add_diff_variable: Add the lagged difference between multiple variables to a...

In epiforecasts/covid19.track.severity: Track Covid-19 Severity Measures

Description

Differences multiple variables (either exactly or partially defined) by another variable for a specified lag and stratification.

Usage

add_diff_variable(
  dt,
  variable,
  label,
  by,
  shift_var = "value",
  vars = c("median", "mean", "secondary", "value"),
  partial_vars = c("lower_", "upper_"),
  fill = 1,
  n = 1L,
  type = "lag"
)

Arguments

dt	A data.table containing at a target variable and the variables identified in the other arguments.
variable	Character string identifying the variable in target to calculate the lagged difference for.
label	Character string giving the name for the new lagged variable.
by	An optional character vector identifying the variables to stratify by.
shift_var	Character string, indicating the variable to use to calculate the difference.
vars	Character vector giving the exact names of variables to calculate the difference for.
partial_vars	Character vector giving the partial names of variables to calculate the difference for.
fill	Value to use for padding when the window goes beyond the input length.
n	integer vector denoting the offset by which to lead or lag the input. To create multiple lead/lag vectors, provide multiple values to n; negative values of n will "flip" the value of type, i.e., n=-1 and type='lead' is the same as n=1 and type='lag'.
type	default is "lag" (look "backwards"). The other possible values "lead" (look "forwards") and "shift" (behave same as "lag" except given names).

Value

The input data.table combined with the new differenced variable.

Examples

dt <- data.frame(target = "test", var = 1:100, var2 = c(1, 2),
                 strat = c("a", "b"))
add_diff_variable(dt, "test", "new", vars = "var", shift_var = "var2",
                  by = "strat")

epiforecasts/covid19.track.severity documentation built on July 6, 2021, 4:50 p.m.