Analysis of regression in game theory approach

DOI10.1002/asmb.446zbMath1008.62041OpenAlexW1971916086WikidataQ56505274 ScholiaQ56505274MaRDI QIDQ4781100

Stan Lipovetsky, Michael Conklin

Publication date: 21 November 2002

Published in: Applied Stochastic Models in Business and Industry (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1002/asmb.446

zbMATH Keywords

Shapley valuemulticollinearityregressor net effects

Mathematics Subject Classification ID

Nonparametric regression and quantile regression (62G08) Nonparametric estimation (62G05) Cooperative games (91A12)

Related Items (19)

Measuring the relevance of factors in the occurrences of events ⋮ Variance allocation and Shapley value ⋮ Linear regression with special coefficient features attained via parameterization in exponential, logistic, and multinomial-logit forms ⋮ OnML: an ontology-based approach for interpretable machine learning ⋮ Causality Modeling and Statistical Generative Mechanisms ⋮ Tail variance allocation, Shapley value, and the majorization problem ⋮ SURF — STRUCTURAL UNDUPLICATED REACH AND FREQUENCY: LATENT CLASS TURF AND SHAPLEY VALUE ANALYSES ⋮ Cooperative games on simplicial complexes ⋮ Regression games ⋮ Predictor relative importance and matching regression parameters ⋮ Do not adjust coefficients in Shapley value regression ⋮ Explaining predictive models using Shapley values and non-parametric vine copulas ⋮ On the comparison of Shapley values for variance and standard deviation games ⋮ Unnamed Item ⋮ Information importance of predictors: concept, measures, Bayesian inference, and applications ⋮ Antagonistic and bargaining games in optimal marketing decisions ⋮ A theory of dichotomous valuation with applications to variable selection ⋮ Wasserstein-based fairness interpretability framework for machine learning models ⋮ Latent class regression model in IRLS approach

Uses Software

• alr3

Cites Work

• Unnamed Item
• Unnamed Item
• Unnamed Item
• Unnamed Item
• Linear methods in multimode data analysis for decision making
• A decision-theoretic generalization of on-line learning and an application to boosting
• Canonical correlation analyses for three data sets: A unified framework with application to management
• Modelling and forecasting with robust canonical analysis: Method and application
• A globally concave, monotone and flexible cost function: derivation and application
• Multiple Comparisons
• The Shapley Value as a von Neumann-Morgenstern Utility
• Generalized Inverses, Ridge Regression, Biased Linear Estimation, and Nonlinear Estimation

This page was built for publication: Analysis of regression in game theory approach