Other packages > Find by keyword >

tspredit  

Time Series Prediction Integrated Tuning
View on CRAN: Click here


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

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

Install by package version:
library("remotes")
install_version("tspredit", "1.0.777")



Attach the package and use:
library("tspredit")
Maintained by
Eduardo Ogasawara
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2023-07-19
Latest Update: 2023-12-22
Description:
Prediction is one of the most important activities while working with time series. There are many alternative ways to model the time series. Finding the right one is challenging to model them. Most data-driven models (either statistical or machine learning) demand tuning. Setting them right is mandatory for good predictions. It is even more complex since time series prediction also demands choosing a data pre-processing that complies with the chosen model. Many time series frameworks have features to build and tune models. The package differs as it provides a framework that seamlessly integrates tuning data pre-processing activities with the building of models. The package provides functions for defining and conducting time series prediction, including data pre(post)processing, decomposition, tuning, modeling, prediction, and accuracy assessment. More information is available at Izau et al. <doi:10.5753/sbbd.2022.224330>.
How to cite:
Eduardo Ogasawara (2023). tspredit: Time Series Prediction Integrated Tuning. R package version 1.0.777, https://cran.r-project.org/web/packages/tspredit. Accessed 21 Nov. 2024.
Previous versions and publish date:
1.0.707 (2023-07-19 17:20), 1.0.727 (2023-11-02 19:50), 1.0.737 (2023-11-09 17:40), 1.0.747 (2023-12-22 06:00), 1.0.767 (2024-03-26 03:20)
Other packages that cited tspredit R package
View tspredit citation profile
Other R packages that tspredit depends, imports, suggests or enhances
Complete documentation for tspredit
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

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  
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  
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  
RcppHNSW  
'Rcpp' Bindings for 'hnswlib', a Library for Approximate Nearest Neighbors
'Hnswlib' is a C++ library for Approximate Nearest Neighbors. This package provides a minimal R int ...
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  
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