mml_fixed_str_adaptive: MML for a fixed Markov blanket model using adaptive code...
In kelvinyangli/mbmml: Learn Markov blankets using Minimum Message Length

This function calculates the mml score of the target under a fixed Markov blanket model. The structure can be a general DAG. This returns the message length without stating the mml estimate of the parameters.

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mml_fixed_str_adaptive(data, vars, arities, sampleSize, targetIndex,
  logProbTarget, cachedPXGivenT, probsMtx, str, mbIndices, cachedPXGivenY,
  cachInd)

`data`	A dataset whost variables are in numeric/integer format. Any categorical variables must be converted into numeric/integer first.
`vars`	A vector of all variables in data, in the same order as the column names of data.
`arities`	A vector of variable arities in data, in the same order as the column names of data.
`sampleSize`	The sample size. That is, the number of rows of data.
`targetIndex`	The target node's index in vars, whose Markov blanket we are interested in.
`logProbTarget`	Log of the probability of the target.
`cachedPXGivenT`	cachedPXGivenT
`probsMtx`	probsMtx
`str`	A fixed Markov blanket model stores in the bnlearn dag format.
`mbIndices`	The indices of potential Markov blanket variables.
`cachedPXGivenY`	cachedPXGivenY
`cachInd`	cachInd