Re: [R] joint estimation of two poisson equations

2011-02-20 Thread danielepippo

Hi,
  I have the same problem to find out the standard errors of the parameter
in the same package you have used. 
I couldn't find out how to get standard errors and p-values from the 
package, so I bootstrapped them.
Can you explain your method to find out the standard errors with the
bootstrap method?


Thanks a lot

-- 
View this message in context: 
http://r.789695.n4.nabble.com/joint-estimation-of-two-poisson-equations-tp894847p3315520.html
Sent from the R help mailing list archive at Nabble.com.

__
R-help@r-project.org mailing list
https://stat.ethz.ch/mailman/listinfo/r-help
PLEASE do read the posting guide http://www.R-project.org/posting-guide.html
and provide commented, minimal, self-contained, reproducible code.


Re: [R] joint estimation of two poisson equations

2009-06-19 Thread ryusuke



ryusuke wrote:
> 
> 
> 
> Owen Powell-2 wrote:
>> 
>> Thanks Tirthankar, that did the trick.
>> Here's the solution to my problem using the "bivpois" package:
>> 
>> rm(list = ls())
>> library(bivpois)
>> 
>> y1 = c(1,2,3,4,4,3)
>> y2 = c(0,2,0,2,3,5)
>> x1 = c(2,3,4,8,1,3)
>> x2 = c(3,5,6,7,8,9)
>> d = data.frame(cbind(y1, y2, x))
>> 
>> eq1 = y1 ~ x1 + x2
>> eq2 = y2 ~ x1 + x2
>> 
>> out = lm.pb(eq1, eq2, data = d, zeroL3 = TRUE)
>> print(out)
>> 
>> I couldn't find out how to get standard errors and p-values from the
>> package, so I bootstrapped them.
>> 
>> ~Owen
>> 
>> 2009/4/13 Tirthankar Chakravarty 
>> 
>>> You should probably try the -bivpois- package:
>>> http://cran.r-project.org/web/packages/bivpois/index.html
>>>
>>> A very good discussion of multivariate Poissons, negative binomials
>>> etc. can be found in Chapter 7 of Rainer Winkelmann's book
>>> "Econometric Analysis of Count Data" (Springer 2008). Most of the
>>> likelihoods involved are fairly straightforward.
>>>
>>> T
>>>
>>> On Mon, Apr 13, 2009 at 9:32 AM, Owen Powell  wrote:
>>> > Dear list members,
>>> >
>>> > Is there a package somewhere for jointly estimating two poisson
>>> processes?
>>> >
>>> > I think the closest I've come is using the "SUR" option in the Zelig
>>> > package (see below), but when I try the "poisson" option instead of
>>> > the "SUR" optioin I get an error (error given below, and indeed,
>>> > reading the documentation of the Zelig package, I get the impression
>>> > "poisson" was not meant to handle a system of equations).
>>> >
>>> > I think I could do it myself by constructing the likelihood function
>>> > and then applying ML, but I'd prefer to avoid doing that unless it's
>>> > entirely necessary.
>>> >
>>> > I'll post my solution to the list when I've worked it out.
>>> >
>>> > Regards,
>>> >
>>> > ~Owen
>>> >
>>> > # CODE FOR "sur" OPTION
>>> > rm(list = ls())
>>> > library(Zelig)
>>> >
>>> > y1 = c(1,2,3,4)
>>> > y2 = c(0,2,0,2)
>>> > x = c(2,3,4,8)
>>> > d = data.frame(cbind(y1, y2, x))
>>> >
>>> > eq1 = y1 ~ x
>>> > eq2 = y2 ~ x
>>> > eqSystem = list (eq1, eq2)
>>> >
>>> > system_out = zelig(formula = eqSystem, model = "sur", data = d)
>>> > summary(system_out)
>>> >
>>> > -
>>> >
>>> > # ERROR FROM REPLACING "sur" WITH "poisson"
>>> > Error in switch(mode(x), `NULL` = structure(NULL, class = "formula"), 
>>> :
>>> >  invalid formula
>>> >
>>> > --
>>> > Owen Powell
>>> > http://center.uvt.nl/phd_stud/powell
>>> >
>>> > __
>>> > R-help@r-project.org mailing list
>>> > https://stat.ethz.ch/mailman/listinfo/r-help
>>> > PLEASE do read the posting guide
>>> http://www.R-project.org/posting-guide.html
>>> > and provide commented, minimal, self-contained, reproducible code.
>>> >
>>>
>>>
>>>
>>> --
>>> To every ù-consistent recursive class ê of formulae there correspond
>>> recursive class signs r, such that neither v Gen r nor Neg(v Gen r)
>>> belongs to Flg(ê) (where v is the free variable of r).
>>>
>> 
>> 
>> 
>> -- 
>> Owen Powell
>> http://center.uvt.nl/phd_stud/powell
>> 
>>  [[alternative HTML version deleted]]
>> 
>> 
>> __
>> R-help@r-project.org mailing list
>> https://stat.ethz.ch/mailman/listinfo/r-help
>> PLEASE do read the posting guide
>> http://www.R-project.org/posting-guide.html
>> and provide commented, minimal, self-contained, reproducible code.
>> 
>> 
> 
> I would like to know the bivpois coding and write a same function in VBA
> Excel, anyone gonna good suggestion?
> 
http://www.nabble.com/file/p24115406/%257Ebivpois%257E.txt %7Ebivpois%7E.txt 
-- 
View this message in context: 
http://www.nabble.com/joint-estimation-of-two-poisson-equations-tp23019442p24115406.html
Sent from the R help mailing list archive at Nabble.com.

__
R-help@r-project.org mailing list
https://stat.ethz.ch/mailman/listinfo/r-help
PLEASE do read the posting guide http://www.R-project.org/posting-guide.html
and provide commented, minimal, self-contained, reproducible code.


Re: [R] joint estimation of two poisson equations

2009-04-13 Thread Owen Powell
Thanks Tirthankar, that did the trick.
Here's the solution to my problem using the "bivpois" package:

rm(list = ls())
library(bivpois)

y1 = c(1,2,3,4,4,3)
y2 = c(0,2,0,2,3,5)
x1 = c(2,3,4,8,1,3)
x2 = c(3,5,6,7,8,9)
d = data.frame(cbind(y1, y2, x))

eq1 = y1 ~ x1 + x2
eq2 = y2 ~ x1 + x2

out = lm.pb(eq1, eq2, data = d, zeroL3 = TRUE)
print(out)

I couldn't find out how to get standard errors and p-values from the
package, so I bootstrapped them.

~Owen

2009/4/13 Tirthankar Chakravarty 

> You should probably try the -bivpois- package:
> http://cran.r-project.org/web/packages/bivpois/index.html
>
> A very good discussion of multivariate Poissons, negative binomials
> etc. can be found in Chapter 7 of Rainer Winkelmann's book
> "Econometric Analysis of Count Data" (Springer 2008). Most of the
> likelihoods involved are fairly straightforward.
>
> T
>
> On Mon, Apr 13, 2009 at 9:32 AM, Owen Powell  wrote:
> > Dear list members,
> >
> > Is there a package somewhere for jointly estimating two poisson
> processes?
> >
> > I think the closest I've come is using the "SUR" option in the Zelig
> > package (see below), but when I try the "poisson" option instead of
> > the "SUR" optioin I get an error (error given below, and indeed,
> > reading the documentation of the Zelig package, I get the impression
> > "poisson" was not meant to handle a system of equations).
> >
> > I think I could do it myself by constructing the likelihood function
> > and then applying ML, but I'd prefer to avoid doing that unless it's
> > entirely necessary.
> >
> > I'll post my solution to the list when I've worked it out.
> >
> > Regards,
> >
> > ~Owen
> >
> > # CODE FOR "sur" OPTION
> > rm(list = ls())
> > library(Zelig)
> >
> > y1 = c(1,2,3,4)
> > y2 = c(0,2,0,2)
> > x = c(2,3,4,8)
> > d = data.frame(cbind(y1, y2, x))
> >
> > eq1 = y1 ~ x
> > eq2 = y2 ~ x
> > eqSystem = list (eq1, eq2)
> >
> > system_out = zelig(formula = eqSystem, model = "sur", data = d)
> > summary(system_out)
> >
> > -
> >
> > # ERROR FROM REPLACING "sur" WITH "poisson"
> > Error in switch(mode(x), `NULL` = structure(NULL, class = "formula"),  :
> >  invalid formula
> >
> > --
> > Owen Powell
> > http://center.uvt.nl/phd_stud/powell
> >
> > __
> > R-help@r-project.org mailing list
> > https://stat.ethz.ch/mailman/listinfo/r-help
> > PLEASE do read the posting guide
> http://www.R-project.org/posting-guide.html
> > and provide commented, minimal, self-contained, reproducible code.
> >
>
>
>
> --
> To every ù-consistent recursive class ê of formulae there correspond
> recursive class signs r, such that neither v Gen r nor Neg(v Gen r)
> belongs to Flg(ê) (where v is the free variable of r).
>



-- 
Owen Powell
http://center.uvt.nl/phd_stud/powell

[[alternative HTML version deleted]]

__
R-help@r-project.org mailing list
https://stat.ethz.ch/mailman/listinfo/r-help
PLEASE do read the posting guide http://www.R-project.org/posting-guide.html
and provide commented, minimal, self-contained, reproducible code.


Re: [R] joint estimation of two poisson equations

2009-04-13 Thread Tirthankar Chakravarty
You should probably try the -bivpois- package:
http://cran.r-project.org/web/packages/bivpois/index.html

A very good discussion of multivariate Poissons, negative binomials
etc. can be found in Chapter 7 of Rainer Winkelmann's book
"Econometric Analysis of Count Data" (Springer 2008). Most of the
likelihoods involved are fairly straightforward.

T

On Mon, Apr 13, 2009 at 9:32 AM, Owen Powell  wrote:
> Dear list members,
>
> Is there a package somewhere for jointly estimating two poisson processes?
>
> I think the closest I've come is using the "SUR" option in the Zelig
> package (see below), but when I try the "poisson" option instead of
> the "SUR" optioin I get an error (error given below, and indeed,
> reading the documentation of the Zelig package, I get the impression
> "poisson" was not meant to handle a system of equations).
>
> I think I could do it myself by constructing the likelihood function
> and then applying ML, but I'd prefer to avoid doing that unless it's
> entirely necessary.
>
> I'll post my solution to the list when I've worked it out.
>
> Regards,
>
> ~Owen
>
> # CODE FOR "sur" OPTION
> rm(list = ls())
> library(Zelig)
>
> y1 = c(1,2,3,4)
> y2 = c(0,2,0,2)
> x = c(2,3,4,8)
> d = data.frame(cbind(y1, y2, x))
>
> eq1 = y1 ~ x
> eq2 = y2 ~ x
> eqSystem = list (eq1, eq2)
>
> system_out = zelig(formula = eqSystem, model = "sur", data = d)
> summary(system_out)
>
> -
>
> # ERROR FROM REPLACING "sur" WITH "poisson"
> Error in switch(mode(x), `NULL` = structure(NULL, class = "formula"),  :
>  invalid formula
>
> --
> Owen Powell
> http://center.uvt.nl/phd_stud/powell
>
> __
> R-help@r-project.org mailing list
> https://stat.ethz.ch/mailman/listinfo/r-help
> PLEASE do read the posting guide http://www.R-project.org/posting-guide.html
> and provide commented, minimal, self-contained, reproducible code.
>



-- 
To every ω-consistent recursive class κ of formulae there correspond
recursive class signs r, such that neither v Gen r nor Neg(v Gen r)
belongs to Flg(κ) (where v is the free variable of r).

__
R-help@r-project.org mailing list
https://stat.ethz.ch/mailman/listinfo/r-help
PLEASE do read the posting guide http://www.R-project.org/posting-guide.html
and provide commented, minimal, self-contained, reproducible code.