nopool {plm} | R Documentation |
Least Squares estimation for each individual or time observation
nopool(y,...) ## S3 method for class 'formula': nopool(y,data=data,effect="individual",...) ## Default S3 method: nopool(y,X,cond,...) ## S3 method for class 'nopool': print(x,digits=3, ...) ## S3 method for class 'nopool': summary(object, ...) ## S3 method for class 'summary.nopool': print(x,digits=3, ...) ## S3 method for class 'nopool': plot(x,...)
y |
a symbolic description for the model to be estimated for the formula method, a numerical vector for the default method, |
cond |
a vector containing the individual or the time index, |
object,x |
an object of class nopool , |
X |
a matrix of explanatory variables, |
data |
the data, |
effect |
one of "individual" or "time" ,
respectively for an estimation for each individual or time observation, |
digits |
digits, |
... |
further arguments. |
The nopool
model may also be estimated with the plm
function if np=TRUE
.
an object of class "nopool"
, which is a list of :
residuals
the vector of residuals,
df.residuals
the degrees of freedom of the regression,
ssr
the sum of the squared residuals,
coefficients
a data.frame
containing the coefficients for each
estimation,
std.error
a data.frame
containing the standard errors of the
coefficients for each estimation,
The print
prints the data.frame
containing the
coefficients, and the summary
method is the
data.frame
's method applied to the coefficients.
The plot
method plots histograms for each coefficient.
plm
and pooltest
for poolability tests.
library(Ecdat) data(Produc) Produc <-pdata.frame(Produc,state,year) zz <- nopool(log(gsp)~log(pcap)+log(pc)+log(emp)+unemp,data=Produc) zz <- nopool(log(gsp)~log(pcap)+log(pc)+log(emp)+unemp,effect="temp",data=Produc) summary(zz) plot(zz)