SAFEPG: A Novel SAFE Model for Predicting Climate-Related Extreme Losses

The goal of 'SAFEPG' is to predict climate-related extreme losses by fitting a frequency-severity model. It improves predictive performance by introducing a sign-aligned regularization term, which ensures consistent signs for the coefficients across the frequency and severity components. This enhancement not only increases model accuracy but also enhances its interpretability, making it more suitable for practical applications in risk assessment.

Version:	0.0.1
Depends:	R (≥ 3.5.0)
Imports:	stats, Matrix, methods
Suggests:	knitr, rmarkdown
Published:	2025-05-09
Author:	Qian Tang [aut, cre], Yikai Zhang [aut], Boxiang Wang [aut]
Maintainer:	Qian Tang <qian-tang at uiowa.edu>
License:	GPL-2
NeedsCompilation:	yes
CRAN checks:	SAFEPG results

Documentation:

Reference manual:	SAFEPG.pdf
Vignettes:	SAFEPG (source, R code)

Downloads:

Package source:	SAFEPG_0.0.1.tar.gz
Windows binaries:	r-devel: not available, r-release: not available, r-oldrel: not available
macOS binaries:	r-release (arm64): SAFEPG_0.0.1.tgz, r-oldrel (arm64): SAFEPG_0.0.1.tgz, r-release (x86_64): SAFEPG_0.0.1.tgz, r-oldrel (x86_64): SAFEPG_0.0.1.tgz

Linking:

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