Other packages > Find by keyword >

InterNL  

Time Series Intervention Model Using Non-Linear Function
View on CRAN: Click here


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

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

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



Attach the package and use:
library("InterNL")
Maintained by
Dr. Md Yeasin
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2024-04-18
Latest Update: 2024-04-18
Description:
Intervention analysis is used to investigate structural changes in data resulting from external events. Traditional time series intervention models, viz. Autoregressive Integrated Moving Average model with exogeneous variables (ARIMA-X) and Artificial Neural Networks with exogeneous variables (ANN-X), rely on linear intervention functions such as step or ramp functions, or their combinations. In this package, the Gompertz, Logistic, Monomolecular, Richard and Hoerl function have been used as non-linear intervention function. The equation of the above models are represented as: Gompertz: A * exp(-B * exp(-k * t)); Logistic: K / (1 + ((K - N0) / N0) * exp(-r * t)); Monomolecular: A * exp(-k * t); Richard: A + (K - A) / (1 + exp(-B * (C - t)))^(1/beta) and Hoerl: a*(b^t)*(t^c).This package introduced algorithm for time series intervention analysis employing ARIMA and ANN models with a non-linear intervention function. This package has been developed using algorithm of Yeasin et al. <doi:10.1016/j.hazadv.2023.100325> and Paul and Yeasin <doi:10.1371/journal.pone.0272999>.
How to cite:
Dr. Md Yeasin (2024). InterNL: Time Series Intervention Model Using Non-Linear Function. R package version 0.1.0, https://cran.r-project.org/web/packages/InterNL. Accessed 21 Nov. 2024.
Previous versions and publish date:
No previous versions
Other packages that cited InterNL R package
View InterNL citation profile
Other R packages that InterNL depends, imports, suggests or enhances
Complete documentation for InterNL
Functions, R codes and Examples using the InterNL R package
Full InterNL 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

crossrun  
Joint Distribution of Number of Crossings and Longest Run
Joint distribution of number of crossings and the longest run in a series of independent Bernoulli ...
Download / Learn more Package Citations See dependency  
deductive  
Data Correction and Imputation Using Deductive Methods
Attempt to repair inconsistencies and missing values in data records by using information from vali ...
Download / Learn more Package Citations See dependency  
r2resize  
In-Text Resize for Images, Tables and Fancy Resize Containers in 'shiny', 'rmarkdown' and 'quarto' Documents
Automatic resizing toolbar for containers, images and tables. Various resizable or expandable contai ...
Download / Learn more Package Citations See dependency  
kgschart  
KGS Rank Graph Parser
Restore underlining numeric data from rating history graph of KGS (an online platform of the game o ...
Download / Learn more Package Citations See dependency  
pkgdepends  
Package Dependency Resolution and Downloads
Find recursive dependencies of 'R' packages from various sources. Solve the dependencies to obtain ...
Download / Learn more Package Citations See dependency  
SCBiclust  
Identifies Mean, Variance, and Hierarchically Clustered Biclusters
Identifies a bicluster, a submatrix of the data such that the features and observations within the s ...
Download / Learn more Package Citations See dependency  

23,229

R Packages

199,929

Dependencies

62,984

Author Associations

23,230

Publication Badges

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