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", "1.0.787")



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 1.0.787, https://cran.r-project.org/web/packages/tspredit. Accessed 22 Dec. 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), 1.0.777 (2024-07-29 16:20)
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

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  
wordspace  
Distributional Semantic Models in R
An interactive laboratory for research on distributional semantic models ('DSM', see < ...
Download / Learn more Package Citations See dependency  
tropAlgebra  
Tropical Algebraic Functions
It includes functions like tropical addition, tropical multiplication for vectors and matrices. In t ...
Download / Learn more Package Citations See dependency  
composits  
Compositional, Multivariate and Univariate Time Series Outlier Ensemble
A compositional multivariate and univariate time series outlier ensemble.It uses the four R packages ...
Download / Learn more Package Citations See dependency  
elect  
Estimation of Life Expectancies Using Multi-State Models
Functions to compute state-specific and marginal life expectancies. The computation is based on a fi ...
Download / Learn more Package Citations See dependency  
dmlalg  
Double Machine Learning Algorithms
Implementation of double machine learning (DML) algorithms in R, based on Emmenegger and Buehlmann ...
Download / Learn more Package Citations See dependency  

23,394

R Packages

201,798

Dependencies

63,416

Author Associations

23,395

Publication Badges

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