data_nextpoint_em

<p>Data containing 'next point selected' information for emulation algorithm in vignette comparing emulation and parametric algorithms. For generation, see hidden code in vignette, or in pipeline at https://github.com/jamesliley/OptHoldoutSize_pipelines</p>

data

aspre

Predictive scores must be updated with care, because actions taken on the basis of existing risk scores causes bias in risk estimates from the updated score. A holdout set is a straightforward way to manage this problem: a proportion of the population is 'held-out' from computation of the previous risk score. This package provides tools to estimate a size for this holdout set and associated errors. Comprehensive vignettes are included. Please see: Haidar-Wehbe S, Emerson SR, Aslett LJM, Liley J (2022) <doi:10.48550/arXiv.2202.06374> (to appear in Annals of Applied Statistics) for details of methods.

James Liley

OptHoldoutSize

Estimation of Optimal Size for a Holdout Set for Updating a
Predictive Score

Sami Haidar-Wehbe

Sam Emerson

Louis Aslett

data_nextpoint_em function

<p>An object of class <code>list</code> of length 6.</p>

Format

Data for 'next point' demonstration vignette on algorithm comparison using emulation algorithm — data_nextpoint_em

Data for 'next point' demonstration vignette on algorithm comparison using emulation algorithm

data_nextpoint_em: Data for 'next point' demonstration vignette on algorithm comparison using emulation algorithm

Description

Usage

Arguments

Format