Description Usage Arguments Details Value Author(s) References See Also

Computes the filter coefficients for all Savitzky-Golay smoothing filters.

1 |

`p` |
filter order. |

`n` |
filter length (must be odd). |

`m` |
return the m-th derivative of the filter coefficients. |

`ts` |
time scaling factor. |

The early rows of the result `F`

smooth based on future values and later rows
smooth based on past values, with the middle row using half future
and half past. In particular, you can use row `i`

to estimate `x[k]`

based on the `i-1`

preceding values and the `n-i`

following values of x
values as `y[k] = F[i,] * x[(k-i+1):(k+n-i)]`

.

Normally, you would apply the first `(n-1)/2`

rows to the first `k`

points of the vector, the last `k`

rows to the last `k`

points of the
vector and middle row to the remainder, but for example if you were
running on a realtime system where you wanted to smooth based on the
all the data collected up to the current time, with a lag of five
samples, you could apply just the filter on row `n-5`

to your window
of length `n`

each time you added a new sample.

An square matrix with dimensions `length(n)`

that is of
class `'sgolayFilter'`

(so it can be used with `filter`

).

Original Octave version by Paul Kienzle pkienzle@users.sf.net. Modified by Pascal Dupuis. Conversion to R by Tom Short.

William H. Press, Saul A. Teukolsky, William T. Vetterling, Brian
P. Flannery, *Numerical Recipes in C: The Art of Scientific Computing* ,
2nd edition, Cambridge Univ. Press, N.Y., 1992.

Octave Forge https://octave.sourceforge.io/

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