utils_time_units

Returns a data frame with the names of the supported time units, the classes that can handle each time unit, and a the threshold used to identify what time units can be used when aggregating a time series.

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

utils_time_units function

<dl><dt>all_columns</dt>
<dd>(optional, logical) If TRUE, all columns are returned. Default: FALSE</dd>
<dt>class</dt>
<dd>(optional, class name). Used to filter rows and columns. Accepted values are "numeric", "Date", and "POSIXct". Default: NULL</dd></dl>

Arguments

Data Frame with Supported Time Units — utils_time_units

<dl>

<dt>all_columns</dt>
<dd>(optional, logical) If TRUE, all columns are returned. Default: FALSE</dd>


<dt>class</dt>
<dd>(optional, class name). Used to filter rows and columns. Accepted values are "numeric", "Date", and "POSIXct". Default: NULL</dd>

</dl>

utils_time_units: Data Frame with Supported Time Units

Description

Usage

Value

Arguments

See Also

Examples