surv_optimize_allocation: Optimize sequencing allocation across strata

In survinger: Design-Adjusted Inference for Pathogen Lineage Surveillance

Optimize sequencing allocation across strata

Description

Given fixed total sequencing capacity, finds the optimal allocation across strata that minimizes a specified objective function.

Usage

## S3 method for class 'surv_allocation'
print(x, ...)

## S3 method for class 'surv_allocation'
as.data.frame(x, ...)

surv_optimize_allocation(
  design,
  objective = c("min_mse", "max_detection", "min_imbalance"),
  total_capacity,
  budget = NULL,
  min_per_stratum = 2L,
  target_lineage = NULL,
  target_prevalence = 0.01,
  cost_col = NULL
)

Arguments

x	Object to print.
...	Additional arguments (unused).
design	A surv_design object.
objective	Character. One of "min_mse", "max_detection", or "min_imbalance".
total_capacity	Integer. Total sequences available.
budget	Numeric or NULL. Optional budget constraint.
min_per_stratum	Integer. Minimum per stratum. Default 2.
target_lineage	Character. Required for "max_detection".
target_prevalence	Numeric. Assumed prevalence for detection. Default 0.01.
cost_col	Character or NULL. Column name for per-sequence cost.

Value

Invisibly returns the input object.

A surv_allocation object.

Examples

sim <- surv_simulate(n_regions = 4, n_weeks = 10, seed = 1)
d <- surv_design(sim$sequences, ~ region,
                 sim$population[c("region", "seq_rate")], sim$population)
a <- surv_optimize_allocation(d, "min_mse", total_capacity = 500)
print(a)

survinger documentation built on April 27, 2026, 9:10 a.m.