butools.dmap.MarginalMomentsFromDMRAP¶

butools.dmap.MarginalMomentsFromDMRAP()¶

Matlab:	moms = MarginalMomentsFromDMRAP(H, K, precision)
Mathematica:	moms = MarginalMomentsFromDMRAP[H, K, precision]
Python/Numpy:	moms = MarginalMomentsFromDMRAP(H, K, precision)

Returns the moments of the marginal distribution of a discrete marked rational arrival process.

Parameters:	H : list/cell of matrices of shape(M,M), length(N) The H0...HN matrices of the DMRAP K : int, optional Number of moments to compute. If K=0, 2*M-1 moments are computed. The default value is K=0. precision : double, optional Numerical precision for checking if the input is valid. The default value is 1e-14
Returns:	moms : row vector of doubles, length K The vector of moments.

Examples

For Matlab:

>>> H0 = [0.15, 0.2, 0.18; -0.23, 0.17, 0.22; 0.19, 0.15, 0.16];
>>> H1 = [0.01, 0.08, 0.16; 0.02, 0.2, 0.07; 0.02, 0.15, 0.17];
>>> H2 = [0.14, 0.07, 0.01; 0.19, 0.02, 0.34; 0.06, 0.1, 0];
>>> moms = MarginalMomentsFromDMRAP({H0, H1, H2});
>>> disp(moms);
       1.5948       3.4185       9.9595       37.742       177.13

For Mathematica:

>>> H0 = {{0.15, 0.2, 0.18},{-0.23, 0.17, 0.22},{0.19, 0.15, 0.16}};
>>> H1 = {{0.01, 0.08, 0.16},{0.02, 0.2, 0.07},{0.02, 0.15, 0.17}};
>>> H2 = {{0.14, 0.07, 0.01},{0.19, 0.02, 0.34},{0.06, 0.1, 0}};
>>> moms = MarginalMomentsFromDMRAP[{H0, H1, H2}];
>>> Print[moms];
{1.5947682612697014, 3.418532063993288, 9.959485592524356, 37.74236950164582, 177.12501064870213}

For Python/Numpy:

>>> H0 = ml.matrix([[0.15, 0.2, 0.18],[-0.23, 0.17, 0.22],[0.19, 0.15, 0.16]])
>>> H1 = ml.matrix([[0.01, 0.08, 0.16],[0.02, 0.2, 0.07],[0.02, 0.15, 0.17]])
>>> H2 = ml.matrix([[0.14, 0.07, 0.01],[0.19, 0.02, 0.34],[0.06, 0.1, 0]])
>>> moms = MarginalMomentsFromDMRAP([H0, H1, H2])
>>> print(moms)
[1.5947682612697014, 3.4185320639932879, 9.9594855925243557, 37.742369501645818, 177.12501064870213]