| pmodel.response {plm} | R Documentation |
pmodel.response has several method to extract conveniently the response of several objects
pmodel.response(object, ...)
## S3 method for class 'data.frame':
pmodel.response(object,
model = c("pooling","within","Between",
"between","mean","random","fd"),
effect = c("individual","time","twoways"),
lhs = NULL,
theta = NULL, ...)
## S3 method for class 'pFormula':
pmodel.response(object, data,
model = c("pooling","within","Between",
"between","mean","random","fd"),
effect = c("individual","time","twoways"),
lhs = NULL,
theta = NULL, ...)
## S3 method for class 'plm':
pmodel.response(object,
model = c("pooling","within","Between",
"between","mean","random","fd"),
effect = c("individual","time","twoways"),
theta = NULL, ...)
object |
an object of class "plm", |
data |
a data.frame, |
effect |
the effects introduced in the model, one of
"individual", "time" or "twoways", |
model |
one of "pooling", "within",
"between", "random", "fd" and "ht", |
theta |
the parameter for the transformation if model =
"random", |
lhs |
, |
... |
further arguments. |
The model response is extracted (from a data.frame, a
pFormula or a plm object, and the transformation
specified by effect and model is applied to it.
A numeric vector.
Yves Croissant