Thesis (M. Phil.)--University of Hong Kong, 2002. / Includes bibliographical references (leaves 82-91).

Copulas have been known in the statistical literature for many years, and have become useful tools in modeling dependence structure of multivariate random variables, overcoming some of the drawbacks of the commonly-used correlation measures. Goodness-of-fit tests for copulas play a very important role in evaluating the suitability of a potential input copula model. In recent years, many approaches have been proposed for constructing goodness-of-fit tests for copula families. Among them, the so-called “blanket tests" do not require an arbitrary data categorization or any strategic choice of weight function, smoothing parameter, kernel, and so on. As preliminaries, some background and related results of copulas are firstly presented. Three goodness-of-fit test statistics belonging to the blanket test classification are then introduced. Since the asymptotic distributions of the test statistics are very complicated, parametric bootstrap procedures are employed to approximate critical values of the test statistics under the null hypotheses. To assess the performance of the three test statistics in the low dependence cases, simulation studies are carried out for three bivariate copula families, namely the Gumbel-Hougaard copula family, the Ali-Mikhail-Haq copula family, and the Farlie-Gumbel-Morgenstern copula family. Specifically the effect of low dependence on the empirical sizes and powers of the three blanket tests under various combinations of null and alternative copula families are examined. Furthermore, to check the performance of the three tests for higher dimensional copulas, the simulation studies are extended to some three-dimensional copulas. Finally the three goodness-of-fit tests are applied to two real data sets. / published_or_final_version / Statistics and Actuarial Science / Master / Master of Philosophy

published_or_final_version / Statistics and Actuarial Science / Master / Master of Philosophy

Three dimensional laser scanning, also known as Light Detection and Ranging (LiDAR) has quickly been expanding in its applications in the field of geological engineering due to its ability to rapidly acquire highly accurate three dimensional positional data. Recently is has been shown that LiDAR scanning can be easily integrated into an excavation sequence in an underground environment for the purpose of collecting rockmass and discontinuity information. As scans are often taken multiple times of the same environment, the next logical application of LiDAR scanning is for monitoring for change and deformation. Traditionally, deformation and change in an underground environment is measured using a series of five or more permanent control points installed around the profile of an excavation. Using LiDAR for profile analysis provides many benefits as compared to traditional monitoring techniques. Due to the high density of the point cloud data, the change in profile is able to be fully characterized, and areas of anomalous movement can easily be separated from overall closure trends. Furthermore, monitoring with LiDAR does not require the permanent installation of control points, therefore monitoring can be completed more quickly after excavation, and scanning is non-invasive therefore no damage is done during the installation of temporary control points. The main drawback of using LiDAR scanning for deformation monitoring is that the raw point accuracy is generally the same magnitude as the smallest level of deformations that need to be measured. To overcome this, statistical techniques for profile analysis must be developed. This thesis outlines the development one such method, called the Elliptical Fit Analysis (EFA) and LiDAR Profile Analysis (EFA) for tunnel and shaft convergence analysis. Testing of the EFA and LPA has proved the robustness of this technique in its ability to deal with accuracy and precision issues associated with LiDAR scanning. / Thesis (Master, Geological Sciences & Geological Engineering) -- Queen's University, 2012-05-15 13:24:28.398

After defining the structure to a signal detection scheme, this dissertation describes and addresses some of the unresolved issues associated with its use when the interference encountered is impulsive. The alpha-stable (alpha-S) family of distributions is used as a model of this interference due to its physical interpretation and its general form. Despite its attractive features, difficulties arise in using this distribution due to, amongst other things, the lack of a general closed form expression for its probability density function. Relevant to the detection scheme used, this affects parameter estimation, signal detector design and goodness-of-fit tests. Significant contributions are made in the latter through the introduction of characteristic function based test that uses the parametric bootstrap. A modification of this test is then made to define a test of the level of impulsive behaviour - again the parametric bootstrap is employed to maintain levels of significance for this and another test based on testing the alpha-S parameter values. The performance of these tests is examined under simulated and two sources of real, impulsive data, namely human heart rate variability and fluctuations in stock prices. Once the appropriateness of the model assumption has been verified, the final, signal detection process may take place. Detectors based on the locally optimum criterion and approximations to it are described and compared to their rank-based counterparts. Results are presented that suggest compelling arguments based on performance and computational complexity for the consideration of rank-based techniques.Keywords: Impulsive behaviour, alpha-stable distribution, stable laws, Gaussianity testing, parameter estimation, goodness-of-fit, parametric bootstrap, signal detection, locally optimum detectors, rank-based detectors.

Assignment (MComm)--University of Stellenbosch, 2008. / Bibliography. Also available via the Internet.

Thesis (M.S.)--West Virginia University, 2006. / Title from document title page. Document formatted into pages; contains viii, 45 p. : ill. (some col.). Includes abstract. Includes bibliographical references (p. 44-45).

Thesis (Ph.D.)--University of Toledo, 2005. / Typescript. "A dissertation [submitted] as partial fulfillment of the requirements of the Doctor of Philosophy degree in Mathematics." Bibliography: leaves 100-105.

Thesis (M. Phil.)--University of Hong Kong, 2005. / Title proper from title frame. Also available in printed format.

abstract: Sustaining a fall can be hazardous for those with low bone mass. Interventions exist to reduce fall-risk, but may not retain long-term interest. "Exergaming" has become popular in older adults as a therapy, but no research has been done on its preventative ability in non-clinical populations. The purpose was to determine the impact of 12-weeks of interactive play with the Wii Fit® on balance, muscular fitness, and bone health in peri- menopausal women. METHODS: 24 peri-menopausal-women were randomized into study groups. Balance was assessed using the Berg/FICSIT-4 and a force plate. Muscular strength was measured using the isokinetic dynamometer at 60°/180°/240°/sec and endurance was assessed using 50 repetitions at 240°/sec. Bone health was tracked using dual-energy x-ray absorptiometry (DXA) for the hip/lumbar spine and qualitative ultrasound (QUS) of the heel. Serum osteocalcin was assessed by enzyme immunoassay. Physical activity was quantified using the Women's Health Initiative Physical Activity Questionnaire and dietary patterns were measured using the Nurses' Health Food Frequency Questionnaire. All measures were repeated at weeks 6 and 12, except for the DXA, which was completed pre-post. RESULTS: There were no significant differences in diet and PA between groups. Wii Fit® training did not improve scores on the Berg/FICSIT-4, but improved center of pressure on the force plate for Tandem Step, Eyes Closed (p-values: 0.001-0.051). There were no significant improvements for muscular fitness at any of the angular velocities. DXA BMD of the left femoral neck improved in the intervention group (+1.15%) and decreased in the control (-1.13%), but no other sites had significant changes. Osteocalcin indicated no differences in bone turnover between groups at baseline, but the intervention group showed increased bone turnover between weeks 6 and 12. CONCLUSIONS: Findings indicate that WiiFit® training may improve balance by preserving center of pressure. QUS, DXA and osteocalcin data confirm that those in the intervention group were experiencing more bone turnover and bone formation than the control group. In summary, twelve weeks of strength /balance training with the Wii Fit® shows promise as a preventative intervention to reduce fall and fracture risk in non-clinical middle aged women who are at risk. / Dissertation/Thesis / Ph.D. Exercise and Wellness 2014