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# CITATION file created with {cffr} R package
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cff-version: 1.2.0
message: 'To cite package "DNAmf" in publications use:'
type: software
license: GPL-3.0-only
title: 'DNAmf: Diffusion Non-Additive Model with Tunable Precision'
version: 0.1.1
doi: 10.32614/CRAN.package.DNAmf
abstract: Performs Diffusion Non-Additive (DNA) model proposed by Heo, Boutelet, and
  Sung (2025+) <https://doi.org/10.48550/arXiv.2506.08328> for multi-fidelity computer
  experiments with tuning parameters. The DNA model captures nonlinear dependencies
  across fidelity levels using Gaussian process priors and is particularly effective
  when simulations at different fidelity levels are nonlinearly correlated. The DNA
  model targets not only interpolation across given fidelity levels but also extrapolation
  to smaller tuning parameters including the exact solution corresponding to a zero-valued
  tuning parameter, leveraging a nonseparable covariance kernel structure that models
  interactions between the tuning parameter and input variables. Closed-form expressions
  for the predictive mean and variance enable efficient inference and uncertainty
  quantification. Hyperparameters in the model are estimated via maximum likelihood
  estimation.
authors:
- family-names: Heo
  given-names: Junoh
  email: heojunoh@msu.edu
- family-names: Boutelet
  given-names: Romain
  email: boutelet@msu.edu
- family-names: Sung
  given-names: Chih-Li
  email: sungchih@msu.edu
repository: https://heojunoh.r-universe.dev
commit: 2f47adba8c91aabc832ce6edeca5dbb4e9a4c707
date-released: '2026-01-29'
contact:
- family-names: Heo
  given-names: Junoh
  email: heojunoh@msu.edu