Testing a causal model (DAG) | Time series | References

Custom performance metrics with metricfunc | Regression: $R^2$ | Classification: balanced accuracy and Brier score | Custom learners with mlfunc | A linear model | Logistic regression with extra arguments | Any model from caret | Tips

Look at the null distribution | Number of Monte Carlo samples and parametric p-values | QQ-plot of p-values | Very high p-values | Failed model fits | Tuning the learner | Choosing the direction of the test | A checklist | References

The idea behind the test | A first test | The formula | Choosing the learner | Different types of data | Large data sets | References

Abstract | 1 Introduction | 2 Theory | 2.1 Algorithms | 2.2 On the use of PLSR and PCR | 3 Example session | 4 Formulas and data frames | 4.1 Formulas | 4.2 Data frames | 5 Fitting models | 6 Choosing the number of components with cross-validation | 7 Inspecting fitted models | 7.1 Plotting | 7.2 Extraction | 7.3 Summaries | 8 Predicting new observations | 9 Further topics | 9.1 Selecting fit algorithms | 9.1.1 Additional responses and focused loadings | 9.1.2 Missing data handling | 9.2 Parallel cross-validation | 9.3 Package design | 9.4 Calling fit functions directly | 9.5 Formula handling in more detail | References

Supervised methods | Formatting data for multiblock analyses | Multiblock Partial Least Squares - MB-PLS | Modelling | Summaries and plotting | Sparse Multiblock Partial Least Squares - sMB-PLS | Plotting | Sequential and orthogonalised PLS - SO-PLS | Måge plot | Loadings | Scores | Prediction | Validation | Principal Components of Predictions | CVANOVA | Parallel and Orthgonalised Partial Least Squares - PO-PLS | Scores and loadings | Response Oriented Sequential Alternation - ROSA | Image plots | Multiblock Redundancy Analysis - mbRDA | Loadings and scores

Unsupervised methods | Formatting data for multiblock data analysis | Method interfaces | Shared sample mode | Shared variable mode | Common output elements across methods | Scores and loadings | Plot from imported package

Complex data structures | L-PLS | Simulated L-shaped data | Exo-L-PLS | Endo-L-PLS | L-PLS cross-validation | SO-PLS Path Modelling | Single SO-PLS-PM model | Multiple paths in an SO-PLS-PM model

Read from file | Data pre-processing | Re-coding categorical data | Data structures for multiblock analysis | Create list of blocks | Create data.frame of blocks

Basic methods | Prepare data | Modelling | Common output elements across methods | Scores and loadings

ANOVA Simultaneous Component Analysis -- ASCA | Simulated data | Formula interface | ASCA modelling | Scores | Loadings

Introduction | Example | Probability mass | Testing | Simulated distribution