Description Usage Arguments Value
Auxiliary function for flowReMix
fitting. Can be
used to generate an appropriate object for modifying the fitting process of
the stochastic EM algorithm used by flowReMix
.
1 2 3 4 5 6 7 8 9 10 | flowReMix_control(updateLag = 10, randomAssignProb = 1e-08, nsamp = 50,
lastSample = NULL, initMHcoef = 2.5, nPosteriors = 3,
maxDispersion = 10^3, minDispersion = 10^7, isingInit = -4.59512,
keepEach = 5, centerCovariance = FALSE, intSampSize = 100,
initMethod = "robust", ncores = NULL, preAssignCoefs = 1,
markovChainEM = TRUE, seed = 100, prior = 0, isingWprior = TRUE,
zeroPosteriorProbs = FALSE, clusterType = c("AUTO", "FORK", "SOCK"),
isingStabilityReps = 200, randStabilityReps = 0, stabilityGamma = 0.9,
stabilityAND = TRUE, learningRate = 0.6, keepWeightPercent = 0.9,
sampleNew = FALSE, subsetDiscardThreshold = 0, threads = NULL)
|
updateLag |
number of iterations before the algorithm is assumed to converge, at which time the parameter estimates will be aggregated. |
randomAssignProb |
an optional parameter for adding noise to the cluster assignments generated by the Gibbs sampler. Should only be changed if ising model estimates are unstable. |
nsamp |
number of Gibbs/componentwise MH cycles to perform for each subject. Must be larger than keepEach. |
lastSample |
how many samples to keep from the final iteration. |
initMHcoef |
the initial value for the shrinkage/inflation to perform on the estimated covariance in the componentwise MH sampler. The initial value does not matter much as this parameter self-tunes as the algorithm runs and usually converges to a good value within a few iterations. |
nPosteriors |
number of posterior samples to take per subject. If left
as |
maxDispersion |
the maximum overdispersion level allowed. The lower the value of the variable the more overdispersion is allowed. Must be larger than 0. |
minDispersion |
the minimum overdispersion allowed. The larger the value of the variable the less overdispersion is allowed. |
isingInit |
initialize the Ising model with this value. |
keepEach |
one out of how many Gibbs/MH samples to keep. This is used to reduce the dependence between posterior samples. |
centerCovariance |
whether to center random effect estimates before computing the covariance estimate or not. |
intSampSize |
number of importance samples to take when performing univariate numerical integration in the Gibbs sampler. |
initMethod |
the method used to initialize the regression coefficients.
Options are either "sparse" for |
ncores |
The number of cpu cores to use to fit the model in parallel. |
preAssignCoefs |
coefficients to multiply the posterior probabilities. 0 is a hard assignment and observations that are designated non-responders based on pu > ps will have posterior probabilities of 0. > 0 is a soft assignment, and a prior will be placed on the prior probability of non-response in the Ising model. |
markovChainEM |
|
seed |
|
prior |
|
isingWprior |
|
zeroPosteriorProbs |
boolean. |
clusterType |
|
sampleNew |
|
An object of type flowReMix_control
.
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