Man pages for neilbramley/acl_source
Functions for active causal learning

aclacl.
actionGenerates the outcome of an intervention or observation of a...
cat_functionA Cat Function
choose_intGet intervention values
choose_int.nlGet intervention values
choose_int.nvChoose intervention with your own choice of value function
choose_int.recursiveGet n-step-ahead intervention values
draw_graphUses igraph to draw graphs how I like them
draw_weighted_graphUses igraph to draw weighted graphs
error_barCreates error bars
generate_unfoldingUnfold a cyclic causal network
get_jointGet joint probability distribution over all possible...
graph_cyclicIs this graph cyclic
indi_likeCreate likelihoods for a particular observation/intervention...
initialise_payoffsCreate a value matrix for utility calculations
likelihoodCreate likelihood data.frame
likelihood_unfoldingGet log likelihood of a particular unfolded graph
my.graph.formulaA slight mod of graph.formul() from igraphs to avoid the...
num2binTurn numbers to binary
plotprogA Cat Function
posterior_pairwisePosterior distribution over two graphs given prior and an...
priorGenerate a prior
propagationPropagation function
renyi_entropyComputes Renyi entropy
repmatReplicates a matrix m by n times
resaveResave a rData file with all the previous stuff plus more
shannon_entropyComputes Shannon entropy
similarity_jointsHow similar are two joint probability distributions
tsallis_entropyComputes Tsallis entropy
valid_proposalsValid proposal space for a causal judgement
virilityVirility property of graphs
neilbramley/acl_source documentation built on Feb. 4, 2018, 12:03 a.m.