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RE: st: Time Series Poisson
From
Richard Williams <[email protected]>
To
[email protected]
Subject
RE: st: Time Series Poisson
Date
Sun, 30 Oct 2011 23:46:55 -0500
Thanks Cameron and Tirthankar. Many of these look
promising. To be clear, there is only 1 country
involved here, with separate records for each of
45 years. Some of these sources sound like they
might be designed for cross-sectional time series
rather than time series, but I don't understand
either well enough to really say. (And I am still
hoping for that nifty Stata-specific solution,
since I am not sure how far we will get if we
have to figure out how to program this ourselves!)
At 08:42 PM 10/30/2011, Cameron McIntosh wrote:
Hi Richard, Tirthankar
I might also suggest:
Oh, M.-S., & Lim, Y.B. (2001). Bayesian analysis
of time series Poisson data. Journal of Applied Statistics, 28(2), 259-271.
Drescher, D. (2008). Testing for presence of a
latent process in count series. Journal of
Statistical Computation and Simulation, 78(7), 595-607.
Jung, R.C., Kukuk, M., & Liesenfeld, R. (2006).
Time series of count data: modeling, estimation
and diagnostics. Computational Statistics & Data Analysis, 51(4), 2350-2364.
Jorgensen, B., Lundbye-Christensen, S., Song,
P.X-K., & Sun, Li. (1999). A State Space Model
for Multivariate Longitudinal Count Data. Biometrika, 86(1), 169-181.
Knape, J., Jonzén, N., Sköld, M., & Sokolov, L.
(2009). Multivariate state-space modelling of
bird migration count data. Environmental and
Ecological Statistics, 3(Section I), 59-79.
Knape et al. (2009) model a 54-year time series
of various bird species counts, your student
might follow their Bayesian strategy... I was
also thinking that it might be possible to fit a
latent growth curve or multilevel model to this
type of data, with Poisson links on the 45 indicators:
Liu, H. (2007). Growth Curve Models for
Zero-Inflated Count Data: An Application to
Smoking Behavior. Structural Equation Modeling, 14(2), 247-279.
Alosh, M. (2009). Modeling longitudinal count
data with dropouts. Pharmaceutical Statistics, 9(1), 35-45.
Min, Y., & Agresti, A. (2005). Random effect
models for repeated measures of zero-inflated
count data. Statistical Modelling, 5(1), 1-19.
Coelho-Barrosa, E.A., Achcar, J.A., & Mazucheli,
J. (2010). Longitudinal Poisson modeling: an
application for CD4 counting in HIV-infected
patients. Journal of Applied Statistics, 37(5), 865-880.
My two cents,
Cam
> Date: Sun, 30 Oct 2011 18:04:46 -0700
> Subject: Re: st: Time Series Poisson
> From: [email protected]
> To: [email protected]
>
> Richard,
>
> See chapter 4 in this book:
> http://amzn.com/0471363553
>
> T
>
>
> On Sun, Oct 30, 2011 at 6:53 PM, Richard Williams
> <[email protected]> wrote:
> > One of my students (a political scientist
of course -- they always bring up
> > these weird problems I have never
encountered myself!) has a data set that
> > consists of 45 yearly records for the
United States. The dependent variable
> > is a count. It sounded to me like the sort
of thing that should be analyzed
> > by a time series poisson model. But,
unfortunately, I wasn't even sure that
> > such a thing existed - I was hoping there was a tspoisson command, but no
> > such luck.
> >
> > However, I found this Stata Technical
Bulletin for a very old user-written
> > command called nwest.
http://www.stata.com/products/stb/journals/stb39.pdf.
> > It says "This article discusses the
calculation of standard errors that are
> > robust to heteroscedasticity and serial
correlation for probit, logit, and
> > poisson regression models."
> >
> > I also found this slightly newer post from 2003:
> > http://www.stata.com/statalist/archive/2003-06/msg00258.html.
> >
> > What I take from this is that he should -tsset- his data and use -glm- to
> > estimate a Poisson model with Newey-West standard errors, e.g. something
> > like
> >
> > glm y x1 x2 x3, family(poisson) link(log) vce(hac nwest)
> >
> > Does this sound right, and if so is this
the best he can do, at least with
> > Stata?
> >
> >
> > -------------------------------------------
> > Richard Williams, Notre Dame Dept of Sociology
> > OFFICE: (574)631-6668, (574)631-6463
> > HOME: (574)289-5227
> > EMAIL: [email protected]
> > WWW: http://www.nd.edu/~rwilliam
> >
> > *
> > * For searches and help try:
> > * http://www.stata.com/help.cgi?search
> > * http://www.stata.com/support/statalist/faq
> > * http://www.ats.ucla.edu/stat/stata/
> >
>
>
>
> --
> Tirthankar Chakravarty
> [email protected]
> [email protected]
>
> *
> * For searches and help try:
> * http://www.stata.com/help.cgi?search
> * http://www.stata.com/support/statalist/faq
> * http://www.ats.ucla.edu/stat/stata/
*
* For searches and help try:
* http://www.stata.com/help.cgi?search
* http://www.stata.com/support/statalist/faq
* http://www.ats.ucla.edu/stat/stata/
-------------------------------------------
Richard Williams, Notre Dame Dept of Sociology
OFFICE: (574)631-6668, (574)631-6463
HOME: (574)289-5227
EMAIL: [email protected]
WWW: http://www.nd.edu/~rwilliam
*
* For searches and help try:
* http://www.stata.com/help.cgi?search
* http://www.stata.com/support/statalist/faq
* http://www.ats.ucla.edu/stat/stata/