Core computing function

EMtree(
  PLN.Cor,
  n = NULL,
  maxIter = 30,
  unlinked = NULL,
  random.init = FALSE,
  cond.tol = 1e-10,
  eps = 0.001,
  verbatim = TRUE,
  plot = FALSE
)

Arguments

PLN.Cor	Either an object resulting from the use of the `PLN` function from package `PLNmodels`, or an estimation of Gaussian data correlation matrix.
n	Number of samples, required if a correlation matrix is supplied
maxIter	Maximum number of iterations for EMtree
unlinked	An optional vector of nodes which are not linked with each other
random.init	A boolean for trying a random initialization of the EM
cond.tol	Tolerance parameter for the conditioning of psi matrix
eps	Precision parameter controlling the convergence of weights beta
verbatim	Talks if set to TRUE
plot	Plots likelihood if set to TRUE

Value

edges_prob: p x p matrix of edges probabilities
edges_weight: p x p matrix of edges weights for any spanning tree
logpY: vector of log-likelihoods
maxIter: final number of iterations EMtree has ran
timeEM: EMtree computation time
alpha: data signal/noise ratio

Examples

n=30
p=10
Y=data_from_scratch("tree",p=p)$data
PLN_Y = PLNmodels::PLN(Y~1)
#> 
#>  Initialization...
#>  Adjusting a PLN model with full covariance model
#>  Post-treatments...
#>  DONE!
EMtree(PLN.Cor=PLN_Y,verbatim=TRUE, plot=TRUE)
#> 
#> Convergence took 0.04 secs  and  4  iterations.
#> $edges_prob
#>               [,1]         [,2]         [,3]         [,4]         [,5]
#>  [1,] 0.000000e+00 2.703099e-05 9.999972e-01 1.815177e-09 1.254817e-07
#>  [2,] 2.703099e-05 0.000000e+00 9.999734e-01 2.864417e-07 2.395402e-10
#>  [3,] 9.999972e-01 9.999734e-01 0.000000e+00 4.093157e-08 1.129899e-10
#>  [4,] 1.815177e-09 2.864417e-07 4.093157e-08 0.000000e+00 1.000000e+00
#>  [5,] 1.254817e-07 2.395402e-10 1.129899e-10 1.000000e+00 0.000000e+00
#>  [6,] 2.589464e-14 2.860662e-07 1.089955e-12 9.999427e-01 6.680481e-11
#>  [7,] 1.824194e-09 9.999992e-01 7.284665e-09 2.695970e-11 2.171250e-13
#>  [8,] 2.764005e-14 1.200601e-08 2.039234e-12 9.999487e-01 9.657021e-10
#>  [9,] 4.264622e-06 7.227053e-08 9.999978e-01 1.427830e-09 2.324378e-12
#> [10,] 2.823114e-11 6.353540e-12 5.668745e-09 1.000000e+00 1.452511e-09
#>               [,6]         [,7]         [,8]         [,9]        [,10]
#>  [1,] 2.589464e-14 1.824194e-09 2.764005e-14 4.264622e-06 2.823114e-11
#>  [2,] 2.860662e-07 9.999992e-01 1.200601e-08 7.227053e-08 6.353540e-12
#>  [3,] 1.089955e-12 7.284665e-09 2.039234e-12 9.999978e-01 5.668745e-09
#>  [4,] 9.999427e-01 2.695970e-11 9.999487e-01 1.427830e-09 1.000000e+00
#>  [5,] 6.680481e-11 2.171250e-13 9.657021e-10 2.324378e-12 1.452511e-09
#>  [6,] 0.000000e+00 7.452400e-07 1.086028e-04 1.666670e-13 1.176126e-11
#>  [7,] 7.452400e-07 0.000000e+00 2.029631e-12 3.231531e-09 4.160184e-13
#>  [8,] 1.086028e-04 2.029631e-12 0.000000e+00 2.626290e-15 1.913354e-13
#>  [9,] 1.666670e-13 3.231531e-09 2.626290e-15 0.000000e+00 9.999994e-01
#> [10,] 1.176126e-11 4.160184e-13 1.913354e-13 9.999994e-01 0.000000e+00
#> 
#> $norm.cst
#> [1] 0.04574459
#> 
#> $timeEM
#> Time difference of 0.038028 secs
#> 
#> $edges_weight
#>               [,1]         [,2]         [,3]         [,4]         [,5]
#>  [1,] 0.0000000000 0.0014344900 0.6255184655 0.0003693756 0.0002273583
#>  [2,] 0.0014344900 0.0000000000 0.7326361332 0.0004523573 0.0002566469
#>  [3,] 0.6255184655 0.7326361332 0.0000000000 0.0006710738 0.0003488472
#>  [4,] 0.0003693756 0.0004523573 0.0006710738 0.0000000000 0.5636040088
#>  [5,] 0.0002273583 0.0002566469 0.0003488472 0.5636040088 0.0000000000
#>  [6,] 0.0002086555 0.0002655944 0.0003288846 0.7094018780 0.0003465707
#>  [7,] 0.0002580523 0.4808940308 0.0004837664 0.0002843805 0.0001806361
#>  [8,] 0.0002099167 0.0002476292 0.0003318501 0.7121271186 0.0003500244
#>  [9,] 0.0007781311 0.0006565140 0.8977009776 0.0008966172 0.0003901036
#> [10,] 0.0003995989 0.0004904984 0.0008707997 0.8627640017 0.0005090056
#>               [,6]         [,7]         [,8]         [,9]        [,10]
#>  [1,] 0.0002086555 0.0002580523 0.0002099167 0.0007781311 0.0003995989
#>  [2,] 0.0002655944 0.4808940308 0.0002476292 0.0006565140 0.0004904984
#>  [3,] 0.0003288846 0.0004837664 0.0003318501 0.8977009776 0.0008707997
#>  [4,] 0.7094018780 0.0002843805 0.7121271186 0.0008966172 0.8627640017
#>  [5,] 0.0003465707 0.0001806361 0.0003500244 0.0003901036 0.0005090056
#>  [6,] 0.0000000000 0.0002045982 0.0020975425 0.0003662526 0.0004698800
#>  [7,] 0.0002045982 0.0000000000 0.0001754051 0.0003445916 0.0002952816
#>  [8,] 0.0020975425 0.0001754051 0.0000000000 0.0003698229 0.0004756862
#>  [9,] 0.0003662526 0.0003445916 0.0003698229 0.0000000000 0.8826063532
#> [10,] 0.0004698800 0.0002952816 0.0004756862 0.8826063532 0.0000000000
#> 
#> $logpY
#> [1] 130.2054 130.7740 130.7780 130.7780
#> 
#> $maxIter
#> [1] 4
#>