Man pages for neilbramley/acl_source
Functions for active causal learning
| acl | acl. |
| action | Generates the outcome of an intervention or observation of a... |
| cat_function | A Cat Function |
| choose_int | Get intervention values |
| choose_int.nl | Get intervention values |
| choose_int.nv | Choose intervention with your own choice of value function |
| choose_int.recursive | Get n-step-ahead intervention values |
| draw_graph | Uses igraph to draw graphs how I like them |
| draw_weighted_graph | Uses igraph to draw weighted graphs |
| error_bar | Creates error bars |
| generate_unfolding | Unfold a cyclic causal network |
| get_joint | Get joint probability distribution over all possible... |
| graph_cyclic | Is this graph cyclic |
| indi_like | Create likelihoods for a particular observation/intervention... |
| initialise_payoffs | Create a value matrix for utility calculations |
| likelihood | Create likelihood data.frame |
| likelihood_unfolding | Get log likelihood of a particular unfolded graph |
| my.graph.formula | A slight mod of graph.formul() from igraphs to avoid the... |
| num2bin | Turn numbers to binary |
| plotprog | A Cat Function |
| posterior_pairwise | Posterior distribution over two graphs given prior and an... |
| prior | Generate a prior |
| propagation | Propagation function |
| renyi_entropy | Computes Renyi entropy |
| repmat | Replicates a matrix m by n times |
| resave | Resave a rData file with all the previous stuff plus more |
| shannon_entropy | Computes Shannon entropy |
| similarity_joints | How similar are two joint probability distributions |
| tsallis_entropy | Computes Tsallis entropy |
| valid_proposals | Valid proposal space for a causal judgement |
| virility | Virility property of graphs |
