Computation of weighted ordinal patterns of a time series. Weights can be generated by a user-specified function (e.g. variance-weighted, see Fadlallah et al 2013).

1 | ```
weighted_ordinal_pattern_distribution(x, ndemb)
``` |

`x` |
A numeric vector (e.g. a time series), from which the weighted ordinal pattern distribution is to be calculated |

`ndemb` |
Embedding dimension of the ordinal patterns (i.e. sliding window size). Should be chosen such as length(x) >> ndemb |

This function returns the distribution of weighted ordinal patterns using the Keller coding scheme, detailed in Physica A 356 (2005) 114-120. NA values are allowed. The function uses old and slow R routines and is only maintained for comparability. For faster routines, see weighted_ordinal_pattern_distribution.

A character vector of length factorial(ndemb) is returned.

Sebastian Sippel

Fadlallah, B., Chen, B., Keil, A. and Principe, J., 2013. Weighted-permutation entropy: A complexity measure for time series incorporating amplitude information. Physical Review E, 87(2), p.022911.

`weighted_ordinal_pattern_distribution`

1 2 | ```
x = arima.sim(model=list(ar = 0.3), n = 10^4)
weighted_ordinal_pattern_distribution(x = x, ndemb = 6)
``` |

Questions? Problems? Suggestions? Tweet to @rdrrHQ or email at ian@mutexlabs.com.

All documentation is copyright its authors; we didn't write any of that.