T‐calibration in semi‐parametric models

Abstract This article relates the calibration of models to the consistent loss functions for the target functional of the model. Correctly specified models are calibrated. Conversely, we demonstrate that if there is a parameter value that is optimal under all consistent loss functions, then a model is calibrated.

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Publication Details

Journal
Canadian Journal of Statistics
Published
2026-01-08
DOI
https://doi.org/10.1002/cjs.70035
Citations
1
Primary Topic
Statistical Methods and Inference
Type
article
Field-Weighted Citation Impact
41.27
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article

T‐calibration in semi‐parametric models

Johanna F. Ziegel
1 citations
Canadian Journal of Statistics
Statistical Methods and Inference
41.27
article

T‐calibration in semi‐parametric models

Johanna F. Ziegel
article en
1 citations

Abstract

Abstract This article relates the calibration of models to the consistent loss functions for the target functional of the model. Correctly specified models are calibrated. Conversely, we demonstrate that if there is a parameter value that is optimal under all consistent loss functions, then a model is calibrated.

Canadian Journal of StatisticsVol. 54(1)
University of Bern (CH), Bern University of Applied Sciences (CH), ETH Zurich (CH), Institute for Biomedical Engineering (CH), Zurich University of Teacher Education (CH)
Reduced inequalities
Openalex Percentile: Top 1%
Statistical Methods and Inference
41.27
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