Suchergebnisse - "RIDGE regression (Statistics)"

New kinds of biased estimators for linear regression model.

Autoren: Alheety, Mustafa. I. Alanaz, Mazin M. Al-Thanoon, Niam Abdulmunim et al.

Quelle: Communications in Statistics: Simulation & Computation. Oct2025, p1-10. 10p.

Schlagwörter: *REGRESSION analysis, *ESTIMATION bias, *SIMULATION methods & models, RIDGE regression (Statistics), GOODNESS-of-fit tests, MULTICOLLINEARITY, MEAN square algorithms

On some new and old shrinkage estimators in ridge regression model.

Autoren: Khalid, Nida Muhammad Khan, Dost Suhail, Muhammad et al.

Quelle: Communications in Statistics: Simulation & Computation. Oct2025, p1-31. 31p. 9 Illustrations.

Schlagwörter: *MONTE Carlo method, RIDGE regression (Statistics), MULTICOLLINEARITY, MEAN square algorithms, RESEARCH evaluation

Comparison of behavior of standardized Pearson residuals in different diagnostics measures for Gamma-Pareto regression and Gamma-Pareto ridge regression model.

Autoren: Saleem, Nasir Akbar, Atif

Quelle: Communications in Statistics: Simulation & Computation. Oct2025, p1-22. 22p. 2 Illustrations.

Schlagwörter: *QUANTITATIVE research, *REGRESSION analysis, RIDGE regression (Statistics), OUTLIERS (Statistics), DIAGNOSIS

How well do ridge parameter estimators proposed so far perform in terms of normality, outlier detection, and MSE criteria?

Autoren: Mermi, Selman Göktaş, Atila Akkuş, Özge

Quelle: Communications in Statistics: Simulation & Computation. 2025, Vol. 54 Issue 11, p4841-4907. 67p.

Schlagwörter: *MONTE Carlo method, *PARAMETER estimation, RIDGE regression (Statistics), OUTLIER detection, LOSS functions (Statistics), RANK correlation (Statistics), MULTICOLLINEARITY

Personalized Differential Privacy for Ridge Regression Under Output Perturbation.

Autoren: Acharya, Krishna Boenisch, Franziska Naidu, Rakshit et al.

Quelle: Naval Research Logistics. Oct2025, p1. 13p. 8 Illustrations.

Schlagwörter: *RIGHT of privacy, RIDGE regression (Statistics), MACHINE learning, DATA protection software, PERTURBATION theory

Ridging out many covariates.

Autoren: Anatolyev, Stanislav¹ (AUTHOR) sanatoly@nes.ru

Quelle: Communications in Statistics: Theory & Methods. 2025, Vol. 54 Issue 24, p8064-8078. 15p.

Schlagwörter: *SIMULATION methods & models, RIDGE regression (Statistics), RANDOM effects model, MATHEMATICAL regularization, ASYMPTOTIC distribution, CONFOUNDING variables, HETEROSCEDASTICITY

A new robust ridge estimator for linear regression model with non normal, heteroscedastic and autocorrelated errors.

Autoren: Chand, Sohail Shabbir, Maha

Quelle: Communications in Statistics: Theory & Methods. 2025, Vol. 54 Issue 23, p7651-7667. 17p.

Schlagwörter: *MONTE Carlo method, RIDGE regression (Statistics), MULTICOLLINEARITY, MEAN square algorithms, AUTOCORRELATION (Statistics), MEASUREMENT uncertainty (Statistics), HETEROSCEDASTICITY, ADAPTIVE estimation (Statistics)

Shrinkage estimations of semi-parametric models for high-dimensional data in finite mixture models.

Autoren: Rahimi, Soghra Eskandari, Farzad

Quelle: Communications in Statistics: Theory & Methods. 2025, Vol. 54 Issue 19, p6264-6276. 13p.

Schlagwörter: *BIG data, *FORECASTING, FINITE mixture models (Statistics), RIDGE regression (Statistics), EXPECTATION-maximization algorithms, MATHEMATICAL simplification, STATISTICAL models

Virtue or Mirage? Complexity in Exchange Rate Prediction.

Autoren: Kılıç, Rehim¹ rehim.kilic@frb.gov

Quelle: Working Papers: U.S. Federal Reserve Board's Finance & Economic Discussion Series. Sep2025, p1-39. 40p.

Schlagwörter: *FORECASTING, *MARKET timing, *FOREIGN exchange rates, *LINEAR statistical models, *ECONOMIC indicators, RIDGE regression (Statistics), COMPUTATIONAL complexity

Simulation study of recent ridge parameter for different ridge estimators.

Autoren: Mohammed, Fatima Salih Alheety, Mustafa I. N.

Quelle: AIP Conference Proceedings. 2025, Vol. 3395 Issue 1, p1-23. 23p.

Schlagwörter: *RIDGE regression (Statistics), *REGULARIZATION parameter, *MEAN square algorithms, *NUMERICAL analysis, *SIMULATION methods & models

New biased and unbiased convex estimators for regression model.

Autoren: Saray, Karam Fouad Alheety, Mustafa I. N.

Quelle: AIP Conference Proceedings. 2025, Vol. 3395 Issue 1, p1-22. 22p.

Schlagwörter: *REGRESSION analysis, *RIDGE regression (Statistics), *SIMULATION methods & models, *LEAST squares, *MEAN square algorithms

Optimal ridge estimation in the restricted logistic semiparametric regression models using generalized cross-validation.

Autoren: Roozbeh, Mahdi¹ (AUTHOR) mahdi.roozbeh@semnan.ac.ir

Quelle: Journal of Applied Statistics. Aug2025, p1-20. 20p. 5 Illustrations.

Schlagwörter: *MONTE Carlo method, LOGISTIC regression analysis, RIDGE regression (Statistics), SMOOTHING (Numerical analysis), MULTICOLLINEARITY, MODEL validation, MAXIMUM likelihood statistics

Ridge-penalized Zero-Inflated Probit Bell model for multicollinearity in count data.

Autoren: Ali, Essoham Lukman, Adewale F.

Quelle: Journal of Applied Statistics. Jul2025, p1-26. 26p. 8 Illustrations.

Schlagwörter: *PARAMETER estimation, *STATISTICS, *ZERO-inflated probability distribution, MULTICOLLINEARITY, RIDGE regression (Statistics), STATISTICS methodology, STATISTICAL models

Ridge estimation strategies for the simplex regression model with different link functions: simulation and applications.

Autoren: Nisa, Aaiza Amin, Muhammad Cheema, Maryam

Quelle: Communications in Statistics: Simulation & Computation. Jul2025, p1-29. 29p. 28 Illustrations.

Schlagwörter: *SIMULATION methods & models, *REGRESSION analysis, *MATHEMATICAL statistics, MULTICOLLINEARITY, RIDGE regression (Statistics), MAXIMUM likelihood statistics, MEAN square algorithms

A robust hybrid ridge estimation framework using scaled error variance and M-estimation in contaminated linear models.

Autoren: Rehman, Abdur Dar, Irum Sajjad Chand, Sohail

Quelle: Communications in Statistics: Theory & Methods. Sep2025, p1-25. 25p. 4 Illustrations.

Schlagwörter: *ESTIMATION theory, OUTLIERS (Statistics), RIDGE regression (Statistics), ADAPTIVE estimation (Statistics), MULTICOLLINEARITY, ROBUST statistics, MEAN square algorithms

Improved ridge regression estimators for multicollinearity and heteroscedasticity: A simulation and real-world study.

Autoren: Mashal Asim, Syed Muhammad Suhail, Muhammad

Quelle: Communications in Statistics: Theory & Methods. Aug2025, p1-21. 21p. 8 Illustrations.

Schlagwörter: *SIMULATION methods & models, *ESTIMATION theory, *EMPIRICAL research, RIDGE regression (Statistics), MULTICOLLINEARITY, HETEROSCEDASTICITY, MEAN square algorithms, LIVESTOCK farms

A novel zero-inflated regression model for overdispersed count data with enhancing its estimation for multicollinearity in medical data.

Autoren: El-Alosey, Alaa R. Hammad, Ali T. Gemeay, Ahmed M.

Quelle: Statistics. Dec2025, Vol. 59 Issue 6, p1463-1494. 32p.

Schlagwörter: *MULTICOLLINEARITY, *RIDGE regression (Statistics), *MEDICAL databases, *ZERO-inflated probability distribution, *STATISTICAL models

Bioinformatics and machine learning-based simultaneous spectrophotometric identification of Montelukast sodium and Desloratadine in a commercial film-coated tablet.

Autoren: Demirkaya Miloglu, Fatma Bayrak, Burak Kucuk, Hira Beril et al.

Quelle: Journal of Analytical Science & Technology. 11/18/2025, Vol. 16 Issue 1, p1-11. 11p.

Schlagwörter: *MACHINE learning, *RIDGE regression (Statistics), *SPECTROPHOTOMETRY, *MONTELUKAST, *BIOINFORMATICS software, *ANTIALLERGIC agents, *DRUG analysis, *SUSTAINABLE chemistry

Novel Data-Driven Shrinkage Ridge Parameters for Handling Multicollinearity in Regression Models with Environmental and Chemical Data Applications.

Autoren: Alharthi, Muteb Faraj¹ (AUTHOR)

Quelle: Axioms (2075-1680). Nov2025, Vol. 14 Issue 11, p812. 15p.

Schlagwörter: *MULTICOLLINEARITY, *RIDGE regression (Statistics), *REGULARIZATION parameter, *ENVIRONMENTAL databases, *MONTE Carlo method, *PARAMETER estimation, *REGRESSION analysis

An optimized ridge regression for forecasting time series with a fixed period.

Autoren: Han, Chuang Zhou, Yusen Sun, Jiajia et al.

Quelle: Pattern Recognition Letters. Nov2025, Vol. 197, p274-281. 8p.

Schlagwörter: *RIDGE regression (Statistics), *FORECASTING, *OPTIMIZATION algorithms, *TIME series analysis, *ECONOMIC seasonal variations, *METAHEURISTIC algorithms