greybox (version 2.0.8)

B: Create Lagged or Lead Variables for Time Series Regression

Description

`B()` acts as a backshift operator and creates lagged (past values) or lead (future values) versions of a variable for use in regression formulas. This function is designed to work within R formula syntax, similar to how `I()` or `log()` work.

Usage

B(x, k, ...)

Value

A numeric vector of the same length as `x`. The missing values are treated by the `xregExpander()`. By default they are extrapolated (gaps="auto").

Arguments

x

A numeric vector or time series variable to be lagged or lead

k

An integer specifying the lag order:

• Positive values (e.g., `k = 1`) create lags (past values)

• Negative values (e.g., `k = -1`) create leads (future values)

• Zero (`k = 0`) returns the original variable unchanged

...

Parameters passed to `xregExpander()`.

Details

The function calls for the `xregExpander()` to create lags/leads. So, you can pass additional parameters to it via ellipsis.

When `k > 0` (lag), the function shifts values forward in time, so `B(x, 1)` at time `t` contains the value of `x` at time `t-1`.

When `k < 0` (lead), the function shifts values backward in time, so `B(x, -1)` at time `t` contains the value of `x` at time `t+1`.

See Also

, xregExpander for data frame lag operations lag for time series lag (different behavior)

Examples

# Create sample time series data
y = rnorm(10)

# Create lags
B(y, 1)

# Create leads
B(y, -1)