Please don't repeat post. In fact, you should definitely read the Posting
Guide mentioned at the bottom if this or any other post from the list and
follow its advice.
The usual way to predict output of a model in R is to use the predict
function appropriate to your model object class. You might find reading the
help file ?predict.glm helpful. If not, then you might be needing to study
some more basic use cases of R so you can interpret the help files.
---------------------------------------------------------------------------
Jeff Newmiller The ..... ..... Go Live...
DCN:<jdnewmil at dcn.davis.ca.us> Basics: ##.#. ##.#. Live
Go...
Live: OO#.. Dead: OO#.. Playing
Research Engineer (Solar/Batteries O.O#. #.O#. with
/Software/Embedded Controllers) .OO#. .OO#. rocks...1k
---------------------------------------------------------------------------
Sent from my phone. Please excuse my brevity.
On August 14, 2014 10:54:17 PM PDT, DHIMAN BHADRA <dhimanbhadra at gmail.com>
wrote:
Dear all.
I am trying to relate daily deaths in a given city with air pollution
values. The model I am using is as follows:
model <- glm(deaths ~ pollution + ns(time, 13) + ns(temp, 7) + ns(rh,
5) +
dow + holiday, family=quasipoisson, data=city)
Where -
deaths: daily number of deaths
pollution: daily measured levels of air pollution
ns(time, 13): smooth function (i.e. cubic spline) of time with 13
degrees
of freedom
ns(temp, 7): smooth function (i.e. cubic spline) of temperature with 7
degrees of freedom
ns(rh, 5): smooth function (i.e. cubic spline) of humidity with 5
degrees
of freedom
dow: day of the week
holiday: dummy variable to indicate public holidays
Having run this model, how do I obtain predicted values of deaths for
any
given set of pollution values? Any suggestions will be much
appreciated.
Thanks in advance,
Dhiman Bhadra
Assistant professor.
IIM Ahmedabad.
[[alternative HTML version deleted]]