Hi
did you look at help page of lme?
r-help-boun...@r-project.org napsal dne 25.10.2010 22:59:40:
>
>
> Hi,
>
> I am trying to run a panel regression where I have a matrix of
observations
> and a matrix of independant variables - examples would trying to predict
> countries's GDP with their data on education, FDI, tax rates, over time.
>
> For the purpose of simplicity, my data would be:
>
> dep = matrix(rnorm(50),ncol=5)
> indep1 = matrix(rnorm(50),ncol=5)
> indep2 = matrix(rnorm(50),ncol=5)
>
> >From what I could find, the lme{nlme} function would be the function.
> However, after I installed the package and I type in:
>
> > lme(dep~indep1, indep2)
> Error in model.frame.default(formula = ~indep1 + dep, data =
> c(-0.63665929869261, :
> 'data' must be a data.frame, not a matrix or an array
>
> I keep getting error messages even after I transform the data in a data
> frame. Any idea on how I could get R to perform a simple panel
regression?
How did you transform your data to data frame? The input object shall be
data frame with one column of dependent values and one or more columns of
independent variables and one column of categorical variable for
discrimination.
See
> head(Orthodont)
Grouped Data: distance ~ age | Subject
distance age Subject Sex
1 26.0 8 M01 Male
2 25.0 10 M01 Male
3 29.0 12 M01 Male
4 31.0 14 M01 Male
5 21.5 8 M02 Male
6 22.5 10 M02 Male
In lme call you need to give a formula which will be evaluated based on
the data frame.
something like
lme(GDP~education+FDI+tax+time|Country, my.data.frame, ...)
Regards
Petr
>
>
> Thanks!
> --
> View this message in context:
http://r.789695.n4.nabble.com/Panel-regression-
> tp3012794p3012794.html
> Sent from the R help mailing list archive at Nabble.com.
>
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