/// <summary>
/// Evidence message for VMP
/// </summary>
/// <param name="sample">Incoming message from 'sample'. Must be a proper distribution. If any element is uniform, the result will be uniform.</param>
/// <param name="probsTrue">Constant value for 'probsTrue'.</param>
/// <param name="MeanLog">Buffer 'MeanLog'.</param>
/// <param name="MeanLogOneMinus">Buffer 'MeanLogOneMinus'.</param>
/// <returns>Average of the factor's log-value across the given argument distributions</returns>
/// <remarks><para>
/// The formula for the result is <c>sum_(sample) p(sample) log(factor(sample,probsTrue))</c>.
/// Adding up these values across all factors and variables gives the log-evidence estimate for VMP.
/// </para></remarks>
/// <exception cref="ImproperMessageException"><paramref name="sample"/> is not a proper distribution</exception>
public static double AverageLogFactor([Proper] SparseBernoulliListBase sample, SparseVector probsTrue, SparseVector MeanLog, SparseVector MeanLogOneMinus)
{
return(AverageLogFactor(sample, SparseBetaList.PointMass(probsTrue), MeanLog, MeanLogOneMinus));
}
