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| bootstrap | This method computes predicted outcome for each observation in the data frame using the tree model supplied as an input argument. |
| compute.acc | Predictive accuracy estimates across trees for logistic regression model |
| compute.mse | Predictive accuracy estimates (MSE) across trees for linear or poisson regression model. |
| compute.r2 | Predictive accuracy estimates across trees for linear or poisson regression |
| get.mf.object.glm | Fit a general linear model to a mobForest model |
| get.mf.object.lm | Fit a linear model to a mobForest model |
| get.pred.values | Get predictions summarized across trees for out-of-bag cases or all cases for cases from new test data |
| get.pred.values, | Class '"mobforest.output"' of mobforest model |
| get.varimp | Variable importance scores computed through random forest analysis |
| logical, | Class '"mobforest.output"' of mobforest model |
| logical-method | Class '"mobforest.output"' of mobforest model |
| logistic.acc | Contingency table: Predicted vs. Observed Outcomes |
| mob.rf.tree | Model based recursive partitioning - randomized subset of partition variables considered during each split. |
| mobfores.output, | Class '"mobforest.output"' of mobforest model |
| mobforest.analysis | Model-based random forest analysis |
| mobforest.control | Control parameters for random forest |
| mobforest.control-class | Class '"mobforest.control"' of mobForest model |
| mobforest.output | Model-based random forest object |
| mobforest.output, | Class '"mobforest.output"' of mobforest model |
| mobforest.output-class | Class '"mobforest.output"' of mobforest model |
| mobforest.output-method | Class '"mobforest.output"' of mobforest model |
| mobforest.output-method, | Class '"mobforest.output"' of mobforest model |
| mob_fit_checksplit | Utility Function. Taken from party package to remove ":::" warning |
| mob_fit_childweights | Utility Function. Taken from party package to remove ":::" warning |
| mob_fit_fluctests | Utility Function. Taken from party package to remove ":::" warning |
| mob_fit_getlevels | Utility Function. Taken from party package to remove ":::" warning |
| mob_fit_getobjfun | Utility Function. Taken from party package to remove ":::" warning |
| mob_fit_setupnode | Utility Function. Taken from party package to remove ":::" warning |
| mob_fit_splitnode | Utility Function. Taken from party package to remove ":::" warning |
| prediction.output | Predictions and predictive accuracy estimates |
| prediction.output-class | Class '"prediction.output"' of mobForest model |
| predictive.acc | Predictive performance across all trees |
| predictive.acc, | Class '"mobforest.output"' of mobforest model |
| print.estimates | Predictive Accuracy Report |
| residual.plot | Produces two plots: a) histogram of residuals, b) predicted Vs residuals. This feature is applicable only when linear regression is considered as the node model. |
| show-method | Class '"mobforest.output"' of mobforest model |
| string.formula | Model in the formula object converted to a character |
| tree.predictions | Predictions from tree model |
| varimp.output | Variable importance matrix containing the decrease in predictive accuracy after permuting the variables across all trees |
| varimp.output-class | Class '"varimp.output"' of mobforest model |
| varimplot | A plot with variable importance score on X-axis and variable name on Y-axis. |