Global ETD Search
Search theses and dissertations gathered from participating repositories worldwide. Every result links back to the library that holds it. No account is needed.
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Showing 1 to 20 of 260 for “"Principal components analysis."”.
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Hedging Interest-Rate Options Using Principal Components Analysis
… securities. As an alternative, we consider using principal components analysis (PCA) to condense most of the variability in the market rates into a much smaller number of risk factors, called the principal components. One can then construct a hedging portfolio so as to make the portfolio immune to …
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Longitudinal principal components analysis for binary and continuous data
… part of this thesis, we propose a longitudinal principal component analysis (LPCA) using a random-effects eigen-decomposition, where the eigen-decomposition utilizes longitudinal information over time to model time-varying eigenvalues and eigenvectors of the corresponding covariance matrices. …
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Inter-finger coordination in robot hands via mechanical implementation of principal components analysis
… collected with a dataglove, and analyzed using principal components analysis to determine the postural synergies. The synergies are then mechanically hardwired into the driving mechanism, resulting in a concept dubbed eigenpostures.
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P300-Based BCI Performance Prediction through Examination of Paradigm Manipulations and Principal Components Analysis.
… and BCI performance. Both waveform and component analysis have revealed several task-dependent aspects of brain activity that show significant correlation with the user's performance. These components may provide a fast and reliable metric to indicate whether the BCI system will work for a given …
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Unconfined compressive strength prediction using drilling parameters and analyzing feature importance through principal components analysis
… consists of a data processing method called Principal Component Analysis (PCA) to indicate the importance of each parameter by quantifying their variance contribution. Random Forest machine learning algorithm is utilized to build a regression model to estimate UCS. The regression model …
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Atmospheric temperature profile estimation from infrared and microwave spectral radiance observations using principal components analysis
Thesis (M.S.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 1995.
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POSITIVE PEER CULTURE PROBLEM LABELS AND JUVENILE DELINQUENCY: AN EXPLORATORY PRINCIPAL COMPONENTS ANALYSIS AND ORDINARY LEAST SQUARES REGRESSION ANALYSIS OF LOW SELF-IMAGE, INCONSIDERATE OF OTHERS, AND INCONSIDERATE OF SELF
… values and attitudes. The confirmatory factor analysis findings show that the PPC problem labels can be transformed into scaled variables those outlined in the literature. Findings based on ordinary least squares regression models suggest that the PPC problem labels are not significant …
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POSITIVE PEER CULTURE PROBLEM LABELS AND JUVENILE DELINQUENCY: AN EXPLORATORY PRINCIPAL COMPONENTS ANALYSIS AND ORDINARY LEAST SQUARES REGRESSION ANALYSIS OF LOW SELF-IMAGE, INCONSIDERATE OF OTHERS, AND INCONSIDERATE OF SELF
… values and attitudes. The confirmatory factor analysis findings show that the PPC problem labels can be transformed into scaled variables those outlined in the literature. Findings based on ordinary least squares regression models suggest that the PPC problem labels are not significant …
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Contributions to Functional Data Analysis
… common in biomedical applications and their analysis is currently an active area of research in statistics. This dissertation makes two contributions to functional data analysis. The first contribution is development of a methodology for modeling and analysis of functional data arising in …
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Seismic Response of Low -Rise Shear Wall Structures With Flexible Diaphragms
… The proposed methods are based on the principal modes obtained from a principal components analysis (PCA) of computed inelastic dynamic responses. The method can consider variations in the design response spectrum and gives reasonably good estimates for use for preliminary design of the …
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Methods for Evaluating Aquifer-System Parameters from a Cumulative Compaction Record
… water-level data deconvolved into temporal components. Over a decade of compaction and water-level data were collected from an extensometer and multi-level piezometer at the Lorenzi site in Las Vegas Valley and when graphed yearly, seasonal, and daily signals are observed. Each temporal …
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Focus on form from the inside : the significance of grammatical sensitivity for L2 learning in communicative ESL classrooms
… the course of one academic year. Three types of analysis were performed on the data: a principal components analysis, a cluster analysis, and an interlanguage analysis. The results of these analyses indicate that grammatical sensitivity is associated with success in L2 learning to some degree …
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An exploration of selected variables associated with the instructional leadership of secondary school principals
… instructional leadership of secondary school principals in Virginia. Four variables--(a) clarity of instructional goals, (b) performance efficacy, (c) autonomy, and (d) instructional expertise--were used to predict the instructional leadership of the principals. Data for the predictor …
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An empirical analysis of a systems model of family resource management/
… into four categories. Using Varimax rotated principal components analysis, eight factors were extracted from 34 items assessing managerial behavior. The resulting dimension scale scores represented throughput in the model. Output, by definition. encompasses individual satisfaction. Using …
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Inferences on high-dimensional data
… than the number of observations. Two methods, principal components analysis (PCA) and partial least squares (PLS), are used for regression and classification. We show that the null distribution of the PLS ""f-test"" statistic, which is obtained from one factor PLS regression, depends heavily on …
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Neural networks and neurophysiological signals
… classification results on novel waveforms. Also, principal components analysis is a powerful preprocessing technique which allows for a significant reduction in processing efficiency, while maintaining performance standards. This system is implementable as a real-time quality control process for …
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A repertory grid study of anorexia nervosa in females
… using Slater's (1972) "INGRID 72 PROGRAM : the principal components analysis for the repertory grid", and comprehensive data is tabulated and discussed with reference to each subject's psychological grid space. A comparison of the efficacy of the two repertory grid measures is discussed and …
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The geography of HIV/AIDS and an assessment of risk factor perspectives in Nigeria: the case of Benin City and Makurdi
… (i.e. geographic information science or GIS and principal components analysis) and qualitative analytical techniques (questionnaires and focus group discussions). Both the principal components analysis and the focus group discussions assisted in unraveling the major HIV/AIDS risk factors that …
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Intrapersonal Grief as a Clinical Entity Distinct from Depression: Does It Exist Among a Medically Ill Parkinson's Disease Population?
… and their distinction from one another, using principal components analysis among their respective symptom items, and (3) examine the unique and added contribution of grief on concurrent and prospective emotional and physical health outcomes (i.e. self-esteem, intrusive thoughts and avoidant …
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The development and validation of a disease-specific instrument to measure quality of life in systemic lupus erythematosus
… (63 items) was completed by 322 patients. Principal components analysis and Cronbach alpha coefficients highlighted eight domains. The LupusQoL was further revised (42 items) based on factor analysis, clinical decision and patient feedback. Principal components analysis was performed on the …
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