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Physical Sciences and Mathematics Commons

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Operational Research

Theses/Dissertations

Monte Carlo method

Publication Year

Articles 1 - 3 of 3

Full-Text Articles in Physical Sciences and Mathematics

Uncertainty Quantification Of Multi-Component Isotope-Separation Cascade Model, Khoi D. Tran Mar 2010

Uncertainty Quantification Of Multi-Component Isotope-Separation Cascade Model, Khoi D. Tran

Theses and Dissertations

Monte Carlo uncertainty quantification (UQ) capability has been added to a code for modeling multi-component steady-state isotope-separation enrichment cascades to characterize the propagation of uncertainties in input data that define the cascade and the feed. Random samples of error for every computational input are drawn from its individual uncertainty distribution and added to the inputs, creating a set of enrichment cascade problems with perturbed inputs. The set of problems is solved using the verified code. The cascade outputs are then characterized using the empirical cumulative distribution. The uncertainty output data are analyzed to gain new insights into the behaviors of …


Minimum Distance Estimation For Time Series Analysis With Little Data, Hakan Tekin Mar 2001

Minimum Distance Estimation For Time Series Analysis With Little Data, Hakan Tekin

Theses and Dissertations

Minimum distance estimate is a statistical parameter estimate technique that selects model parameters that minimize a good-of-fit statistic. Minimum distance estimation has been demonstrated better standard approaches, including maximum likelihood estimators and least squares, in estimating statistical distribution parameters with very small data sets. This research applies minimum distance estimation to the task of making time series predictions with very few historical observations. In a Monte Carlo analysis, we test a variety of distance measures and report the results based on many different criteria. Our analysis tests the robustness of the approach by testing its ability to make predictions when …


A New Sequential Goodness Of Fit Test For The Three-Parameter Weibull Distribution With Known Shape Based On Skewness And Kurtosis, Jonathan C. Clough Mar 1998

A New Sequential Goodness Of Fit Test For The Three-Parameter Weibull Distribution With Known Shape Based On Skewness And Kurtosis, Jonathan C. Clough

Theses and Dissertations

The Weibull distribution finds wide applicability across a broad spectrum of disciplines and is very prevalent in reliability theory. Consequently, numerous statistical tests have been developed to determine whether sample data can be adequately modeled with this distribution. Unfortunately, the majority of these goodness-of-fit tests involve a substantial degree of computational complexity. The study presented here develops and evaluates a new sequential goodness-of-fit test for the three-parameter Weibull distribution with a known shape that delivers power comparable to popular procedures while dramatically reducing computational requirements. The new procedure consists of two distinct tests, using only the sample skewness and sample …