Man pages for tmlenet
Targeted Maximum Likelihood Estimation for Network Data
| BinDat | R6 class for storing the design matrix and binary outcome for... |
| BinOutModel | R6 class for fitting and making predictions for a single... |
| CategorSummaryModel | R6 class for fitting and predicting joint probability for a... |
| ContinSummaryModel | R6 class for fitting and predicting joint probability for a... |
| DatNet | R6 class for storing and managing already evaluated summary... |
| DatNet.sWsA | R6 class for storing and managing the combined summary... |
| DefineSummariesClass | R6 class for parsing and evaluating user-specified summary... |
| Define_sVar | R6 class for parsing and evaluating node R expressions. |
| def.sW | Define Summary Measures sA and sW |
| df_netKmax2 | An example of a row-dependent dataset with known network of... |
| df_netKmax6 | An example of a row-dependent dataset with known network of... |
| eval.summaries | Evaluate Summary Measures sA and sW |
| mcEvalPsi | R6 class for Monte-Carlo evaluation of various substitution... |
| NetInd_mat_Kmax6 | An example of a network ID matrix |
| print_tmlenet_opts | Print Current Option Settings for 'tmlenet' |
| RegressionClass | R6 class that defines regression models evaluating P(sA|sW),... |
| SummariesModel | R6 class for fitting and predicting model P(sA|sW) under... |
| tmlenet | Estimate Average Network Effects For Arbitrary (Stochastic)... |
| tmlenet_options | Setting Options for 'tmlenet' |
| tmlenet-package | Targeted Maximum Likelihood Estimation for Network Data |
