AverageN2-class: Regularization via L1 norm

In kkmann/otsd: Adaptive Optimal Two-Stage Designs in R

Regularization via L1 norm

Description

Implements the L1-norm of the design's stage-two sample size function. The average of the stage-two sample size without weighting with the data distribution is computed. This can be interpreted as integration over a unifrom prior on the continuation region.

Usage

AverageN2(label = NA_character_)

## S4 method for signature 'AverageN2,TwoStageDesign'
evaluate(s, design, optimization = FALSE, subdivisions = 10000L, ...)

Arguments

label	object label (string)
s	Score object
design	object
optimization	logical, if TRUE uses a relaxation to real parameters of the underlying design; used for smooth optimization.
subdivisions	number of subdivisions to use for adaptive integration (only affects non-optimization code)
...	further optional arguments

Value

an object of class AverageN2

See Also

N1 for penalizing n1 values

Examples

avn2 <- AverageN2()

evaluate(
   AverageN2(),
   TwoStageDesign(100, 0.5, 1.5, 60.0, 1.96, order = 5L)
) # 60

kkmann/otsd documentation built on Feb. 3, 2024, 4:50 p.m.