`cumsumk` (Series)

Cumulative sum with a k-period leap

Syntax

Y = cumsumk(X, Range, ...)

Input arguments

X [ tseries ]

Input time series.

Range [ Dater | Inf ]

Range on which the cumulative sum will be computed and the output time series returned, not including the presample or postsample needed.

Output arguments

X [ tseries ]

Output time series constructed as described below; the time series is returned for the Range, without the presample or postsample data used for initial or terminal condition.

Options

K=@auto [ numeric | @auto ]

Number of periods that will be leapt the cumulative sum will be taken; @auto means K is chosen to match the frequency of the input series (e.g. K=-4 for quarterly data), or K=-1 for integer frequency.

Log=false [ true | false ]

Logarithmize the input data before, and de-logarithmize the output data back afterwards.

Rho=1 [ numeric ]

Autoregressive coefficient.

Description

If K<0, the first K observations in the output series are copied from the input series, and the new observations are given recursively by Y{t} = Rho*Y{t-K} + X{t}.

If K>0, the last K observations in the output series are copied from the input series, and the new observations are given recursively by Y{t} = Rho*Y{t+K} + X{t}, going backwards in time.

If K == 0, the input data are returned.

Examples

Construct random data with seasonal pattern, and run X12 to seasonally adjust these series.

x = tseries(qq(1990, 1):qq(2020, 4), @randn);
x1 = cumsumk(x, -4, 1);
x2 = cumsumk(x, -4, 0.7);
x1sa = x12(x1);
x2sa = x12(x2);

The new series x1 will be a unit-root process while x2 will be stationary. Note that the command on the second line could be replaced with x1 = cumsumk(x).

cumsumk (Series)