EStep {GMCM} | R Documentation |
Functions to perform the expectation and maximization steps of the EM algorithm for an multivariate Gaussian mixture model.
EStep(x, theta)
MStep(x, kappa, meta.special.case = FALSE)
x |
A matrix of observations where rows corresponds to features and columns to experiments. |
theta |
A list of parameters formatted as described in
|
kappa |
A matrix where the (i,j)'th entry is the probability that
|
meta.special.case |
Logical. If |
EStep
returns a matrix of probabilities as kappa
above.
MStep
returns a list of parameters formatted as described in
rtheta
.
Anders Ellern Bilgrau <anders.ellern.bilgrau@gmail.com>
Li, Q., Brown, J. B. J. B., Huang, H., & Bickel, P. J. (2011). Measuring reproducibility of high-throughput experiments. The Annals of Applied Statistics, 5(3), 1752-1779. doi:10.1214/11-AOAS466
set.seed(1)
sim <- GMCM:::SimulateGMMData(n = 100)
x <- sim$z
true.theta <- sim$theta
init.theta <- GMCM:::rtheta() # Generate starting parameters
# Do one EM interation
es <- GMCM:::EStep(x, init.theta)
new.theta <- GMCM:::MStep(x, es)
# Compare current estimate with the true
new.theta
true.theta