i suggest you use sim and then compute expected values or predicted values
(the manual gives details and examples). these are generally better than
fitted values since they include all sources of uncertainty; fitted values
don't.
Gary
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GaryKing.org - King(a)Harvard.edu - @KingGary <https://twitter.com/kinggary> -
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On Thu, Mar 27, 2014 at 4:54 PM, Meredith, Christy S -FS <
csmeredith(a)fs.fed.us> wrote:
Hello I am having trouble finding the fitted values
from Zelig. I
ultimately want to use my models to predict on a new dataset and then be
able to extract the fitted values to determine how well my model performs.
I have tried varies methods in the documentation, but nothing works for me.
I appreciate any help.
Thanks!
Christy Meredith
My code:
z.out=zelig(beavpres~Grad+Elev + distancew+Elev +
GrazingR+AvgPrecip+deciduous+Bf+AvgVWidth*Grad,data=update5a,model="relogit",tau=0.05)
cv.out=cv.glm(z.out,data=update5a) # try cross validation
x.out <- setx(z.out)
s.out <- sim(z.out,x.out)
#attempt to determine fitted values- doesn’t work
s.out$qi$ev
z.out$fitted.values
Christy Meredith
USDA Forest Service
Rocky Mountain Research Station
PIBO Monitoring
Data Analyst
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Fax: 435-755-3563
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