I'm not sure what you are asking, especially since I do not have
access to "regaccdis". However, will something like the following do
what you want?
caeLvls <- c(1, 5, 10)
for(i in 1:3)
coef[i,2:4] <-
coef(plm(ff,data=regaccdis,na.action=na.omit,model="pooling",subset=(regaccdis$caedois==caeLvls[i])))
If this does NOT answer your question, PLEASE do read the posting guide
http://www.R-project.org/posting-guide.html
and provide commented, minimal, self-contained, reproducible code.
Hope this helps.
Spencer
Cecilia Carmo wrote:
Hi R-helpers,
I want to determine the coefficients of the following regression for
several subsets, and I want to save it in a dataframe:
The data is in «regaccdis», «regaccdis$caedois» is the column that
defines the subsets and the function I have runned is
coef(plm(ff,data=regaccdis,na.action=na.omit,model="pooling",subset=(regaccdis$caedois==i)))
I‘ve created a dataframe named «coef» to store the coefficients like
this :
caedois b1 b2 b3
1 1 0.033120395 -20.29478 -0.27463886
2 5 -0.040629634 74.54240 -0.06995842
3 10 -0.001116816 35.23986 0.21432718
…
And I runned the following regressions to obtain those values:
coef[1,2:4] <-
coef(plm(ff,data=regaccdis,na.action=na.omit,model="pooling",subset=(regaccdis$caedois==1)))
coef[2,2:4] <-
coef(plm(ff,data=regaccdis,na.action=na.omit,model="pooling",subset=(regaccdis$caedois==5)))
coef[3,2:4] <-
coef(plm(ff,data=regaccdis,na.action=na.omit,model="pooling",subset=(regaccdis$caedois==10)))
But I need to do this more than 50 times!
Anyone could help me with a loop or with a function like apply?
Thank you!
Cecília (Universidade de Aveiro – Portugal)
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and provide commented, minimal, self-contained, reproducible code.
