How to compare interpretatively different models for the conditional variance function

DOI10.1080/02664760902984642OpenAlexW2089032691MaRDI QIDQ5123593

Ilmari Juutilainen, Juha Röning

Publication date: 29 September 2020

Published in: Journal of Applied Statistics (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1080/02664760902984642

zbMATH Keywords

variance functionpredictive likelihoodconditional variancepredictive densitylog-scoring rulemodel performance measureout-of-sample testing

Mathematics Subject Classification ID

Statistics (62-XX)

Uses Software

• GLIM
• UCI-ml

Cites Work

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• Predictive density and conditional confidence interval accuracy tests
• Estimation of the confidence limits for the quadratic forms in normal variables using a simple Gaussian distribution approximation
• Constructing Bayesian formulations of sparse kernel learning methods
• A TEST FOR COMPARING MULTIPLE MISSPECIFIED CONDITIONAL INTERVAL MODELS
• Robust Linear Model Selection by Cross-Validation
• Strictly Proper Scoring Rules, Prediction, and Estimation
• Tests of Conditional Predictive Ability
• Probabilistic Forecasts, Calibration and Sharpness
• Likelihood-Based Local Linear Estimation of the Conditional Variance Function

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