Automated Uncertainty Analysis
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Documentation for package ‘ldt’ version 0.3.2.1
Help Pages
| coefs.plot | Plot Estimation Results |
| coefs.table | Create Table of Coefficients |
| combineSearch | Combine More Than One 'ldtsearch' Objects |
| estim.bin | Estimate a Discrete Choice Model |
| estim.sur | Estimate a SUR Model |
| estim.varma | Estimate a VARMA Model |
| fan.plot | Create a fan plot from a matrix of distribution parameters |
| get.items.modelcheck | Set Options to Exclude a Model Subset |
| get.items.search | Specify the Purpose of the Model Search Process |
| get.options.lbfgs | Get Options for L-BFGS Optimization |
| get.options.metric | Get Options for Measuring Performance |
| 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.options.search | Get Extra Options for Model Search Process |
| get.varma.params | Split VARMA parameter into its Components |
| h.get.estim | Gets Estimation from Search Result |
| latex.matrix | Convert a matrix to LaTeX code |
| latex.variable.vector | Generate LaTeX code for a variable vector |
| print.ldtsearch | Prints the Output of a Search Process |
| rand.mnormal | Generate Random Samples from a Multivariate Normal Distribution |
| 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 | Search for Best Discrete-Choice Models |
| search.bin.stepwise | Step-wise Search for Best Discrete-Choice Models |
| search.sur | Search for Best SUR Models |
| search.sur.stepwise | Step-wise Search for Best SUR Models |
| search.varma | Search for Best VARMA Models |
| search.varma.stepwise | Step-wise Search for Best VARMA Models |
| Search_s | Stepwise estimation |
| 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.ldtsearch | Summarizes Model Search Output |
| to.data.frame | Get Data from Model Search Output |
| vig_data | Data for Vignettes (and Tests) |