Other packages > Find by keyword >

SVMD  

Spearman Variational Mode Decomposition
View on CRAN: Click here


Download and install SVMD package within the R console
Install from CRAN:
install.packages("SVMD")

Install from Github:
library("remotes")
install_github("cran/SVMD")

Install by package version:
library("remotes")
install_version("SVMD", "0.1.0")



Attach the package and use:
library("SVMD")
Maintained by
Dr. Himadri Shekhar Roy
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2024-09-16
Latest Update: 2024-09-16
Description:
In practice, it is difficult to determine the number of decomposition modes, K, for Variational Mode Decomposition (VMD). To overcome this issue, this study offers Spearman Variational Mode Decomposition (SVMD), a method that uses the Spearman correlation coefficient to calculate the ideal mode number. Unlike the Pearson correlation coefficient, which only returns a perfect value when X and Y are linearly connected, the Spearman correlation can be calculated without knowing the probability distributions of X and Y. The Spearman correlation coefficient, also called Spearman's rank correlation coefficient, is a subset of a wider correlation coefficient. As VMD decomposes a signal, the Spearman correlation coefficient between the reconstructed and original sequences rises as the mode number K increases. Once the signal has been fully decomposed, subsequent increases in K cause the correlation to gradually level off. When the correlation reaches a specific level, VMD is said to have adequately decomposed the signal. Numerous experiments revealed that a threshold of 0.997 produces the best denoising effect, so the threshold is set at 0.997. This package has been developed using concept of Yang et al. (2021)<doi:10.1016/j.aej.2021.01.055>.
How to cite:
Dr. Himadri Shekhar Roy (2024). SVMD: Spearman Variational Mode Decomposition. R package version 0.1.0, https://cran.r-project.org/web/packages/SVMD. Accessed 28 Sep. 2024.
Previous versions and publish date:
No previous versions
Other packages that cited SVMD R package
View SVMD citation profile
Other R packages that SVMD depends, imports, suggests or enhances
Complete documentation for SVMD
Functions, R codes and Examples using the SVMD R package
Full SVMD package functions and examples
Downloads during the last 30 days
Get rewarded with contribution points by helping add
Reviews / comments / questions /suggestions ↴↴↴

Today's Hot Picks in Authors and Packages

mbRes  
Exploration of Multiple Biomarker Responses using Effect Size
Summarize multiple biomarker responses of aquatic organisms to contaminants using Cliff ...
Download / Learn more Package Citations See dependency  
mhtboot  
Multiple Hypothesis Test Based on Distribution of p Values
A framework for multiple hypothesis testing based on distribution of p values. It is well known tha ...
Download / Learn more Package Citations See dependency  
semTable  
Structural Equation Modeling Tables
For confirmatory factor analysis ('CFA') and structural equation models ('SEM') estimated with the ...
Download / Learn more Package Citations See dependency  
plm  
Linear Models for Panel Data
A set of estimators for models and (robust) covariance matrices, and tests for panel data econometr ...
Download / Learn more Package Citations See dependency  
baseballr  
Acquiring and Analyzing Baseball Data
Provides numerous utilities for acquiring and analyzing baseball data from online sources such as ' ...
Download / Learn more Package Citations See dependency  
quickcode  
Quick and Essential 'R' Tricks for Better Scripts
The NOT functions, 'R' tricks and a compilation of some simple quick plus often used 'R' codes to im ...
Download / Learn more Package Citations See dependency  

22,869

R Packages

195,887

Dependencies

63,882

Author Associations

22,870

Publication Badges

© Copyright 2022 - present. All right reserved, rpkg.net.  Based in Cambridge, Massachusetts, USA