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mixtools (version 1.0.1)

summary.npEM: Summarizing non- and semi-parametric multivariate mixture model fits

Description

summary method for class npEM.

Usage

## S3 method for class 'npEM':
summary(object, \dots)
## S3 method for class 'summary.npEM':
print(x, digits=3, \dots)

Arguments

object,x
an object of class npEM such as a result of a call to npEM
digits
Significant digits for printing values
...
further arguments passed to or from other methods.

Value

  • The function summary.npEM returns a list of type summary.npEM with the following components:
  • nThe number of observations
  • mThe number of mixture components
  • BThe number of blocks
  • blockidThe block ID (from 1 through B) for each of the coordinates of the multivariate observations. The blockid component is of length $r$, the dimension of each observation.
  • meansA $B\times m$ matrix giving the estimated mean of each block in each component.
  • variancesSame as means but giving the estimated variances instead.

Details

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.

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 (to appear).

See Also

npEM, plot.npEM

Examples

Run this code
data(Waterdata)
set.seed(100)
a <- npEM(Waterdata, 3, bw=4) # Assume indep but not iid
summary(a) 

b <- npEM(Waterdata, 3, bw=4, blockid=rep(1,8)) # Now assume iid
summary(b)

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