| binom.nettest | Performes a binomial test with FDR correction for network... |
| center | Mean centers timeseries in a 2D array timeseries x nodes,... |
| corTs | Correlation of time series. |
| dlm.lpl | Calculate the log predictive likelihood for a specified set... |
| dlmLplCpp | C++ implementation of the dlm.lpl |
| exhaustive.search | A function for an exhaustive search, calculates the optimum... |
| getAdjacency | Get adjacency and associated likelihoods (LPL) and disount... |
| getModel | Get specific parent model from all models. |
| getThreshAdj | Get thresholded adjacency network. |
| getWinner | Get winner network by maximazing log predictive likelihood... |
| gplotMat | Plots network as adjacency matrix. |
| mdm.group | A group is a list containing restructured data from subejcts... |
| 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... |
| patel | Patel. |
| patel.group | A group is a list containing restructured data from subejcts... |
| perf | Performance of estimates, such as sensitivity, specificity,... |
| perm.test | Permutation test for Patel's kappa. Creates a distribution of... |
| priors.spec | Specify the priors. Without inputs, defaults will be used. |
| read.subject | Reads single subject's network from txt files. |
| reshapeTs | Reshapes a 2D concatenated time series into 3D according to... |
| rmdiag | Removes diagnoal from matrix with NAs. |
| rmna | Removes NAs from matrix. |
| scaleTs | Scaling data. Zero centers and scales the nodes (SD=1). |
| stepwise.backward | Stepise backward non-exhaustive greedy search, calculates the... |
| stepwise.combine | Stepise combine: combines the stepwise forward and the... |
| stepwise.forward | Stepise forward non-exhaustive greedy search, calculates the... |
| subject | Estimate subject's full network: runs exhaustive search on... |
| utestdata | Results from v.1.0 for unit tests. |
