pdim {plm} | R Documentation |
This function checks the number of individuals and time observations in the panel and whether it is balanced or not.
pdim(x, ...) ## S3 method for class 'data.frame' pdim(x, index = NULL, ...) ## S3 method for class 'panelmodel' pdim(x, ...) ## S3 method for class 'pseries' pdim(x, ...) ## S3 method for class 'pdata.frame' pdim(x, ...) ## S3 method for class 'pgmm' pdim(x, ...)
x |
a |
index |
see |
... |
further arguments. |
pdim
is called by the estimation functions and can be also used stand-alone.
An object of class pdim
containing the following elements:
nT |
a list containing |
Tint |
a list containing two vectors (of type integer): |
balanced |
a logical value: |
panel.names |
a list of character vectors: |
Calling pdim
on an estimated panelmodel
object and on the corresponding (p)data.frame
used for this estimation does not necessarily yield the same result. When called on an estimated panelmodel
,
the number of observations (individual, time) actually used for model estimation are taken into account.
When called on a (p)data.frame
, the rows in the (p)data.frame
are considered, disregarding any
NA values in the dependent or independent variable(s) which would be dropped during model estimation.
Yves Croissant
is.pbalanced
to just determine balancedness of data (slightly faster than pdim
),
punbalancedness
for measures of unbalancedness,
nobs
, pdata.frame
,
pvar
to check for each variable if it varies cross-sectionally and over time.
# There are 595 individuals data("Wages", package = "plm") pdim(Wages, 595) # Gasoline contains two variables which are individual and time indexes # and are the first two variables data("Gasoline", package="plm") pdim(Gasoline) # Hedonic is an unbalanced panel, townid is the individual index data("Hedonic", package = "plm") pdim(Hedonic, "townid") # An example of the panelmodel method data("Produc", package = "plm") z <- plm(log(gsp)~log(pcap)+log(pc)+log(emp)+unemp,data=Produc, model="random", subset = gsp > 5000) pdim(z)