GaussianSmooth: Calculate rolling Gaussian smooth of pollutant values

In openair: Tools for the Analysis of Air Pollution Data

Calculate rolling Gaussian smooth of pollutant values

Description

This is a utility function designed to calculate rolling Gaussian smooth (kernel smoothing). The function will try and fill in missing time gaps to get a full time sequence but return a data frame with the same number of rows supplied.

Usage

GaussianSmooth(
  mydata,
  pollutant = "o3",
  sigma = 24L,
  type = "default",
  data.thresh = 0,
  new.name = NULL,
  date.pad = FALSE,
  ...
)

Arguments

mydata	A data frame containing a date field. mydata must contain a date field in Date or POSIXct format. The input time series must be regular, e.g., hourly, daily.
pollutant	The name of a pollutant, e.g., pollutant = "o3". More than one pollutant can be supplied as a vector, e.g., pollutant = c("o3", "nox").
sigma	The value of sigma to use in the Gaussian.
type	Used for splitting the data further. Passed to cutData().
data.thresh	The % data capture threshold. No values are calculated if data capture over the period of interest is less than this value.
new.name	The name given to the new column(s). If not supplied it will create a name based on the name of the pollutant and the averaging period used.
date.pad	Should missing dates be padded? Default is FALSE.
...	Passed to cutData() for use with type.

Details

The function provides centre-aligned smoothing out to 3 sigma, which captures 99.7% of the data.

Value

A tibble with two new columns for the Gaussian smooth value.

Author(s)

David Carslaw

Examples

# Gaussian smoother with sigma = 24
mydata <- GaussianSmooth(mydata,
  pollutant = "o3", sigma = 24, data.thresh = 75)

openair documentation built on April 2, 2026, 9:07 a.m.