Bayesian networks | Introduction | Example: Chest clinic | Building a Bayesian network | Queries to networks | A one--minute version of gRain | Specifying a Bayesian network | Setting evidence and querying a network | Setting evidence | Hints and shortcuts | Conditioning on evidence with zero probability | Hard and soft (likelihood) evidence | Hard evidence | Soft evidence (also called virtual evidence or likelihood evidence) | Building a network from data | Building a network from a known network | Building networks from data | Handling zeros in the data | Building a network from an unknown network | Extending networks to include other types of variables | Brute force computations and why they fail

Introduction | Kenward--Roger approach | Satterthwaite approach | Parametric bootstrap | Matrices for random effects

Introduction | Arrays/tables in R | Cross classified data - contingency tables | Defining arrays | Operations on arrays | Normalizing an array | Subsetting an array -- slicing | Collapsing and inflating arrays - tab_marg() and tab_expand() | Permuting an array -- tab_perm() | Equality - tab_equal() | Aligning - tab_align() | Multiplication, addition etc: $+$, $-$, $*$, $/$ | An array as a probability density - tabDist() | Miscellaneous - tab_sliceMult() | Examples | A Bayesian network | Iterative Proportional Scaling (IPS) | Some low level functions | cell2entry and entry2cell | next_cell() | next_cell_slice() and slice2entry() | fact_grid() - factorial grid | More about slicing

Graphical Interaction Models and the gRim package | Introduction | Introductory examples | A Discrete Model | Model specification shortcuts | Plotting models | A Continuous Model | A Mixed Model | Model editing - update() | Testing for conditional independence - ciTest() | Fundamental methods for inference | Testing for addition and deletion of edges | Finding edges | Testing several edges | Stepwise model selection | Backward search | Forward search | Backward and forward search | Fixing edges/terms in model as part of model selection | Further topics on models for contingency tables | Sparse Contingency Tables | Dimension of a log--linear model | A space--efficient implementation of IPS for contingency tables | testdelete() | testadd() | getInEdges() | getOutEdges() | Evaluating edges in the model | evalInEdges() | evalOutEdges() | Miscellaneous | The Model Object | Methods for model objects

Graphs and Conditional Independence | Introduction | Graphs | Undirected Graphs | Directed Acyclic Graphs | Mixed Graphs | Conditional Independence and Graphs | More About Graphs | Special Properties | Operations on Graphs in Different Representations

Introduction | Simulating a dataset | Using the waves argument | Using a fixed correlation matrix and the zcor argument