Package 'ssmooth'

Smooth Raster Time Series

Description

Applies a smoothing operation to each pixel's time series in a multi-layer raster using one of three methods: mean (moving average), weighted moving average, or exponential moving average.

Usage

SmoothRasterTS(
  rast,
  ...,
  cores = 1L,
  filename = "",
  overwrite = FALSE,
  wopt = list()
)

Arguments

rast	SpatRaster. A multi-layer raster object where each layer represents a time point in the series.
...	Additional arguments passed to the SmoothTS function, such as method, n, weights, alpha, and n_init.
cores	Integer. Number of CPU cores to use for parallel processing. Default is 1. Don't change this unless you know what you're doing.
filename	Character. Optional filename for writing the output raster. If provided, the output raster will be written to this file.
overwrite	Logical. If TRUE and filename is provided, allows overwriting the existing file; optional.
wopt	List. Optional list of additional arguments to pass to terra::writeRaster.

Details

Assumes that the input raster has multiple layers, where each layer represents a time point in the series. The function applies the specified smoothing method to the time series of each pixel across the layers and returns a new raster with the smoothed time series for each pixel.

Value

SpatRaster. A multi-layer raster object with smoothed time series for each pixel.

Examples

rast <- terra::rast(nrow = 1, ncol = 2, nlyrs = 5)
terra::values(rast) <- matrix(rep(1:5, each = 2), nrow = 2)
out <- SmoothRasterTS(rast, method = "mean", n = 3)

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Smooth Time Series Data

Description

Applies a smoothing operation to a numeric vector (time series data) using one of three methods: mean (moving average), weighted moving average, or exponential moving average.

Usage

SmoothTS(
  x,
  method = "exponential",
  n = 3,
  weights = rep(1, 3),
  alpha = 0.3,
  n_init = 5
)

Arguments

x	Numeric vector. The time series data to be smoothed.
method	Character. Smoothing method to use. Options are "mean", "weighted", or "exponential". Default is "exponential".
n	Integer. Number of points for the moving average (used in "mean" method). Default is 3.
weights	Numeric vector. Weights for the weighted moving average (used in "weighted" method). Default is a vector of 1's (i.e., simple moving average).
alpha	Numeric. Smoothing factor for exponential moving average (used in "exponential" method). Default is 0.3.
n_init	Integer. Number of initial points to use for the first smoothed value in the exponential moving average (used in "exponential" method). Default is 5.

Details

For the "mean" method, a simple moving average is computed over a specified window size. For the "weighted" method, a weighted moving average is computed using a specified set of weights. For the "exponential" method, an exponential moving average is computed using a specified smoothing factor (alpha) and a specified number of initial points to use for the first smoothed value.

If you use a windowing method (mean or weighted), the function pads the input vector with the mean of the non-NA values at the beginning and end to ensure that the output vector has the same length as the input.

Value

Numeric vector of smoothed values.

Examples

x <- 1:10
SmoothTS(x, method = "mean", n = 3)
SmoothTS(x, method = "weighted", n = 3, weights = c(0.1, 0.5, 0.4))
SmoothTS(x, method = "exponential", alpha = 0.5, n_init = 3)

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