Displaying 5 results from an estimated 5 matches for "fm_zinb2".
2024 Jan 04
1
Obtaining a value of pie in a zero inflated model (fm-zinb2)
Are you referring to the zeroinfl() function in the countreg package? If
so, I think
predict(fm_zinb2, type = "zero", newdata = some.new.data)
will give you pi for each combination of covariate values that you
provide in some.new.data
where pi is the probability to observe a zero from the point mass component.
As to your second question, I'm not sure that's possible, for any
*p...
2024 Jan 04
1
Obtaining a value of pie in a zero inflated model (fm-zinb2)
I am running a zero inflated regression using the zeroinfl function similar to the model below:
fm_zinb2 <- zeroinfl(art ~ . | ., data = bioChemists, dist = "poisson")
summary(fm_zinb2)
I have three questions:
1) How can I obtain a value for the parameter pie, which is the fraction of the population that is in the zero inflated model vs the fraction in the count model?
2) For any part...
2012 May 05
0
Getting predicted values from a zero-inflated negative binomial using zeroinfl()
Hi,
I am a little confused at the output from predict() for a zeroinfl object.
Here's my confusion:
## From zeroinfl package
fm_zinb2 <- zeroinfl(art ~ . | ., data = bioChemists, dist = "negbin")
## The raw zero-inflated overdispersed data
> table(bioChemists$art)
0 1 2 3 4 5 6 7 8 9 10 11 12 16 19
275 246 178 84 67 27 17 12 1 2 1 1 2 1 1
## The default output from p...
2012 Apr 26
2
Lambert (1992) simulation
Hi,
I am trying to replicate Lambert (1992)'s simulation with zero-inflated
Poisson models. The citation is here:
@article{lambert1992zero,
Author = {Lambert, D.},
Journal = {Technometrics},
Pages = {1--14},
Publisher = {JSTOR},
Title = {Zero-inflated {P}oisson regression, with an application to defects
in manufacturing},
Year = {1992}}
Specifically I am trying to recreate Table 2. But my
2024 Jan 06
0
Help request: Parsing docx files for key words and appending to a spreadsheet
...(fm-zinb2)
>> Message-ID: <02c6fe89-ccae-6c7c-c61e-f79cffad4358 at binghamton.edu>
>> Content-Type: text/plain; charset="utf-8"
>>
>> Are you referring to the zeroinfl() function in the countreg package? If so, I
>> think
>>
>> predict(fm_zinb2, type = "zero", newdata = some.new.data)
>>
>> will give you pi for each combination of covariate values that you provide in
>> some.new.data
>>
>> where pi is the probability to observe a zero from the point mass
>> component.
>>
>> As to y...