gapsMapRun {CoGAPS} | R Documentation |
Backwards Compatibility with v2
gapsMapRun(D, S, FP, ABins = data.frame(), PBins = data.frame(), nFactor = 5, simulation_id = "simulation", nEquil = 1000, nSample = 1000, nOutR = 1000, output_atomic = FALSE, fixedMatrix = "P", fixedBinProbs = FALSE, fixedDomain = "N", sampleSnapshots = TRUE, numSnapshots = 100, alphaA = 0.01, nMaxA = 1e+05, max_gibbmass_paraA = 100, alphaP = 0.01, nMaxP = 1e+05, max_gibbmass_paraP = 100, seed = -1, messages = TRUE)
D |
data matrix |
S |
uncertainty matrix |
FP |
data.frame with rows giving fixed patterns for P |
ABins |
unused |
PBins |
unused |
nFactor |
number of patterns (basis vectors, metagenes), which must be greater than or equal to the number of rows of FP |
simulation_id |
unused |
nEquil |
number of iterations for burn-in |
nSample |
number of iterations for sampling |
nOutR |
number of output messages |
output_atomic |
unused |
fixedMatrix |
unused |
fixedBinProbs |
unused |
fixedDomain |
unused |
sampleSnapshots |
indicates if snapshots should be made |
numSnapshots |
how many snapshots to take |
alphaA |
sparsity parameter for A domain |
nMaxA |
unused |
max_gibbmass_paraA |
limit truncated normal to max size |
alphaP |
sparsity parameter for P domain |
nMaxP |
unused |
max_gibbmass_paraP |
limit truncated normal to max size |
seed |
a positive seed is used as-is, while any negative seed tells the algorithm to pick a seed based on the current time |
messages |
display progress messages |
... |
v2 style parameters |
list with A and P matrix estimates
data(SimpSim) nC <- ncol(SimpSim.D) patterns <- matrix(1:nC/nC, nrow=1, ncol=nC) result <- gapsMapRun(SimpSim.D, SimpSim.S, FP=patterns, nFactor=3)