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caretForecast  

Conformal Time Series Forecasting Using State of Art Machine Learning Algorithms
View on CRAN: Click here


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

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

Install by package version:
library("remotes")
install_version("caretForecast", "0.1.1")



Attach the package and use:
library("caretForecast")
Maintained by
Resul Akay
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2022-01-27
Latest Update: 2022-10-24
Description:
Conformal time series forecasting using the caret infrastructure. It provides access to state-of-the-art machine learning models for forecasting applications. The hyperparameter of each model is selected based on time series cross-validation, and forecasting is done recursively.
How to cite:
Resul Akay (2022). caretForecast: Conformal Time Series Forecasting Using State of Art Machine Learning Algorithms. R package version 0.1.1, https://cran.r-project.org/web/packages/caretForecast. Accessed 27 Jun. 2026.
Previous versions and publish date:
0.0.2 (2022-01-27 09:20), 0.0.3 (2022-05-03 00:22), 0.1.1 (2022-10-24 09:05), 0.1.2 (2026-01-30 07:10)
Other packages that cited caretForecast R package
View caretForecast citation profile
Other R packages that caretForecast depends, imports, suggests or enhances
Complete documentation for caretForecast
Functions, R codes and Examples using the caretForecast R package
Some associated functions: ARml . conformalRegressor . forecast.ARml . get_var_imp . predict.conformalRegressor . reexports . retail . retail_wide . split_ts . suggested_methods . 
Some associated R codes: arml.R . fit_conformal_reg.R . forecast.R . predict_conformal.R . utils.R .  Full caretForecast package functions and examples
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