gen_preds

Generate matrix of random observations. Observations are unit Gaussian-distributed.

Simulation

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

gen_preds function

<dl><dt>nobs</dt>
<dd>Number of observations (samples)</dd>
<dt>npreds</dt>
<dd>Number of predictors</dd>
<dt>ninters</dt>
<dd>Number of interaction terms, default 0. Up to npreds*(npreds-1)/2</dd></dl>

Arguments

Generate matrix of random observations — gen_preds

<dl>

<dt>nobs</dt>
<dd>Number of observations (samples)</dd>


<dt>npreds</dt>
<dd>Number of predictors</dd>


<dt>ninters</dt>
<dd>Number of interaction terms, default 0. Up to npreds*(npreds-1)/2</dd>

</dl>

gen_preds: Generate matrix of random observations

Description

Usage

Value

Arguments

Examples