[R] making sense of posterior statistics in the deal package

[Aaron Tarone]

Hello,
    I'm doing bayesian network analyses with the deal package.  I am at a loss for how to interpret output from the analysis (i.e. what is a good score, what is a bad score, which stats tell me what about the network edges/nodes).

Here is an example node with its posterior scores for all parent nodes.


------------------------------------------------------------
Conditional Posterior: Yp1| 3  4  5  6  9  11  12  15  18  
[[1]]
[[1]]$tau
              [,1]        [,2]       [,3]        [,4]       [,5]        [,6]
 [1,]  138.0000000 -201.944190 -61.827901 -29.5419149 11.7780877 -56.1691436
 [2,] -201.9441898  379.014299 101.336606  49.2886631 -9.5976678  99.0119458
 [3,]  -61.8279013  101.336606  55.301879  18.3175413  0.4718180  31.7741275
 [4,]  -29.5419149   49.288663  18.317541  18.5074653  0.7297184  14.7963722
 [5,]   11.7780877   -9.597668   0.471818   0.7297184 11.9705940  -0.1152971
 [6,]  -56.1691436   99.011946  31.774127  14.7963722 -0.1152971  33.0750507
 [7,]   11.8398168  -11.819652   2.372613   2.4241871  8.3525307  -0.5909911
 [8,]  -15.8233513   27.136706  13.261521  10.3380918  5.2238205  10.7721059
 [9,]  -63.0844071  112.477658  36.867027  18.7342207  1.8345119  32.6573681
[10,]   -0.9125676    0.892410   3.995155   3.3759532  5.2495044   4.8010982
             [,7]       [,8]       [,9]      [,10]
 [1,]  11.8398168 -15.823351 -63.084407 -0.9125676
 [2,] -11.8196521  27.136706 112.477658  0.8924099
 [3,]   2.3726129  13.261521  36.867027  3.9951552
 [4,]   2.4241871  10.338092  18.734221  3.3759532
 [5,]   8.3525307   5.223821   1.834512  5.2495044
 [6,]  -0.5909911  10.772106  32.657368  4.8010982
 [7,]  11.7576987   5.339882   1.364748  4.5801216
 [8,]   5.3398823  17.269931  14.659995  6.8871204
 [9,]   1.3647480  14.659995  43.586099  4.5549556
[10,]   4.5801216   6.887120   4.554956 11.1188844

[[1]]$phi
[1] 5.395758

[[1]]$mu
 [1] -0.151400686  0.459786917 -0.091988847 -0.009952914  0.074523419
 [6]  0.215198198 -0.010968581 -0.026347501  0.423837846 -0.018999184

[[1]]$rho
[1] 147

Any help you can give me is greatly appreciated.

Aaron Tarone


______________________________________
Aaron Tarone
Postdoctoral Research Associate
Molecular and Computational Biology Program
University of Southern California
atarone at usc.edu
(213) 740-3063