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r-qualv

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Qualitative methods for the validation of dynamic models. It contains (i) an orthogonal set of deviance measures for absolute, relative and ordinal scale and (ii) approaches accounting for time shifts. The first approach transforms time to take time delays and speed differences into account. The second divides the time series into interval units according to their main features and finds the longest common subsequence (LCS) using a dynamic programming algorithm.

Installation

To install this package, run one of the following:

Conda
$conda install conda-forge::r-qualv

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About

Summary

Qualitative methods for the validation of dynamic models. It contains (i) an orthogonal set of deviance measures for absolute, relative and ordinal scale and (ii) approaches accounting for time shifts. The first approach transforms time to take time delays and speed differences into account. The second divides the time series into interval units according to their main features and finds the longest common subsequence (LCS) using a dynamic programming algorithm.

Last Updated

Jul 2, 2023 at 19:54

License

GPL-2.0-or-later

Total Downloads

58.3K

Supported Platforms

macOS-64
win-64
linux-64