Dakota Reference Manual: allocation_control

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allocation_control

Sample allocation approach for multilevel expansions

## Specification

Alias: none

Argument(s): none

Child Keywords:

| Required/Optional | Description of Group | Dakota Keyword | Dakota Keyword Description
--- | --- | --- | --- | ---
| Required (Choose One) | Multilevel Sample Allocation Control (Group 1) | estimator_variance | Variance of mean estimator within multilevel polynomial chaos
rip_sampling | Sample allocation based on restricted isometry property (RIP) within multilevel polynomial chaos

## Description

Multilevel expansions, including regression-based polynomial chaos expansion (PCE) and function train (FT) expansions, require a sample allocation strategy. Three options are currently available:

- allocation based on assuming a convergence rate for the estimator variance (for regression PCE)
- restricted isometry property (RIP) sampling (for regression PCE via compressed sensing)
- rank sampling (for FT)

Default Behavior

Current defaults, when `allocation_control` is not specified, are estimator variance for PCE and rank sampling for FT.