Description Usage Arguments Details Value See Also Examples
View source: R/is.pconsecutive_pbalanced.R
This function checks if the data are balanced, i.e., if each individual has the same time periods
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 | is.pbalanced(x, ...)
## Default S3 method:
is.pbalanced(x, y, ...)
## S3 method for class 'data.frame'
is.pbalanced(x, index = NULL, ...)
## S3 method for class 'pdata.frame'
is.pbalanced(x, ...)
## 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 |
... |
further arguments. |
y |
(only in default method) the time index variable (2nd index variable), |
index |
only relevant for |
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()
.
1 2 3 4 5 6 7 8 9 10 11 12 13 | # 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)
|
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