The role of green energy stock market in forecasting China's crude oil market: An application of IIS approach and sparse regression models
This study investigates the effectiveness of sparse regression models with their diverse
specifications and the impulse indicator saturation (IIS) method in forecasting crude oil …
specifications and the impulse indicator saturation (IIS) method in forecasting crude oil …
[HTML][HTML] On the use of a new probabilistic model and machine learning methods with applications to reliability and music engineering
M Zhang, Y Jia, JT Seong, E Alshawarbeh… - Alexandria Engineering …, 2024 - Elsevier
In this paper, we considered a new probability distribution with new applications in the field
of engineering, in particular, in music engineering. The new probability distribution is mainly …
of engineering, in particular, in music engineering. The new probability distribution is mainly …
Comparison of Weighted Lag Adaptive LASSO with Autometrics for Covariate Selection and Forecasting Using Time‐Series Data
In order to reduce the dimensionality of parameter space and enhance out‐of‐sample
forecasting performance, this research compares regularization techniques with Autometrics …
forecasting performance, this research compares regularization techniques with Autometrics …
Cross‐Sectional Analysis of Impulse Indicator Saturation Method for Outlier Detection Estimated via Regularization Techniques with Application of COVID‐19 Data
S Muhammadullah, A Urooj, MH Mengal… - … Methods in Medicine, 2022 - Wiley Online Library
Impulse indicator saturation is a popular method for outlier detection in time series modeling,
which outperforms the least trimmed squares (LTS), M‐estimator, and MM‐estimator …
which outperforms the least trimmed squares (LTS), M‐estimator, and MM‐estimator …
[HTML][HTML] Can Denoising Enhance Prediction Accuracy of Learning Models? A Case of Wavelet Decomposition Approach
Denoising is an integral part of the data pre-processing pipeline that often works in
conjunction with model development for enhancing the quality of data, improving model …
conjunction with model development for enhancing the quality of data, improving model …
[HTML][HTML] Analysis of Fat Big Data Using Factor Models and Penalization Techniques: A Monte Carlo Simulation and Application
F Khan, O Albalawi - Axioms, 2024 - mdpi.com
This article assesses the predictive accuracy of factor models utilizing Partial· Least·
Squares (PLS) and Principal· Component· Analysis (PCA) in comparison to autometrics and …
Squares (PLS) and Principal· Component· Analysis (PCA) in comparison to autometrics and …