permute_restricted_by_row_cpp

Divides a sequence in blocks of a given size and permutes rows
within these blocks.
Larger block sizes increasingly disrupt the data structure over time.

Fast C++ implementation of Dynamic Time Warping for time series dissimilarity analysis, with applications in environmental monitoring and sensor data analysis, climate science, signal processing and pattern recognition, and financial data analysis. Built upon the ideas presented in Benito and Birks (2020) <doi:10.1111/ecog.04895>, provides tools for analyzing time series of varying lengths and structures, including irregular multivariate time series. Key features include individual variable contribution analysis, restricted permutation tests for statistical significance, and imputation of missing data via GAMs. Additionally, the package provides an ample set of tools to prepare and manage time series data.

Blas M. Benito

distantia

Advanced Toolset for Efficient Time Series Dissimilarity
Analysis

permute_restricted_by_row_cpp function

<dl><dt>x</dt>
<dd>(required, numeric matrix). Numeric matrix to permute.</dd>
<dt>block_size</dt>
<dd>(optional, integer) block size in number of rows.
Minimum value is 2, and maximum value is nrow(x).</dd>
<dt>seed</dt>
<dd>(optional, integer) random seed to use.</dd></dl>

Arguments

(C++) Restricted Permutation of Complete Rows Within Blocks — permute_restricted_by_row_cpp

<dl>

<dt>x</dt>
<dd>(required, numeric matrix). Numeric matrix to permute.</dd>


<dt>block_size</dt>
<dd>(optional, integer) block size in number of rows.
Minimum value is 2, and maximum value is nrow(x).</dd>


<dt>seed</dt>
<dd>(optional, integer) random seed to use.</dd>

</dl>

permute_restricted_by_row_cpp: (C++) Restricted Permutation of Complete Rows Within Blocks

Description

Usage

Value

Arguments

See Also