tframe (version 2015.12-1.1)

tfL: Time Series Shifting and Differencing

Description

Lag, shift forward, or difference a tframe or tframed object.

Usage

tfL(x, p=1)
    # S3 method for default
tfL(x, p=1)
    # S3 method for tframe
tfL(x, p=1)
    # S3 method for tframe
diff(x,lag=1, differences=1, ...)
    # S3 method for tframed
diff(x,lag=1, differences=1, ...)

Arguments

x

a tframed object.

lag

difference calculated relative to lag periods previous.

differences

order of differencing.

p

number of periods to shift or lag periods for differencing.

...

arguments to be passed to other methods.

Details

tfL methods shift the time frame, or the time frame of the object, by p periods. (This might also be thought of as the exponent of the lag operator.) Positive p means shift the time frame forward and negative p means shift the time frame back. Shifting the time frame forward means the data at a point in time is the data from the previous point in time in the unshifted data, so the result corresponds to what is often called the lagged data. The default p (+1) means the start and end for the results are one period later. When applied to a data object, the default result is one lag of the data. This convention is not the same as that used for k in the function lag.

Note that the time frame of the data is shifted, but a vector or matrix representation of the data is unchanged. This means that operations on the data, such as +, -, *, and /, need to be time aware as, for example, operations on ts objects are. If the operations do not recognize the time framed aspect of the objects, then the operation will be performed with default methods that will probably have unintended results (see examples).

Differencing methods create a time frame or time framed object by differencing the number of times indicated by differences at a lagged number of periods indicated by lag. (Positive values of lag indicate number of periods back.) The default is take the difference from data one period previous. See diff for more details, but note that the result when applied to a time frame is a time frame, not a series.

See Also

diff, lag

Examples

# NOT RUN {
    z <- ts(rnorm(100), start=c(1982,1), frequency=12)
    tfstart(z)
    Tobs(z)
    z <- diff(z)
    tfstart(z)
    Tobs(z)

    ts(1:5) - tfL(ts(1:5))
    (1:5) - tfL(1:5) # (1:5) this is not a tframed object, so minus is the default
    ts(1:5) - tfL(ts(1:5), p= 2)

    z <- ts(1:10, start=c(1992,1), frequency=4)
    z - tfL(z)

    z <- ts(matrix(1:10,5,2), start=c(1992,1), frequency=4)
    seriesNames(z) <- c("One", "Two")
    z - tfL(z)
# }