Dear all,

 

I would be very pleased if someone could help me with the following
issue on the structure of the residuals variance-covariance matrix.

 

I have repeated observations (t = 1, ..., T) for several products,
belonging to a category in several countries:

 

Product i = 1, ... , I

Category k = 1, ..., K

Country j = 1, ... , J

 

The same product i is present in several/all countries. I also have some
extra explanatory variables in x.

 

I want to model y_{ikjt} = beta*x_{ikjt} + u_j + v_{kj} + w_{ikj} +
e_{ikjt} allowing for:

 

- within-category correlation Corr(e_{ik},e_{i'k}), 

 

- within-country correlation Corr(e_{ikj},e_{i'k'j}),

 

- different variances for the different products (heteroskedasticy among
products).

 

I do the following:

 

lme(y~-1+x,random=~1|country/category/product,           

                        weights=varIdent(~1|country/category/product),

 
correlation=corCompSymm(form=~1|country/category/product))

 

is it correct and does it exist a way to extract the residual variance
covariance matrix?

 

Thanks a lot,

A. Lemmens (aurelie.lemmens@econ.kuleuven.be)

 



Disclaimer: http://www.kuleuven.be/cwis/email_disclaimer.htm


	[[alternative HTML version deleted]]


