Summarizing non- and semi-parametric multivariate mixture model fits
summary method for class npEM.
## S3 method for class 'npEM' summary(object, ...) ## S3 method for class 'summary.npEM' print(x, digits=3, ...)
object,x |
an object of class |
digits |
Significant digits for printing values |
... |
further arguments passed to or from other methods. |
summary.npEM prints means and variances of each block for
each component. These quantities might not be part of the model, but they
are estimated nonparametrically based on the posterior probabilities and the
data.
The function summary.npEM returns a list of type summary.npEM
with the following components:
n |
The number of observations |
m |
The number of mixture components |
B |
The number of blocks |
blockid |
The block ID (from 1 through B) for each of the coordinates
of the multivariate observations. The |
means |
A B x m matrix giving the estimated mean of each block in each component. |
variances |
Same as |
Benaglia, T., Chauveau, D., and Hunter, D. R. (2009), An EM-like algorithm for semi- and non-parametric estimation in multivariate mixtures, Journal of Computational and Graphical Statistics, 18(2), 505–526.
data(Waterdata) set.seed(100) ## Not run: a <- npEM(Waterdata[,3:10], 3, bw=4) # Assume indep but not iid summary(a) b <- npEM(Waterdata[,3:10], 3, bw=4, blockid=rep(1,8)) # Now assume iid summary(b) ## End(Not run)
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