Plot.MixReparametrized: plot of the MCMC output produced by K.MixReparametrized
In Ultimixt: Bayesian Analysis of Location-Scale Mixture Models using a Weakly Informative Prior

Description Usage Arguments Details Value Note Author(s) References See Also Examples

This is a generic function for a graphical rendering of the MCMC samples produced by K.MixReparametrized function. The function draws boxplots for unimodal variables and for multimodal arguments after clustering them by applying a k-means algorithm. It also plots line charts for other variables.

1	Plot.MixReparametrized(xobs, estimate)

`xobs`	vector of the observations
`estimate`	output of the K. MixReparametrized function

Boxplots are produced using the boxplot.default method.

The output of this function consists of

`boxplot`	three boxplots for the radial coordinates, the mean and the standard deviation of the mixture distribution, k boxplots for each of the mixture model weights, component means and component standard deviations.
`histogram`	an histogram of the observations against an overlaid curve of the density estimate, obtained by averaging over all mixtures corresponding to the MCMC draws,
`line chart`	line charts that report the evolution of the proposal scales and of the acceptance rates over the number of batch of 50 iterations.

The mixture density estimate is based on the draws simulated of the parameters obtained by K.MixReparametrized function.

Kaniav Kamary

Kamary, K., Lee, J.Y., and Robert, C.P. (2017) Weakly informative reparameterisation of location-scale mixtures. arXiv.

K.MixReparametrized

#data(faithful)
#xobs=faithful[,1]
#estimate=K.MixReparametrized(xobs, k=2, alpha0=.5, alpha=.5, Nsim=20000)
#plo=Plot.MixReparametrized(xobs, estimate)

Ultimixt documentation built on May 1, 2019, 10:56 p.m.