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.

A consistent interface to encrypt and decrypt strings, R objects and files using symmetric and asymmetric key encryption.

Functions to design and apply tests that are anytime valid. The
  functions can be used to design hypothesis tests in the prospective/randomised
  control trial setting or in the observational/retrospective setting. The
  resulting tests remain valid under both optional stopping and optional
  continuation. The current version includes safe t-tests and safe tests of
  two proportions. For details on the theory of safe tests, see
  Grunwald, de Heide and Koolen (2019) "Safe Testing" <arXiv:1906.07801>, 
  for details on safe logrank tests see ter Schure, Perez-Ortiz, Ly and Grunwald
  (2020) "The Safe Logrank Test: Error Control under Continuous Monitoring with 
  Unlimited Horizon" <arXiv:2011.06931v3> and Turner, Ly and Grunwald (2021)
  "Safe Tests and Always-Valid Confidence Intervals for contingency tables and 
  beyond" <arXiv:2106.02693> for details on safe contingency table tests.

A file format for storing tensors that is secure (doesn't allow for
    code execution), fast and simple to implement. 'safetensors' also enables cross
    language and cross frameworks compatibility making it an ideal format for
    storing machine learning model weights.

Contains chart code for monitoring clinical trial safety. Charts can be used as standalone output, but are also designed for use with the 'safetyGraphics' package, which makes it easy to load data and customize the charts using an interactive web-based interface created with Shiny.