| is.pbalanced {plm} | R Documentation |
This function checks if the data are balanced, i.e. each individual has the same time periods
## S3 method for class 'pdata.frame' is.pbalanced(x, ...) ## S3 method for class 'data.frame' is.pbalanced(x, index = NULL, ...) ## S3 method for class 'pseries' is.pbalanced(x, ...) ## S3 method for class 'panelmodel' is.pbalanced(x, ...) ## S3 method for class 'pgmm' is.pbalanced(x, ...)
x |
an object of class |
index |
only relevant for |
... |
further arguments. |
Balanced data are data for which each individual has the same time periods.
The returned values of the is.pbalanced(object) methods are identical to pdim(object)$balanced.
is.pbalanced is provided as a short cut and is faster than pdim(object)$balanced because it
avoids those computations performed by pdim which are unnecessary to determine the balancedness
of the data.
A logical indicating whether the data associated with object x are balanced (TRUE) or not (FALSE).
punbalancedness for two measures of unbalancedness,
make.pbalanced to make data balanced;
is.pconsecutive to check if data are consecutive; make.pconsecutive to make data consecutive
(and, optionally, also balanced).
pdim to check the dimensions of a 'pdata.frame' (and other objects),
pvar to check for individual and time variation of a 'pdata.frame' (and other objects),
pseries, data.frame, pdata.frame.
# take balanced data and make it unbalanced
# by deletion of 2nd row (2nd time period for first individual)
data("Grunfeld", package = "plm")
Grunfeld_missing_period <- Grunfeld[-2, ]
is.pbalanced(Grunfeld_missing_period) # check if balanced: FALSE
pdim(Grunfeld_missing_period)$balanced # same
# pdata.frame interface
pGrunfeld_missing_period <- pdata.frame(Grunfeld_missing_period)
is.pbalanced(Grunfeld_missing_period)
# pseries interface
is.pbalanced(pGrunfeld_missing_period$inv)