scoreEquations(R,U)
This function computes the score equations that arise from taking partial derivatives of the log-likelihood function of the concentration matrix (the inverse of the covariance matrix) of a Gaussian graphical statistical model and returns the ideal generated by such equations.
The input of this function is a gaussianRing and statistical data. The latter can be given as a matrix or a list of observations. The rows of the matrix or the elements of the list are observation vectors given as lists. It is possible to input the sample covariance matrix directly by using the optional input SampleData.
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SaturateOptions allows to use all functionalities of saturate (missing documentation) . Saturate determines whether to saturate. Note that the latter will not provide the score equations of the model.
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The ML-degree of the model is the degree of the score equations ideal. The ML-degree of the running example is 1:
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The object scoreEquations is a method function with options.
The source of this document is in /build/reproducible-path/macaulay2-1.25.05+ds/M2/Macaulay2/packages/GraphicalModelsMLE.m2:1115:0.