LOESS smoothing function

Prefer the use of the wrapper function smooth_incidence(..., smoothing_method = "LOESS") instead of .smooth_LOESS.

.smooth_LOESS(
  incidence_input,
  data_points_incl = 21,
  degree = 1,
  initial_Re_estimate_window = 5
)

Arguments

incidence_input

Module input object. List with two elements:

  1. A numeric vector named values: the incidence recorded on consecutive time steps.

  2. An integer named index_offset: the offset, counted in number of time steps, by which the first value in values is shifted compared to a reference time step This parameter allows one to keep track of the date of the first value in values without needing to carry a date column around. A positive offset means values are delayed in the future compared to the reference values. A negative offset means the opposite.
data_points_incl

integer. Size of the window used in the LOESS algorithm. The span parameter passed to loess is computed as the ratio of data_points_incl and the number of time steps in the input data.
degree

integer. LOESS degree. Must be 0, 1 or 2.
initial_Re_estimate_window

integer. In order to help with the smoothing, the function extends the data back in time, padding with values obtained by assuming a constant Re. This parameter represents the number of timesteps in the beginning of incidence_input to take into account when computing the average initial Re.

Value

A list with two elements:

  1. A numeric vector named values: the result of the computations on the input data.

  2. An integer named index_offset: the offset, counted in number of time steps, by which the result is shifted compared to an index_offset of 0. This parameter allows one to keep track of the date of the first value in values without needing to carry a date column around. A positive offset means values are delayed in the future compared to the reference values. A negative offset means the opposite. Note that the index_offset of the output of the function call accounts for the (optional) index_offset of the input.

If index_offset is 0 and simplify_output = TRUE, the index_offset is dropped and the values element is returned as a numeric vector.

Details

This function implements the LOESS method for smoothing noisy data. It relies on loess. See the help section for loess for details on LOESS.