particle {Bmix} | R Documentation |
This interprets the .particle[i].[t].[rho].txt files generated by the mix function and outputs a data.frame of sufficient statistics and posterior predictive information. The demos illustrate how to use the output for posterior inference.
particle(i, mixobj, t, rho=0)
i |
Particle index. |
mixobj |
Object returned by the |
t |
Time index. |
rho |
BAR process correlation parameter. |
Returns a data.frame
with each row corresponding to a
mixture component (first is the base distribution). The first
column, n
, is the number of observations allocated to each
mixture component, the next set of columns are sufficient
statistics, column p
is the predictive probability for each
component, and the final columns are moments (and degrees of
freedom) for the student-t and multinomial posterior predictive
mixture densities.
Matt Taddy, matt.taddy@chicagobooth.edu
An auto-regressive mixture model for dynamic spatial Poisson processes: Application to tracking the intensity of violent crime (Taddy 2009),
and other papers at faculty.chicagobooth.edu/matt.taddy/research.
mix