On Wednesday 04 May 2005 20:08, Iain Pardoe wrote:
> I'd like to model the relationship between m responses Y1, ..., Ym and a
> single set of predictor variables X1, ..., Xr. Each response is assumed
> to follow its own regression model, and the error terms in each model
> can be correlated. My u
Thanks Henric.
If I may I'd like to go a little further ... For example, Johnson and
Wichern's example 7.10:
> ex7.10 <-
+ data.frame(y1 = c(141.5, 168.9, 154.8, 146.5, 172.8, 160.1, 108.5),
+ y2 = c(301.8, 396.1, 328.2, 307.4, 362.4, 369.5, 229.1),
+ z1 = c(123.5, 14
Iain Pardoe said the following on 2005-05-04 20:08:
I'd like to model the relationship between m responses Y1, ..., Ym and a
single set of predictor variables X1, ..., Xr. Each response is assumed
to follow its own regression model, and the error terms in each model
can be correlated. My understa
I'd like to model the relationship between m responses Y1, ..., Ym and a
single set of predictor variables X1, ..., Xr. Each response is assumed
to follow its own regression model, and the error terms in each model
can be correlated. My understanding is that although lm() handles
vector Y's on th
