smooth_triangular {alkahest} | R Documentation |

## Triangular Smoothing

### Description

Weighted sliding-average or triangular smoothing.

### Usage

```
smooth_triangular(x, y, ...)
## S4 method for signature 'numeric,numeric'
smooth_triangular(x, y, m = 3)
## S4 method for signature 'ANY,missing'
smooth_triangular(x, m)
```

### Arguments

`x` , `y` |
A |

`...` |
Currently not used. |

`m` |
An odd |

### Details

It replaces each point in the signal with the weighted mean of `m`

adjacent points.

### Value

Returns a `list`

with two components `x`

and `y`

.

### Note

There will be `(m - 1) / 2`

points both at the beginning and at the end
of the data series for which a complete `m`

-width window cannot be
obtained. To prevent data loss, progressively wider/narrower windows are
used at both ends of the data series.

### Author(s)

N. Frerebeau

### See Also

Other smoothing methods:
`smooth_likelihood()`

,
`smooth_loess()`

,
`smooth_rectangular()`

,
`smooth_savitzky()`

,
`smooth_whittaker()`

### Examples

```
## Simulate data with some noise
x <- seq(-4, 4, length = 100)
y <- dnorm(x) + rnorm(100, mean = 0, sd = 0.01)
## Plot spectrum
plot(x, y, type = "l", xlab = "", ylab = "")
## Rectangular smoothing
unweighted <- smooth_rectangular(x, y, m = 3)
plot(unweighted, type = "l", xlab = "", ylab = "")
## Triangular smoothing
weighted <- smooth_triangular(x, y, m = 5)
plot(weighted, type = "l", xlab = "", ylab = "")
## Loess smoothing
loess <- smooth_loess(x, y, span = 0.75)
plot(loess, type = "l", xlab = "", ylab = "")
## Savitzkyâ€“Golay filter
savitzky <- smooth_savitzky(x, y, m = 21, p = 2)
plot(savitzky, type = "l", xlab = "", ylab = "")
## Whittaker smoothing
whittaker <- smooth_whittaker(x, y, lambda = 1600, d = 2)
plot(whittaker, type = "l", xlab = "", ylab = "")
```

*alkahest*version 1.1.1 Index]