Description Usage Arguments Author(s)
EM algorithm to fit multivariate Guassian convolution problem.
1 2 | ultimate_deconvolution(x_mat, s_mat, v_mat, pi_vec, itermax = 500,
tol = 10^-5, plot_iter = FALSE, code = c("cpp", "R"))
|
x_mat |
A matrix of data. The rows index the observations and the columns index the variables. |
s_mat |
A matrix of variances (NOT standard deviations). The rows index the observations and the columns index the variables. |
v_mat |
A matrix of initial values for the low-rank mixture covariances. |
pi_vec |
A vector of initial values of the mixing proportions. |
itermax |
The maximum number of fixed-point iterations for the EM to run. |
tol |
The tolerance for the stopping criterion. The current stopping criterion is the ratio of successive likelihoods minus 1. |
plot_iter |
A logical. Should we plot the likelihood at
each step ( |
code |
Should we use the C++ code ( |
David Gerard
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