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Full-Text Articles in Operational Research
Alternative Active Duty Military Retirement Plan, Amy L. Schmidt
Alternative Active Duty Military Retirement Plan, Amy L. Schmidt
Theses and Dissertations
No abstract provided.
Uncertainty Quantification Of Multi-Component Isotope-Separation Cascade Model, Khoi D. Tran
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 …
Multiple Model Adaptive Estimation For Time Series Analysis, Ibrahim Dulger
Multiple Model Adaptive Estimation For Time Series Analysis, Ibrahim Dulger
Theses and Dissertations
Multiple Model Adaptive Estimation (MMAE) is a Bayesian technique that applies a bank of Kalman filters to predict future observations. Each Kalman filter is based on a different set of parameters and hence produces different residuals. The likelihood of each Kalman filter's prediction is determined by a magnitude of the residuals. Since some researchers have obtained good forecasts using a single Kalman filter, we tested MMAE's ability to make time series predictions. Our Kalman filters have a dynamics model based on a Box-Jenkins Auto-Regressive Moving Average (ARMA) model and a measure model with additive noise. The time-series prediction is based …
Identification Of Critical Roles Of Program Managers And Contracting Officers, Daniel R. Shingledecker
Identification Of Critical Roles Of Program Managers And Contracting Officers, Daniel R. Shingledecker
Theses and Dissertations
The purpose of this research was to identify current disagreement among acquisition professionals in regards to their role and authority; and to identify benefits and risks associated with combining program management and contracting officer roles into a single position. The research questions were answered through a literature review and use of the Delphi technique. The literature review indicated that the DoD has been operating with multiple conflicting perceptions of authority among its key acquisition professionals. The literature also identified the need for complex organizations, such as DoD acquisition offices, to pair high levels of responsibility with equally high levels of …
Minimum Distance Estimation For Time Series Analysis With Little Data, Hakan Tekin
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 Parameter Value Based On Skewness And Q-Statis G.O.F. Test Statistics, Tibet Memis
Theses and Dissertations
Due to its flexibility, the Weibull distribution has very wide applicability in a lot of disciplines and is very prevalent in reliability theory. Thus, a lot of statistical tests that generally have a substantial degree of computational complexity have been developed to determine if the data at hand can be represented with this distribution. This research presents a new omnibus goodness-of-fit test (G.O.F.) that has less computational complexity than the existing tests for the three-parameter Weibull distribution using a sequential application of two individual tests, sample skewness and Q-Statistic. A Monte Carlo procedure has been employed to generate critical values …
A New Sequential Goodness Of Fit Test For The Three-Parameter Weibull Distribution With Known Shape Based On Skewness And Kurtosis, Jonathan C. Clough
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 …
A Monte Carlo Study Of The Raw And Normal Varimax Rotation Criterion In Factor Analysis, Willam M. Ibinson
A Monte Carlo Study Of The Raw And Normal Varimax Rotation Criterion In Factor Analysis, Willam M. Ibinson
Theses and Dissertations
Factor analysis is a multivariate statistical procedure for analyzing and reducing large data sets. Many factor analysis schemes and techniques are available that lead to strikingly different results from the same data. This research effort used a Monte Carlo approach to investigate the properties of two rotation methods for simple structure, Kaiser's raw and normal varimax criterion. Data sets were developed from a set of contrived experimental factor patterns by multiplying each factor pattern by its transpose to create a covariance matrix. Data sets of multivariate normal deviates were in turn generated from each covariance matrix via the Choleski algorithm. …
Identification Of The Initial Transient In Discrete-Event Simulation Output Using The Kalman Filter, Mark A. Gallagher
Identification Of The Initial Transient In Discrete-Event Simulation Output Using The Kalman Filter, Mark A. Gallagher
Theses and Dissertations
Data truncation is a commonly accepted method of dealing with initialization bias in discrete-event simulation. Algorithms for determining the appropriate initial-data truncation point for univariate and multivariate output are proposed. The techniques entail averaging across replications and estimating a steady-state output model in a state-space framework. Using the estimated model, Multiple Model Adaptive Estimation (MMAE), which uses Kalman filters with different parameter vectors, is applied. Based on the filters' residuals, the conditional probabilities of each filter's specific parameter vector being correct are determined. The MMAE parameter estimates are the probabilistic- weighted average of the filters' assumed parameter vectors. The estimated …
Preliminary Design Of A Model To Assess The Effect Of Space Surveillance Network (Ssn) Sensor Upgrades On Orbit Prediction Accuracies Relative To The U. S. Anti-Satellite (Asat) Mission, Daniel L. O'Brien
Theses and Dissertations
This study gives a basis for implementation of a model to assess the effect of proposed sensor upgrades to the Space Surveillance Network (SSN) to determine if more accurate orbital element set predictions by the Space Surveillance Center (SSC) can be obtained for U.S. anti-satellite (ASAT) targeting. Handoff orbital element set predictions to nearby ASAT facilities for single, low-orbit satellite passes over a single radar sensor are considered. Model development began with simulation of the selected satellites passing over the selected sensors producing baseline truth observations based on the NORAD simplified General Publications (SGP4) model. Sensor errors, in the form …
New Modified Anderson-Darling And Cramer-Von Mises Goodness-Of-Fit Tests For A Normal Distribution With Specified Parameters, Goksel Kahya
New Modified Anderson-Darling And Cramer-Von Mises Goodness-Of-Fit Tests For A Normal Distribution With Specified Parameters, Goksel Kahya
Theses and Dissertations
This thesis improves the powers of the Anderson-Darling and Cramer-von Mises goodness-of-fit tests using the mean rank and the median rank plotting positions. A Monte Carlo simulation of 5000 repetitions is used to generate the critical values from n =4 through n =80 for certain significance levels. An extensive power study is performed to compare the powers of the modified tests to the known tests for the uniform, the exponential, the double exponential, the lognormal, and the Weibull distributions. The power of the A-D tests modified by the median rank plotting and the mean rank plotting position are approximately 0.01% …
A Goodness-Of-Fit Test For A Family Of Two Parameter Weibulls With Known Shape Using Minimum Distance Estimation Of Parameters, John S. Crown
A Goodness-Of-Fit Test For A Family Of Two Parameter Weibulls With Known Shape Using Minimum Distance Estimation Of Parameters, John S. Crown
Theses and Dissertations
This research is to produce a modified Anderson-Darling goodness of fit test for the Weibull distribution when the location parameter is found by minimum distance estimation, the shape parameter is assumed known, and the MLE is used for the scale parameter. The critical values for the Anderson-Darling test are generated via Monte Carlo simulation when both the Anderson-Darling and Cramer-Von Mises distance statistics are minimized. These critical values are then used for a power study. The Monte Carlo simulation used 5000 repetitions for sample sizes of 5,8,12,15,16,20 and 25 with the Weibull shape parameter of . 5(.5)4.0. The power study …