lag
creates a lagged version of a time series, shifting the time base
forward by a given number of observations. Lag
does exactly the
opposite, shifting the time base backwards by the given number of
observations. lag
and Lag
create a single lagged
series, while lags
and Lags
can create a multivariate
series with several lags at once.
1 2 3 4 5 6 |
x |
A vector or matrix or univariate or multivariate time series
(including |
k |
The number of lags. For |
... |
further arguments to be passed to or from methods |
lags |
vector of lag numbers. For code |
name |
string or a character vector of names to be used in constructing column names for the returned series |
Vector or matrix arguments 'x' are coerced to time series.
For lags
, column names are constructed as follows: If
name
is supplied and has as many elements as x
has
columns, those names are used as the base column names. Otherwise the
column names of x
comprise the base column names, or if those
don't exist, the first ncols(x)
letters of the alphabet are
used as base names. Each column of the returned series has a name
consisting of the basename plus a suffix indicating the lag number for
that column.
Both functions return a time series (ts
or tis
) object.
If the lags
argument to the lags
function argument has
more than one element, the returned object will have a column for each
lag, with NA
's filling in where appropriate.
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