repr_matrix: Computation of matrix of representations from matrix of time...
In PetoLau/TSrepr: Time Series Representations

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

The repr_matrix computes matrix of representations from matrix of time series

repr_matrix(
  x,
  func = NULL,
  args = NULL,
  normalise = FALSE,
  func_norm = norm_z,
  windowing = FALSE,
  win_size = NULL
)

`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 `norm_z`)
`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, <tsreprpackage@gmail.com>

repr_windowing, repr_list

# 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)