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SWMPr (version 2.5.0)

smoother: Smooth swmpr data

Description

Smooth swmpr data with a moving window average

Usage

smoother(x, ...)

# S3 method for default smoother(x, window = 5, sides = 2, ...)

# S3 method for swmpr smoother(x, params = NULL, ...)

Value

Returns a filtered swmpr object. QAQC columns are removed if included with input object.

Arguments

x

input object

...

arguments passed to or from other methods

window

numeric vector defining size of the smoothing window, passed to filter

sides

numeric vector defining method of averaging, passed to filter

params

is chr string of swmpr parameters to smooth, default all

Details

The smoother function can be used to smooth parameters in a swmpr object using a specified window size. This method is a simple wrapper to filter. The window argument specifies the number of observations included in the moving average. The sides argument specifies how the average is calculated for each observation (see the documentation for filter). A value of 1 will filter observations within the window that are previous to the current observation, whereas a value of 2 will filter all observations within the window centered at zero lag from the current observation. The params argument specifies which parameters to smooth.

See Also

Examples

Run this code
## import data
data(apadbwq)
swmp1 <- apadbwq

## qaqc and subset imported data
dat <- qaqc(swmp1)
dat <- subset(dat, subset = c('2012-07-09 00:00', '2012-07-24 00:00'))

## filter
test <- smoother(dat, window = 50, params = 'do_mgl')

## plot to see the difference
plot(do_mgl ~ datetimestamp, data = dat, type = 'l')
lines(test, select = 'do_mgl', col = 'red', lwd = 2)

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