binom.nettest           Performes a binomial test with FDR correction
                        for network edges in an adjacency matrix.
center                  Mean centers timeseries in a 2D array
                        timeseries x nodes, i.e. each timeseries of
                        each node has mean of zero.
corTs                   Correlation of time series.
dlm.lpl                 Calculate the log predictive likelihood for a
                        specified set of parents and a fixed delta.
exhaustive.search       A function for an exhaustive search, calculates
                        the optimum value of the discount factor.
getAdjacency            Get adjacency and associated likelihoods (LPL)
                        and disount factros (df) of winning models.
getModel                Get specific parent model from all models.
getThreshAdj            Get thresholded adjacency network.
getWinner               Get winner network by maximazing log predictive
                        likelihood (LPL) from a set of models.
gplotMat                Plots network as adjacency matrix.
mdm.group               A group is a list containing restructured data
                        from subejcts for easier group analysis.
model.generator         A function to generate all the possible models.
myts                    Network simulation data.
node                    Runs exhaustive search on a single node and
                        saves results in txt file.
patel                   Patel.
patel.group             A group is a list containing restructured data
                        from subejcts for easier group analysis.
perf                    Performance of estimates, such as sensitivity,
                        specificity, and more.
perm.test               Permutation test for Patel's kappa. Creates a
                        distribution of values kappa under the null
                        hypothesis.
read.subject            Reads single subject's network from txt files.
reshapeTs               Reshapes a 2D concatenated time series into 3D
                        according to no. of subjects and volumes.
scaleTs                 Scaling data. Zero centers and scales the nodes
                        (SD=1).
subject                 Estimate subject's full network: runs
                        exhaustive search on very node.
utestdata               Results from v.1.0 for unit tests.
