summary.mvnpEM {mixtools} | R Documentation |
Summarizing Fits for Nonparametric Mixture Models with Conditionally Independent Multivariate Component Densities
Description
summary
method for class mvnpEM
.
Usage
## S3 method for class 'mvnpEM'
summary(object, ...)
## S3 method for class 'summary.mvnpEM'
print(x, digits=3, ...)
Arguments
object , x |
an object of class |
digits |
Significant digits for printing values |
... |
further arguments passed to or from other methods. |
Details
summary.mvnpEM
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.
Value
The function summary.mvnpEM
returns a list of type summary.mvnpEM
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 |
variances |
Same as |
References
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.
Chauveau, D., and Hoang, V. T. L. (2015), Nonparametric mixture models with conditionally independent multivariate component densities, Preprint under revision. https://hal.archives-ouvertes.fr/hal-01094837
See Also
Examples
# Example as in Chauveau and Hoang (2015) with 6 coordinates
## Not run:
m=2; r=6; blockid <-c(1,1,2,2,3,3) # 3 bivariate blocks
# generate some data x ...
a <- mvnpEM(x, mu0=2, blockid, samebw=F) # adaptive bandwidth
plot(a) # this S3 method produces 6 plots of univariate marginals
summary(a)
## End(Not run)