dinvgamma

rinvgamma

buildXY

computePx

computeRho3

computeRho4

cp.birth

cp.computeAlpha

cp.death

cp.shift

hasSeg

init

main

PSRF

readDataTS

readInput

sampleBinit

sampleBxy

sampleDelta2

sampleK

sampleParms

sampleSig2

segment.update

segPos

updateSigMulti

segmentModel.postDist

plotSegmentModel.postDist

CPposition

fast.svd

nsmall.svd

PlotFunction

positive.svd

pseudoinverse

psmall.svd

ARTIVA-internal

Reversible Jump MCMC (RJ-MCMC)sampling for approximating the posterior
distribution of a time varying regulatory network, under the Auto Regressive TIme VArying
(ARTIVA) model (for a detailed description of the algorithm, see Lebre et al. BMC Systems
Biology, 2010). Starting from time-course gene expression measurements for a gene of
interest (referred to as "target gene") and a set of genes (referred to as "parent genes")
which may explain the expression of the target gene, the ARTIVA procedure identifies
temporal segments for which a set of interactions occur between the "parent genes" and the
"target gene". The time points that delimit the different temporal segments are referred to
as changepoints (CP).

ARTIVA-internal: Internal ARTIVA Functions

Description

Arguments

Details