data |
| fan.plot | Fan Plot Function |
| fitted.ldt.estim | Extract Fitted Data |
| get.combinations | Define Combinations for Search Process |
| get.data | Transform and Prepare Data for Analysis |
| get.data.append.newX | Append 'newX' to 'data$data' matrix. |
| get.data.check.discrete | Check if a column is discrete |
| get.data.check.intercept | Check for an intercept in a matrix |
| get.data.keep.complete | Remove Rows with Missing Observations from Data |
| get.indexation | Get Numeric Indices in a Combination |
| get.options.lbfgs | Get Options for L-BFGS Optimization |
| get.options.neldermead | Options for Nelder-Mead Optimization |
| get.options.newton | Get Options for Newton Optimization |
| get.options.pca | Get Options for PCA |
| get.options.roc | Get Options for ROC and AUC Calculations |
| get.search.items | Specify the Purpose of the Model Search Process |
| get.search.metrics | Get Options for Measuring Performance |
| get.search.modelchecks | Set Options to Exclude a Model Subset |
| get.search.options | Get Extra Options for Model Search Process |
| get.varma.params | Split VARMA parameter into its Components |
| logLik.ldt.estim | Extract Maximum Log-Likelihood |
| plot.ldt.estim | Plot Diagnostics for 'ldt.estim' Object |
| plot.ldt.varma.prediction | Plot Predictions from a VARMA model |
| predict.ldt.estim | Extract Prediction Results |
| predict.ldt.estim.varma | Extract Prediction Results from a 'ldt.estim.varma' Object |
| print.ldt.estim | Prints an 'ldt.estim' object |
| print.ldt.estim.projection | Prints an 'ldt.estim.projection' object |
| print.ldt.list | Prints an 'ldt.list' object |
| print.ldt.search | Prints an 'ldt.search' object |
| print.ldt.varma.prediction | Prints an 'ldt.varma.prediction' object |
| rand.mnormal | Generate Random Samples from a Multivariate Normal Distribution |
| residuals.ldt.estim | Extract Residuals Data |
| s.cluster.h | Hierarchical Clustering |
| s.cluster.h.group | Group Variables with Hierarchical Clustering |
| s.combine.stats4 | Combine Mean, Variance, Skewness, and Kurtosis This function combines two sets of mean, variance, skewness, and kurtosis and generates the combined statistics. |
| s.distance | Get the Distances Between Variables |
| s.gld.density.quantile | GLD Density-Quantile Function |
| s.gld.from.moments | Get the GLD Parameters from the moments |
| s.gld.quantile | GLD Quantile Function |
| s.metric.from.weight | Convert a Weight to Metric |
| s.pca | Principal Component Analysis |
| s.roc | Get ROC Curve Data for Binary Classification |
| s.weight.from.metric | Convert a Metric to Weight |
| search.bin | Create a Model Set for Binary Choice Models |
| search.rfunc | Create a Model Set for an R Function |
| search.steps | Step-wise estimation |
| search.sur | Create a Model Set for SUR Models |
| search.varma | Create Model Set for VARMA Models |
| sim.bin | Generate Random Sample from a DC Model |
| sim.sur | Generate Random Sample from an SUR Model |
| sim.varma | Generate Random Sample from a VARMA Model |
| summary.ldt.search | Summary for an 'ldt.search' object |
| summary.ldt.search.item | Summary for an 'ldt.search.item' object |