plotScatter: Produces Scatter Plots of MCMC Draws

In bayesMCClust: Mixtures-of-Experts Markov Chain Clustering and Dirichlet Multinomial Clustering

Description

Produces three scatter plots of MCMC draws of selected transition probabilities over all clusters/groups.

Usage

plotScatter(outList, thin = 1, xi11 = c(1, 1), xi12 = c(2, 2), 
            xi21 = c(2, 2), xi22 = c(3, 3), 
            xi31 = c(1, 1), xi32 = c(3, 3))

Arguments

outList	specifies a list containing the outcome (return value) of an MCMC run of mcClust, dmClust, mcClustExtended or dmClustExtended.
thin	An integer specifying the thinning parameter (default is 1).
xi11	A vector with 2 (valid) integers specifying j and k of ξ_{.,j,k}, the transition probability to use on the x-axis of the first plot.
xi12	A vector with 2 (valid) integers specifying j and k of ξ_{.,j,k}, the transition probability to use on the y-axis of the first plot.
xi21	A vector with 2 (valid) integers specifying j and k of ξ_{.,j,k}, the transition probability to use on the x-axis of the second plot.
xi22	A vector with 2 (valid) integers specifying j and k of ξ_{.,j,k}, the transition probability to use on the y-axis of the second plot.
xi31	A vector with 2 (valid) integers specifying j and k of ξ_{.,j,k}, the transition probability to use on the x-axis of the third plot.
xi32	A vector with 2 (valid) integers specifying j and k of ξ_{.,j,k}, the transition probability to use on the y-axis of the third plot.

Value

No value returned.

Note

Note, that in contrast to the literature (see References), the numbering (labelling) of the states of the categorical outcome variable (time series) in this package is sometimes 0,...,K (instead of 1,...,K), however, there are K+1 categories (states)!

Author(s)

Christoph Pamminger <[e-mail]>

References

Sylvia Fruehwirth-Schnatter, Christoph Pamminger, Andrea Weber and Rudolf Winter-Ebmer, (2011), "Labor market entry and earnings dynamics: Bayesian inference using mixtures-of-experts Markov chain clustering". Journal of Applied Econometrics. DOI: 10.1002/jae.1249 http://onlinelibrary.wiley.com/doi/10.1002/jae.1249/abstract

Christoph Pamminger and Sylvia Fruehwirth-Schnatter, (2010), "Model-based Clustering of Categorical Time Series". Bayesian Analysis, Vol. 5, No. 2, pp. 345-368. DOI: 10.1214/10-BA606 http://ba.stat.cmu.edu/journal/2010/vol05/issue02/pamminger.pdf

See Also

mcClust, dmClust, mcClustExtended, dmClustExtended

Examples

# please run the examples in mcClust, dmClust, mcClustExtended 
# and/or dmClustExtended

bayesMCClust documentation built on May 29, 2017, 3:31 p.m.