lag_vec: Lag Transformation

Description Usage Arguments Details Value See Also Examples

View source: R/vec-lag.R

Description

lag_vec() applies a Lag Transformation.

Usage

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lag_vec(x, lag = 1)

lead_vec(x, lag = -1)

Arguments

x

A numeric vector to be lagged.

lag

Which lag (how far back) to be included in the differencing calculation. Negative lags are leads.

Details

Benefits:

This function is NA padded by default so it works well with dplyr::mutate() operations. The function allows both lags and leads (negative lags).

Lag Calculation

A lag is an offset of lag periods. NA values are returned for the number of lag periods.

Lead Calculation

A negative lag is considered a lead. The only difference between lead_vec() and lag_vec() is that the lead_vec() function contains a starting negative value.

Value

A numeric vector

See Also

Modeling and Advanced Lagging:

Vectorized Transformations:

Examples

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library(dplyr)
library(timetk)

# --- VECTOR ----

# Lag
1:10 %>% lag_vec(lag = 1)

# Lead
1:10 %>% lag_vec(lag = -1)


# --- MUTATE ----

m4_daily %>%
    group_by(id) %>%
    mutate(lag_1 = lag_vec(value, lag = 1))

timetk documentation built on Jan. 19, 2021, 1:06 a.m.