The adaptive LASSO regression and empirical mode decomposition algorithm for enhancing modelling accuracy
From MaRDI portal
Publication:6552975
DOI10.1080/03610918.2022.2032154MaRDI QIDQ6552975
Abdullah S. al-Jawarneh, Mohd. Tahir Ismail
Publication date: 11 June 2024
Published in: Communications in Statistics. Simulation and Computation (Search for Journal in Brave)
Cites Work
- Title not available (Why is that?)
- Title not available (Why is that?)
- Title not available (Why is that?)
- The Adaptive Lasso and Its Oracle Properties
- Application of empirical mode decomposition with local linear quantile regression in financial time series forecasting
- Advanced algorithms for penalized quantile and composite quantile regression
- The role of functional data analysis for instantaneous frequency estimation
- Phase and multifractality analyses of random price time series by finite-range interacting biased voter system
- High-dimensional regression in practice: an empirical study of finite-sample prediction, variable selection and ranking
- Lasso Regression Based on Empirical Mode Decomposition
- The empirical mode decomposition and the Hilbert spectrum for nonlinear and non-stationary time series analysis
- Variable Selection via Nonconcave Penalized Likelihood and its Oracle Properties
- Hilbert–Huang Transform and Its Applications
- Ridge Regression: Biased Estimation for Nonorthogonal Problems
- Improving accuracy models using elastic net regression approach based on empirical mode decomposition
This page was built for publication: The adaptive LASSO regression and empirical mode decomposition algorithm for enhancing modelling accuracy
Report a bug (only for logged in users!)Click here to report a bug for this page (MaRDI item Q6552975)