Nonparametric variance-based methods of assessing uncertainty importance
1997
Abstract This paper examines the feasibility and value of using nonparametric variance-based methods to supplement parametric regression methods for uncertainty analysis of computer models. It shows from theoretical considerations how the usual linear regression methods are a particular case within the general framework of variance-based methods. Examples of strengths and weaknesses of the methods are demonstrated analytically and numerically in an example. The paper shows that relaxation of linearity assumptions in nonparametric variance-based methods comes at the cost of additional computer runs.
Keywords:
- Correction
- Source
- Cite
- Save
- Machine Reading By IdeaReader
11
References
66
Citations
NaN
KQI