Typescript (photocopy). / Digitized by Kansas Correctional Industries

Typescript (photocopy). / Digitized by Kansas Correctional Industries

Typescript. / Digitized by Kansas Correctional Industries

vii, 188 leaves : ill. ; 30 cm. / Title page, contents and abstract only. The complete thesis in print form is available from the University Library. / Thesis (Ph.D.)--University of Adelaide, Dept. of Statistics, 1976

Measuring the source and magnitude of components of variation has important applications in industrial, environmental and biological studies. This thesis considers the problem of constructing confidence intervals for variance components in Gaussian mixed linear models. A number of methods based on the usual ANOVA mean squares have been proposed for constructing confidence intervals for variance components in balanced mixed models. Some authors have suggested extending balanced model procedures to unbalanced models by replacing the ANOVA mean squares with mean squares from an unweighted means ANOVA. However, the unweighted means ANOVA is only defined for a few specific mixed models. In Chapter 2 we define a generalization of the unweighted means ANOVA for the three variance component mixed linear model and illustrate how the mean squares from this ANOVA may be used to construct confidence intervals for variance components. Computer simulations indicate that the proposed procedure gives intervals that are generally consistent with the stated confidence level, except in the case of extremely unbalanced designs. A set of statistics that can be used as an alternative to the generalized unweighted mean squares is developed in Chapter 3. The intervals constructed with these statistics have better coverage probability and are often narrower than the intervals constructed with the generalized unweighted mean squares. / Graduation date: 1998

Thesis (Ph. D.)--University of Chicago, Dept. of Statistics, December 1997. / Includes bibliographical references. Also available on the Internet.

Abstract Under known signals environments, the problem of frequency estimation can be regarded as that of sinusoidal frequency estimation. Therefore, the frequency estimation of a single complex sinusoid signal in a white Gaussian noise channel is an important problem in the field of signal processing. Some of the applications include array signal processing, spectral estimation, carrier and clock synchronization for digital communications, Doppler rate estimation, and many others in radar and sonar systems. Frequency estimations based on the information of phase have threshold effects. While the length of the observation data is fixed, the performance of the estimator will be degraded and the variance will not achieve Cramer-Rao lower bound under the condition that signal-to-noise ratio (SNR) is below a certain threshold. In this thesis, two modified frequency estimation methods are proposed in additive white Gaussian noise channels. These two methods, estimating the frequency value by linearly combining the phase difference of correlated data, are basically extended from Kim¡¦s method. These estimators have lower complexity than optimal maximum likelihood estimator and attain as good performance at moderately high SNR¡¦s. These two methods, at high frequency values, yield a considerably lower variance threshold than Kay¡¦s method and Kim¡¦s method and remain unbiased.

"Submitted in partial fulfillment of the requirements for the degree of Master of Business Administration from the Naval Postgraduate School, December 2009." / Advisor(s): Jones, Lawrence R. ; Potvin, Lisa. "December 2009." "MBA Professional report"--Cover. Description based on title screen as viewed on January 28, 2010. Author(s) subject terms: Navy Working Capital Fund, Net Operating Result (NOR), Accumulative Operating Result (AOR), Naval Facilities Engineering Command (NAVFAC), Public Works Department (PWD), Utilities, Labor Hours, Expenses, Revenues, Break Even, Budget Forecasting, Business Model, Variance Analysis, Stabilized Rate, Financial Management, Operations, Policy, Workload, Industrial Business Information System (IBIS). Includes bibliographical references (p. 71-73). Also available in print.

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