Introduction | Lower Triangular Matrices | Marginal and Conditional Normal Distributions | Multivariate Normal Log-likelihoods | Maximum-likelihood Example | Continuous-discrete Likelihoods | Unstructured Gaussian Copula Estimation | Joint Mean and Covariance Estimation | User Interface | Reduced Rank Covariance Matrices | Package Infrastructure

Introduction | 1. A Simple Example | 2. Details | 3. Applications | References

INTRODUCTION | A CONCEPTUAL LEGO SYSTEM | PLAYING LEGO | DISCUSSION

Introduction | Permutation Tests | Illustrations and Applications | Quality Assurance | Acknowledgements

Introduction | Permutation tests in a nutshell | A class structure for permutation tests | Interfaces to permutation inference | Permutation tests in practice: A categorical data example | Odds and ends | Expectation and covariance

Objectives | Maximum Test | Illustration and Application | Simulation Experiments | Computational Details | Conclusions | Acknowledgements | Example Analyses

Introduction | R Code | C Code | Package Infrastructure

INTRODUCTION | A CONCEPTUAL LEGO SYSTEM | PLAYING LEGO | DISCUSSION

Objectives | Maximum Test | Illustration and Application | Simulation Experiments | Computational Details | Conclusions | Acknowledgements | Example Analyses

Introduction | Permutation Tests | Illustrations and Applications | Quality Assurance | Acknowledgements

Introduction | Permutation tests in a nutshell | A class structure for permutation tests | Interfaces to permutation inference | Permutation tests in practice: A categorical data example | Odds and ends | Expectation and covariance

Motivation | The model-based recursive partitioning algorithm | Illustrations | Conclusion

Introduction | Recursive binary partitioning | Recursive partitioning by conditional inference | Examples | Illustrations and applications

Motivation | The model-based recursive partitioning algorithm | Illustrations | Conclusion

Introduction | Recursive binary partitioning | Recursive partitioning by conditional inference | Examples | Illustrations and applications

Simple Examples | Multiple Comparison Procedures | Two-way ANOVA | Test Procedures | Quality Assurance

Introduction | Model and Parameters | Global and Simultaneous Inference | Applications | Implementation | Illustrations | Conclusion

Ordinal regression: The cumulative Logit Model | Variable Selection according to Pollet and Nettle | Stepwise Backward Selection | Variable Selection by Simultaneous Inference

Simple Examples | Multiple Comparison Procedures | Two-way ANOVA | Test Procedures | Quality Assurance

Introduction | Model and Parameters | Global and Simultaneous Inference | Applications | Implementation | Illustrations | Conclusion

Ordinal regression: The cumulative Logit Model | Variable Selection according to Pollet and Nettle | Stepwise Backward Selection | Variable Selection by Simultaneous Inference

Classes and methods | Coercing tree objects | Growing a simple classification tree | Predictions | Conclusion

Overview | Introduction | Recursive binary partitioning | Recursive partitioning by conditional inference | Examples | Illustrations and applications | Backward compatibility and novel functionality

Overview | MOB: Model-based recursive partitioning | A new implementation in R | Illustrations | Setting up a new mobster | Conclusion

Overview | Motivating example | Technical details | Summary

Maternal Characteristics | Statistical Analysis

Introduction | Specifying Transformation Models | Most Likely Transformations | Transformation Analysis | Classical Likelihood Inference | Simulation-based Likelihood Inference | Summary | The variables Package | The basefun Package | The mlt Package

Overview | Design and Implementation | User Interface by Example | Overview on 2.0 Series Features

Introduction | A Brief Theoretical Overview of Component-Wise Gradient Boosting | The Package mboost | Summary

Illustrations and Applications

Illustrations

Introduction | Glaucoma | Bagging | Indirect Classification | Error Rate Estimation | Summary