DGM1.7.4 package

Dynamic Graphical Models

binom.nettest

Performes a binomial test with FDR correction for network edge occurre...

center

Mean centers timeseries in a 2D array timeseries x nodes, i.e. each ti...

cor2adj

Threshold correlation matrix to match a given number of edges.

corTs

Mean correlation of time series across subjects.

dgm.group

A group is a list containing restructured data from subejcts for easie...

diag.delta

Quick diagnostics on delta.

dlm.lpl

Calculate the log predictive likelihood for a specified set of parents...

dlm.retro

Calculate the location and scale parameters for the time-varying coeff...

dlmLplCpp

C++ implementation of the dlm.lpl

exhaustive.search

A function for an exhaustive search, calculates the optimum value of t...

getAdjacency

Get adjacency and associated likelihoods (LPL) and disount factros (df...

getIncompleteNodes

Checks results and returns job number for incomplete nodes.

getModel

Extract specific parent model with assocated df and ME from complete m...

getModelNr

Get model number from a set of parents.

getWinner

Get winner network by maximazing log predictive likelihood (LPL) from ...

gplotMat

Plots network as adjacency matrix.

mergeModels

Merges forward and backward model store.

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.group

A group is a list containing restructured data from subejcts for easie...

patel

Patel.

perf

Performance of estimates, such as sensitivity, specificity, and more.

priors.spec

Specify the priors. Without inputs, defaults will be used.

prop.nettest

Comparing two population proportions on the network with FDR correctio...

pruning

Get pruned adjacency network.

rand.test

Randomization test for Patel's kappa. Creates a distribution of values...

read.subject

Reads single subject's network from txt files.

reshapeTs

Reshapes a 2D concatenated time series into 3D according to no. of sub...

rmdiag

Removes diagonal of NA's from matrix.

rmna

Removes NAs from matrix.

rmRecipLow

Removes reciprocal connections in the lower diagnoal of the network ma...

scaleTs

Scaling data. Zero centers and scales the nodes (SD=1).

stepwise.backward

Stepise backward non-exhaustive greedy search, calculates the optimum ...

stepwise.combine

Stepise combine

stepwise.forward

Stepise forward non-exhaustive greedy search, calculates the optimum v...

subject

Estimate subject's full network: runs exhaustive search on very node.

symmetric

Turns asymetric network into an symmetric network. Helper function to ...

ttest.nettest

Comparing connectivity strenght of two groups with FDR correction.

Dynamic graphical models for multivariate time series data to estimate directed dynamic networks in functional magnetic resonance imaging (fMRI), see Schwab et al. (2017) <doi:10.1016/j.neuroimage.2018.03.074>.

  • Maintainer: Simon Schwab
  • License: GPL-3
  • Last published: 2021-12-05