MINIMIZING AVERAGE RISK IN REGRESSION MODELS
Explore this paper's citation graph
Summary
The weighted focused information criteria (wFIC) method, which allows one to rank and select candidate models for the purpose of handling a range of similar tasks well, is extended to weighted versions.
- Type
- article
- Published
- 2008-01-15
- Cited by
- 43
- References
- 25
- OpenAlex
- https://openalex.org/W2094776705
- Semantic Scholar
- https://api.semanticscholar.org/CorpusID:122958146
Keywords
Covariate, Selection (genetic algorithm), Model selection, Information Criteria, Inference
References
- Robustness Aspects of Model Choice
- Some Comments on Cp
- A Robust Version of Mallows's C P
- On Predictive Least Squares Principles
- Focused Information Criteria and Model Averaging for the Cox Hazard Regression Model
- An Asymptotic Theory of Bayesian Inference for Time Series
- Variable Selection for Logistic Regression Using a Prediction‐Focused Information Criterion
- The Wisconsin epidemiologic study of diabetic retinopathy. II. Prevalence and risk of diabetic retinopathy when age at diagnosis is less than 30 years.
- Generalized Linear Models
- Bayesian Estimation and Prediction Using Asymmetric Loss Functions
- The Focused Information Criterion
- Frequentist Model Average Estimators
- More comments on C p
- CHALLENGES FOR ECONOMETRIC MODEL SELECTION
- An Introduction to Generalized Linear Models
- A new look at the statistical model identification
- Estimating the Dimension of a Model
- Applied Linear Regression, 2nd Edition.
- Applied Linear Regression
- Discussion: Rejoinder to 'The focussed information criterion' and 'Frequentist model averaging'
Cited by
- On focussed and less focussed model selection
- Choice is Suffering: A Focused Information Criterion for Model Selection Activation Program for Disadvantaged Youths
- Model Uncertainty and Robustness Tests: Towards a New Logic of Statistical Inference
- Structure learning using a focused information criterion in graphical models
- A General Family of Penalties for Combining Differing Types of Penalties in Generalized Structured Models
- Model Averaging in Predictive Regressions
- ORDER SELECTION IN ARMA MODELS USING THE FOCUSED INFORMATION CRITERION
- Model selection for estimating treatment effects
- Energy substitution: When model selection depends on the focus
- Frequentist Model Averaging with missing observations
- A focused information criterion for graphical models
- Focused Information Criteria, Model Selection, and Model Averaging in a Tobit Model With a Nonzero Threshold
- A uniform framework for the combination of penalties in generalized structured models
- Focused estimation and model averaging with penalization methods: an overview
- Focused model selection in quantile regression
- Generalized Empirical Likelihood-Based Focused Information Criterion and Model Averaging
- Focused Estimation and Model Averaging for High-Dimensional Data, An Overview
- An Akaike-type information criterion for model selection under inequality constraints
- Regularization and model selection with categorical predictors and effect modifiers in generalized linear models
- Model Uncertainty & Model Averaging Techniques
Related papers
- On Fractile Transformation of Covariates in Regression
- MODEL SELECTION AND INFERENCE: FACTS AND FICTION
- Linear regression model selection using p-values when the model dimension grows
- Linear Model Selection when Covariates Contain Errors
- Bayesian model choice and information criteria in sparse generalized linear models
- A comparison of methods for the fitting of generalized additive models