R: Arbitrary Dependency Mixed Multivariate Bayesian Models

# Arbitrary Dependency Mixed Multivariate Bayesian Models

## Documentation for package ‘mmb’ version 0.13.3

- DESCRIPTION file
- User guides, package vignettes and other documentation

## Help Pages

bayesCaret | Provides a caret-compatible wrapper around functionality for classification and regression, as implemented by mmb.
bayesComputeMarginalFactor | Compute a marginal factor (continuous or discrete random variable).
bayesConvertData | Convert data for usage within Bayesian models.
bayesFeaturesToSample | Transform a collection of Bayesian features back to a sample.
bayesInferSimple | Perform simple (network) Bayesian inferencing and regression.
bayesProbability | Full Bayesian inferencing for determining the probability or relative likelihood of a given value.
bayesProbabilityAssign | Assign probabilities to one or more samples, given some training data.
bayesProbabilityNaive | Naive Bayesian inferencing for determining the probability or relative likelihood of a given value.
bayesProbabilitySimple | Assign a probability using a simple (network) Bayesian classifier.
bayesRegress | Perform full-dependency Bayesian regression for a sample.
bayesRegressAssign | Regression for one or more samples, given some training data.
bayesRegressSimple | Perform simple (network) Bayesian regression.
bayesToLatex | Create a string that can be used in Latex in an e.g. equation-environment.
centralities | Given a neighborhood of data, computes the similarity of each sample in the neighborhood to the neighborhood.
conditionalDataMin | Segment data according to one or more random variables.
createFeatureForBayes | Create a Bayesian feature by name and value.
discretizeVariableToRanges | Discretize a continuous random variable to ranges/buckets.
distance | Given a neighborhood of data and two samples from that neighborhood, calculates the distance between the samples.
estimatePdf | Safe PDF estimation that works also for sparse random variables.
getDefaultRegressor | Get the system-wide default regressor.
getMessages | Get a boolean indicating whether messages are enabled system-wide.
getProbForDiscrete | Get a probability of a discrete value.
getRangeForDiscretizedValue | Get the range-/bucket-ID of a given value.
getValueKeyOfBayesFeatures | Obtain the type of the value of a Bayesian feature.
getValueOfBayesFeatures | Obtain the value of a Bayesian feature.
getWarnings | Get a boolean indicating whether warnings are enabled system-wide.
neighborhood | Given Bayesian features, returns those samples from a dataset that exhibit a similarity (i.e., the neighborhood).
sampleToBayesFeatures | Transform an entire sample into a collection of Bayesian features.
setDefaultRegressor | Set a system-wide default regressor.
setMessages | Enable or disable messages system-wide.
setWarnings | Enable or disable warnings system-wide.
vicinities | Segment a dataset by each row once, then compute vicinities of samples in the neighborhood.
vicinitiesForSample | Segment a dataset by a single sample and compute vicinities for it and the remaining samples in the neighborhood.