Theta-regularized Kriging penalizes the theta hyperparameter in Gaussian stochastic processes using Lasso, Ridge, or Elastic-net, yielding higher accuracy and stability than prior penalized Kriging variants on numerical tests and engineering cases.
Park, Lasso Kriging for efficiently selecting a global trend model, Struct
1 Pith paper cite this work. Polarity classification is still indexing.
1
Pith paper citing it
fields
stat.CO 1years
2026 1verdicts
UNVERDICTED 1representative citing papers
citing papers explorer
-
Theta-regularized Kriging: Modelling and Algorithms
Theta-regularized Kriging penalizes the theta hyperparameter in Gaussian stochastic processes using Lasso, Ridge, or Elastic-net, yielding higher accuracy and stability than prior penalized Kriging variants on numerical tests and engineering cases.