particle: Reading particle files

Description Usage Arguments Value Author(s) References See Also

Description

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.

Usage

1
particle(i, mixobj, t, rho=0)

Arguments

i

Particle index.

mixobj

Object returned by the mix function.

t

Time index.

rho

BAR process correlation parameter.

Value

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.

Author(s)

Matt Taddy, matt.taddy@chicagobooth.edu

References

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.

See Also

mix


Bmix documentation built on May 1, 2019, 6:47 p.m.

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