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

The `repr_matrix`

computes matrix of representations from matrix of time series

1 2 |

`x` |
the matrix, data.frame or data.table of time series, where time series are in rows of the table |

`func` |
the function that computes representation |

`args` |
the list of additional (or required) parameters of func (function that computes representation) |

`normalise` |
normalise (scale) time series before representations computation? (default is FALSE) |

`func_norm` |
the normalisation function (default is |

`windowing` |
perform windowing? (default is FALSE) |

`win_size` |
the size of the window |

This function computes representation to an every row of a matrix of time series and returns matrix of time series representations.
It can be combined with windowing (see `repr_windowing`

) and normalisation of time series.

the numeric matrix of representations of time series

Peter Laurinec, <[email protected]>

1 2 3 4 5 6 7 8 9 10 11 | ```
# Create random matrix of time series
mat_ts <- matrix(rnorm(100), ncol = 10)
repr_matrix(mat_ts, func = repr_paa,
args = list(q = 5, func = meanC))
# return normalised representations, and normalise time series by min-max normalisation
repr_matrix(mat_ts, func = repr_paa,
args = list(q = 2, func = meanC), normalise = TRUE, func_norm = norm_min_max)
# with windowing
repr_matrix(mat_ts, func = repr_feaclip, windowing = TRUE, win_size = 5)
``` |

TSrepr documentation built on June 1, 2018, 5:06 p.m.

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