psi_null_ls_cpp: (C++) Null Distribution of the Dissimilarity Scores of Two...

In distantia: Advanced Toolset for Efficient Time Series Dissimilarity Analysis

(C++) Null Distribution of the Dissimilarity Scores of Two Aligned Time Series

Description

Applies permutation methods to compute null distributions for the psi scores of two time series observed at the same times. NA values should be removed before using this function. If the selected distance function is "chi" or "cosine", pairs of zeros should be either removed or replaced with pseudo-zeros (i.e. 0.00001).

Usage

psi_null_ls_cpp(
  x,
  y,
  distance = "euclidean",
  repetitions = 100L,
  permutation = "restricted_by_row",
  block_size = 3L,
  seed = 1L
)

Arguments

x	(required, numeric matrix) of same number of columns as 'y'.
y	(required, numeric matrix) of same number of columns as 'x'.
distance	(optional, character string) distance name from the "names" column of the dataset distances (see distances$name). Default: "euclidean".
repetitions	(optional, integer) number of null psi values to generate. Default: 100
permutation	(optional, character) permutation method. Valid values are listed below from higher to lower randomness: "free": unrestricted shuffling of rows and columns. Ignores block_size. "free_by_row": unrestricted shuffling of complete rows. Ignores block size. "restricted": restricted shuffling of rows and columns within blocks. "restricted_by_row": restricted shuffling of rows within blocks.
block_size	(optional, integer) block size in rows for restricted permutation. A block size of 3 indicates that a row can only be permuted within a block of 3 adjacent rows. Minimum value is 2. Default: 3.
seed	(optional, integer) initial random seed to use for replicability. Default: 1

Value

numeric vector

See Also

Other Rcpp_dissimilarity_analysis: psi_dtw_cpp(), psi_equation_cpp(), psi_ls_cpp(), psi_null_dtw_cpp()

distantia documentation built on April 4, 2025, 5:42 a.m.