abn-package | 'abn' Package |
abn.version | abn Version Information |
adg | Dataset related to average daily growth performance and... |
AIC.abnFit | Print AIC of objects of class 'abnFit' |
bern_bugs | Bugs code for Bernoulli response |
BIC.abnFit | Print BIC of objects of class 'abnFit' |
build.control | Control the iterations in 'buildScoreCache' |
buildScoreCache | Build a cache of goodness of fit metrics for each node in a... |
calc.node.inla.glm | Fit a given regression using INLA |
calc.node.inla.glmm | Fit a given regression using INLA |
categorical_bugs | Bugs code for Categorical response |
Cfunctions | Documentation of C Functions |
check.valid.buildControls | Simple check on the control parameters |
check.valid.dag | Set of simple commonsense validity checks on the directed... |
check.valid.data | Set of simple commonsense validity checks on the data.df and... |
check.valid.fitControls | Simple check on the control parameters |
check.valid.groups | Simple check on the grouping variable |
check.valid.parents | Set of simple checks on the given parent limits |
check.which.valid.nodes | Set of simple checks on the list given as parent limits |
coef.abnFit | Print coefficients of objects of class 'abnFit' |
compareDag | Compare two DAGs or EGs |
compareEG | Compare two DAGs or EGs |
createAbnDag | Make DAG of class "abnDag" |
discretization | Discretization of a Possibly Continuous Data Frame of Random... |
dot-onAttach | Prints start up message |
entropyData | Computes an Empirical Estimation of the Entropy from a Table... |
essentialGraph | Construct the essential graph |
eval.across.grid | function to get marginal across an equal grid |
ex0.dag.data | Synthetic validation data set for use with abn library... |
ex1.dag.data | Synthetic validation data set for use with abn library... |
ex2.dag.data | Synthetic validation data set for use with abn library... |
ex3.dag.data | Validation data set for use with abn library examples |
ex4.dag.data | Valdiation data set for use with abn library examples |
ex5.dag.data | Valdiation data set for use with abn library examples |
ex6.dag.data | Valdiation data set for use with abn library examples |
ex7.dag.data | Valdiation data set for use with abn library examples |
expit | expit of proportions |
expit_cpp | expit function |
factorial | Factorial |
factorial_fast | Fast Factorial |
family.abnFit | Print family of objects of class 'abnFit' |
FCV | Dataset related to Feline calicivirus infection among cats in... |
find.next.left.x | Find next X evaluation Point |
fitAbn | Fit an additive Bayesian network model |
fit.control | Control the iterations in 'fitAbn' |
forLoopContentFitBayes | Regress each node on its parents.#' |
formula_abn | Formula to adjacency matrix |
g2b2c_data | Toy Data Set for Examples in README |
g2pbcgrp | Toy Data Set for Examples in README |
gauss_bugs | Bugs code for Gaussian response |
getmarginals | Internal function called by 'fitAbn.bayes'. |
getMargsINLA | function to extract marginals from INLA output |
getModeVector | function to extract the mode from INLA output |
getMSEfromModes | Extract Standard Deviations from all Gaussian Nodes |
get.quantiles | function to extract quantiles from INLA output |
get.var.types | Create ordered vector with integers denoting the distribution |
infoDag | Compute standard information for a DAG. |
irls_binomial_cpp | Iterative Reweighed Least Square algorithm for Binomials |
irls_binomial_cpp_br | BR Iterative Reweighed Least Square algorithm for Binomials |
irls_binomial_cpp_fast | Fast Iterative Reweighed Least Square algorithm for Binomials |
irls_binomial_cpp_fast_br | Fast Br Iterative Reweighed Least Square algorithm for... |
irls_gaussian_cpp | Iterative Reweighed Least Square algorithm for Gaussians |
irls_gaussian_cpp_fast | Fast Iterative Reweighed Least Square algorithm for Gaussians |
irls_poisson_cpp | Iterative Reweighed Least Square algorithm for Poissons |
irls_poisson_cpp_fast | Fast Iterative Reweighed Least Square algorithm for Poissons |
linkStrength | Returns the strengths of the edge connections in a Bayesian... |
logit | Logit of proportions |
logit_cpp | logit functions |
logLik.abnFit | Print logLik of objects of class 'abnFit' |
makebugs | Make BUGS model from fitted DAG |
makebugsGroup | Make BUGS model from fitted DAG with grouping |
mb | Compute the Markov blanket |
mi_cpp | Mutual Information |
miData | Empirical Estimation of the Entropy from a Table of Counts |
modes2coefs | Convert modes to fitAbn.mle$coefs structure |
mostProbable | Find most probable DAG structure |
nobs.abnFit | Print number of observations of objects of class 'abnFit' |
odds | Probability to odds |
or | Odds Ratio from a matrix |
pigs.vienna | Dataset related to diseases present in 'finishing pigs',... |
plotAbn | Plot an ABN graphic |
plot.abnDag | Plots DAG from an object of class 'abnDag' |
plot.abnFit | Plot objects of class 'abnFit' |
plot.abnHeuristic | Plot objects of class 'abnHeuristic' |
plot.abnHillClimber | Plot objects of class 'abnHillClimber' |
plot.abnMostprobable | Plot objects of class 'abnMostprobable' |
pois_bugs | Bugs code for Poisson response |
print.abnCache | Print objects of class 'abnCache' |
print.abnDag | Print objects of class 'abnDag' |
print.abnFit | Print objects of class 'abnFit' |
print.abnHeuristic | Print objects of class 'abnHeuristic' |
print.abnHillClimber | Print objects of class 'abnHillClimber' |
print.abnMostprobable | Print objects of class 'abnMostprobable' |
rank_cpp | Rank of a matrix |
scoreContribution | Compute the score's contribution in a network of each... |
searchHeuristic | A family of heuristic algorithms that aims at finding high... |
searchHillClimber | Find high scoring directed acyclic graphs using heuristic... |
simulateAbn | Simulate data from a fitted additive Bayesian network. |
simulateDag | Simulate a DAG with with arbitrary arcs density |
skewness | Computes skewness of a distribution |
std.area.under.grid | Standard Area Under the Marginal |
strsplits | Recursive string splitting |
summary.abnDag | Prints summary statistics from an object of class 'abnDag' |
summary.abnFit | Print summary of objects of class 'abnFit' |
summary.abnMostprobable | Print summary of objects of class 'abnMostprobable' |
tidy.cache | tidy up cache |
toGraphviz | Convert a DAG into graphviz format |
validate_abnDag | Check for valid DAG of class 'abnDag' |
validate_dists | Check for valid distribution |
var33 | simulated dataset from a DAG comprising of 33 variables |
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