Displaying 3 results from an estimated 3 matches for "recreationdemand".
2018 Feb 16
1
hurdle model - count and response predictions
...ps://stat.ethz.ch/pipermail/r-help/2012-August/320426.html) and here (
https://stackoverflow.com/questions/48794622/hurdle-model-prediction-count-vs-response
).
Since the issue is the same (and not resolved), I'll just use the example
from the second link:
library("pscl")
data("RecreationDemand", package = "AER")
## model
m <- hurdle(trips ~ quality | ski, data = RecreationDemand, dist = "negbin")
nd <- data.frame(quality = 0:5, ski = "no")
predict(m, newdata = nd, type = "count")
predict(m, newdata = nd, type = "response")
Th...
2012 Jan 17
2
pscl package and hurdle model marginal effects
This request is related to the following post from last year:
https://stat.ethz.ch/pipermail/r-help/2011-June/279752.html
After reading the thread, the idea is still not clear. I have fitted a model using HURDLE from the PSCL package. I am trying to get marginal effects / slopes by multiplying the coefficients by the mean of the marginal effects (I think this is right). To my understanding, this
2007 Apr 10
1
When to use quasipoisson instead of poisson family
It seems that MASS suggest to judge on the basis of
sum(residuals(mode,type="pearson"))/df.residual(mode). My question: Is
there any rule of thumb of the cutpoiont value?
The paper "On the Use of Corrections for Overdispersion" suggests
overdispersion exists if the deviance is at least twice the number of
degrees of freedom.
Are there any further hints? Thanks.
--
Ronggui