Other packages > Find by keyword >

tsensembler  

Dynamic Ensembles for Time Series Forecasting
View on CRAN: Click here


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

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

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



Attach the package and use:
library("tsensembler")
Maintained by
Vitor Cerqueira
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2017-08-28
Latest Update: 2020-10-27
Description:
A framework for dynamically combining forecasting models for time series forecasting predictive tasks. It leverages machine learning models from other packages to automatically combine expert advice using metalearning and other state-of-the-art forecasting combination approaches. The predictive methods receive a data matrix as input, representing an embedded time series, and return a predictive ensemble model. The ensemble use generic functions 'predict()' and 'forecast()' to forecast future values of the time series. Moreover, an ensemble can be updated using methods, such as 'update_weights()' or 'update_base_models()'. A complete description of the methods can be found in: Cerqueira, V., Torgo, L., Pinto, F., and Soares, C. "Arbitrated Ensemble for Time Series Forecasting." to appear at: Joint European Conference on Machine Learning and Knowledge Discovery in Databases. Springer International Publishing, 2017; and Cerqueira, V., Torgo, L., and Soares, C.: "Arbitrated Ensemble for Solar Radiation Forecasting." International Work-Conference on Artificial Neural Networks. Springer, 2017 <doi:10.1007/978-3-319-59153-7_62>.
How to cite:
Vitor Cerqueira (2017). tsensembler: Dynamic Ensembles for Time Series Forecasting. R package version 0.1.0, https://cran.r-project.org/web/packages/tsensembler. Accessed 07 Jun. 2026.
Previous versions and publish date:
0.0.2 (2017-08-28 14:20), 0.0.3 (2018-03-10 19:30), 0.0.4 (2018-04-13 22:11), 0.0.5 (2019-07-05 20:00)
Other packages that cited tsensembler R package
View tsensembler citation profile
Other R packages that tsensembler depends, imports, suggests or enhances
Complete documentation for tsensembler
Functions, R codes and Examples using the tsensembler R package
Some associated functions: ADE-class . ADE . DETS-class . DETS . EMASE . ade_hat-class . ade_hat . ae . base_ensemble-class . base_ensemble . base_models_loss . best_mvr . blocked_prequential . bm_cubist . bm_ffnn . bm_gaussianprocess . bm_gbm . bm_glm . bm_mars . bm_pls_pcr . bm_ppr . bm_randomforest . bm_svr . bm_xgb . build_base_ensemble . build_committee . combine_predictions . compute_predictions . dets_hat-class . dets_hat . embed_timeseries . get_target . get_top_models . get_y . holdout . intraining_estimations . intraining_predictions . l1apply . learning_base_models . loss_meta_learn . meta_cubist . meta_cubist_predict . meta_ffnn . meta_ffnn_predict . meta_gp . meta_gp_predict . meta_lasso . meta_lasso_predict . meta_mars . meta_mars_predict . meta_pls . meta_pls_predict . meta_ppr . meta_ppr_predict . meta_predict . meta_rf . meta_rf_predict . meta_svr . meta_svr_predict . meta_xgb . meta_xgb_predict . model_recent_performance . model_specs-class . model_specs . model_weighting . mse . normalize . predict-methods . predict_pls_pcr . proportion . rbind_l . recent_lambda_observations . rmse . roll_mean_matrix . se . select_best . sequential_reweighting . sliding_similarity . soft.completion . softmax . split_by . train_ade . train_ade_quick . tsensembler . update_ade . update_ade_meta . update_base_models . update_weights . water_consumption . xgb_optimizer . xgb_predict . xgb_predict_ . 
Some associated R codes: data.R . ensembling-pipes.R . forecast.R . meta-modeling.R . sequential-reweight.R . ts-preprocess.R . utils.R .  Full tsensembler package functions and examples
Downloads during the last 30 days

Today's Hot Picks in Authors and Packages

keep  
Arrays with Better Control over Dimension Dropping
Provides arrays with flexible control over dimension dropping when subscripting. ...
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  
roxygen2  
In-Line Documentation for R
Generate your Rd documentation, 'NAMESPACE' file, and collation field using specially formatted com ...
Download / Learn more Package Citations See dependency  
embryogrowth  
Tools to Analyze the Thermal Reaction Norm of Embryo Growth
Tools to analyze the embryo growth and the sexualisation thermal reaction norms. See ...
Download / Learn more Package Citations See dependency  
cesR  
Access the Canadian Election Study Datasets
Makes accessing and loading the Canadian Election Study (, ...
Download / Learn more Package Citations See dependency  
gRain  
Bayesian Networks
Probability propagation in graphical independence networks, also known as Bayesian networks or prob ...
Download / Learn more Package Citations See dependency  

27,372

R Packages

233,548

Dependencies

72,820

Author Associations

27,205

Publication Badges

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