# Confidence Intervals from Realizations of Simulated Nuclear Data

## Abstract

Various statistical techniques are discussed that can be used to assign a level of confidence in the prediction of models that depend on input data with known uncertainties and correlations. The particular techniques reviewed in this paper are: 1) random realizations of the input data using Monte-Carlo methods, 2) the construction of confidence intervals to assess the reliability of model predictions, and 3) resampling techniques to impose statistical constraints on the input data based on additional information. These techniques are illustrated with a calculation of the keff value, based on the ^{235}U(n, f) and ^{239}Pu (n, f) cross sections.

- Authors:

- Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States)

- Publication Date:

- Research Org.:
- Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States)

- Sponsoring Org.:
- USDOE

- OSTI Identifier:
- 1399727

- Report Number(s):
- LLNL-TR-739175

- DOE Contract Number:
- AC52-07NA27344

- Resource Type:
- Technical Report

- Country of Publication:
- United States

- Language:
- English

- Subject:
- 73 NUCLEAR PHYSICS AND RADIATION PHYSICS

### Citation Formats

```
Younes, W., Ratkiewicz, A., and Ressler, J. J..
```*Confidence Intervals from Realizations of Simulated Nuclear Data*. United States: N. p., 2017.
Web. doi:10.2172/1399727.

```
Younes, W., Ratkiewicz, A., & Ressler, J. J..
```*Confidence Intervals from Realizations of Simulated Nuclear Data*. United States. doi:10.2172/1399727.

```
Younes, W., Ratkiewicz, A., and Ressler, J. J.. Thu .
"Confidence Intervals from Realizations of Simulated Nuclear Data". United States.
doi:10.2172/1399727. https://www.osti.gov/servlets/purl/1399727.
```

```
@article{osti_1399727,
```

title = {Confidence Intervals from Realizations of Simulated Nuclear Data},

author = {Younes, W. and Ratkiewicz, A. and Ressler, J. J.},

abstractNote = {Various statistical techniques are discussed that can be used to assign a level of confidence in the prediction of models that depend on input data with known uncertainties and correlations. The particular techniques reviewed in this paper are: 1) random realizations of the input data using Monte-Carlo methods, 2) the construction of confidence intervals to assess the reliability of model predictions, and 3) resampling techniques to impose statistical constraints on the input data based on additional information. These techniques are illustrated with a calculation of the keff value, based on the 235U(n, f) and 239Pu (n, f) cross sections.},

doi = {10.2172/1399727},

journal = {},

number = ,

volume = ,

place = {United States},

year = {Thu Sep 28 00:00:00 EDT 2017},

month = {Thu Sep 28 00:00:00 EDT 2017}

}

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