- gsearch

Note: Javascript is disabled or is not supported by your browser. For this reason, some items on this page will be unavailable. For more information about this message, please visit this page: About CDC.gov

Advanced Search

- gsearch

Search Results

Narrow Results:

2018 1

Wheeler, Matthew W. 1

Journal Article 1

1 Results

Refine Results

All Collections

Refine Results:

All Collections

Bayesian Additive Adaptive Basis Tensor Product Models for Modeling High Dimensional Surfaces: An Application to High-throughput Toxicity Testing.

CITE Title : Bayesian Additive Adaptive Basis Tensor Product Models for Modeling High Dimensional Surfaces: An Application to High-throughput Toxicity Testing. Personal Author(s) : Wheeler, Matthew W. Published Date : August 06 2018;3-2019; Source : Biometrics. 75(1):193-201 URL : https://stacks.cdc.gov/view/cdc/75828 Wheeler, Matthew W. (2018). Bayesian Additive Adaptive Basis Tensor Product Models for Modeling High Dimensional Surfaces: An Application to High-throughput Toxicity Testing.. 75(1). Wheeler, Matthew W. "Bayesian Additive Adaptive Basis Tensor Product Models for Modeling High Dimensional Surfaces: An Application to High-throughput Toxicity Testing." 75, no. 1 (2018) Wheeler, Matthew W. "Bayesian Additive Adaptive Basis Tensor Product Models for Modeling High Dimensional Surfaces: An Application to High-throughput Toxicity Testing." vol. 75, no. 1, 2018 Export RIS Citation Information.

:

Wheeler, Matthew W.

August 06 2018 | Biometrics. 75(1):193-201

:

Many modern datasets are sampled with error from complex high-dimensional surfaces. Methods such as tensor product splines or Gaussian processes are e...

To see more results, try removing search filters or changing the search terms