pseries {plm} | R Documentation |
A class for panel series for which several useful computations and data transformations are available.
between(x, ...) Between(x, ...) Within(x, ...) ## S3 method for class 'pseries' between(x, effect = c("individual", "time", "group"), ...) ## S3 method for class 'pseries' Between(x, effect = c("individual", "time", "group"), ...) ## S3 method for class 'pseries' Within(x, effect = c("individual", "time", "group", "twoways"), ...) ## S3 method for class 'pseries' summary(object, ...) ## S3 method for class 'summary.pseries' print(x, ...) ## S3 method for class 'pseries' as.matrix(x, idbyrow = TRUE, ...)
x, object |
a |
effect |
character string indicating the |
idbyrow |
if |
... |
further arguments, e. g. |
The functions between
, Between
, and Within
perform specific
data transformations, i. e. the between and within transformation.
between
returns a vector containing the individual means (over time) with the length of the
vector equal to the number of individuals (if effect = "individual"
(default); if effect = "time"
,
it returns the time means (over individuals)). Between
duplicates the values and returns a vector which
length is the number of total observations. Within
returns a vector containing the
values in deviation from the individual means (if effect = "individual"
, from time means if effect = "time"
),
the so called demeaned data.
For between
, Between
, and Within
in presence of NA values it can
be useful to supply na.rm = TRUE
as an additional argument to
keep as many observations as possible in the resulting transformation, see
also Examples.
All these functions return an object of class pseries
, except:
between
, which returns a numeric vector, as.matrix
, which returns a matrix.
Yves Croissant
For more functions on class 'pseries' see lag
, lead
,
diff
for lagging values, leading values (negative lags) and differencing.
# First, create a pdata.frame data("EmplUK", package = "plm") Em <- pdata.frame(EmplUK) # Then extract a series, which becomes additionally a pseries z <- Em$output class(z) # obtain the matrix representation as.matrix(z) # compute the between and within transformations between(z) Within(z) # Between replicates the values for each time observation Between(z) # between, Between, and Within transformations on other dimension between(z, effect = "time") Between(z, effect = "time") Within(z, effect = "time") # NA treatment for between, Between, and Within z2 <- z z2[length(z2)] <- NA # set last value to NA between(z2, na.rm = TRUE) # non-NA value for last individual Between(z2, na.rm = TRUE) # only the NA observation is lost Within(z2, na.rm = TRUE) # only the NA observation is lost sum(is.na(Between(z2))) # 9 observations lost due to one NA value sum(is.na(Between(z2, na.rm = TRUE))) # only the NA observation is lost sum(is.na(Within(z2))) # 9 observations lost due to one NA value sum(is.na(Within(z2, na.rm = TRUE))) # only the NA observation is lost