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Advanced multivariate statistical analysis of directly and indirectly observed systemsShiells, Helen January 2017 (has links)
No description available.
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Maximum likelihood estimation of multivariate polyserial and polychoric correlation coefficients.January 1985 (has links)
by Wai-yin Poon. / Bibliography: leaves 62-64 / Thesis (M.Ph.)--Chinese University of Hong Kong, 1985
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Analysis of censored and polytomous data.January 1992 (has links)
by Wai-kuen Wong. / Thesis (M.Phil.)--Chinese University of Hong Kong, 1993. / Includes bibliographical references (leaves 57). / Chapter Chapter 1 : --- Introduction --- p.1 / Chapter Chapter 2 : --- Estimation of Correlation between Censored and Polytomous Variables --- p.5 / Chapter 2.1 : --- Model --- p.5 / Chapter 2.2 : --- Maximum Likelihood Estimation between a Censored and a Polytomous Variable --- p.7 / Chapter 2.3 : --- Simulation Study --- p.14 / Chapter 2.4 : --- Extension to Several Variables --- p.18 / Chapter Chapter 3 : --- An application -- Correlation Structure Analysis --- p.33 / Chapter 3.1 : --- Model --- p.33 / Chapter 3.2 : --- Two-stage Estimation Procedure --- p.35 / Chapter 3.3 : --- Optimization Procedure --- p.37 / Chapter Chapter 4 : --- Conclusion --- p.40 / Tables --- p.42 / References --- p.57
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A stepping procedure based on a local influence measure to identify multiple multivariate outliers.January 2000 (has links)
Tse Suk Yan. / Thesis (M.Phil.)--Chinese University of Hong Kong, 2000. / Includes bibliographical references (leaves 114-115). / Abstracts in English and Chinese. / Chapter Chapter 1 --- Introduction --- p.1 / Chapter Chapter 2 --- The Elements of the New Procedure --- p.6 / Chapter 2.1 --- The Stepping Algorithm --- p.6 / Chapter 2.2 --- Outlier Measure and Benchmark --- p.17 / Chapter Chapter 3 --- The New Procedure --- p.21 / Chapter 3.1 --- Procedure --- p.22 / Chapter 3.2 --- Examples --- p.31 / Chapter 3.3 --- Simulation Study --- p.41 / Chapter 3.3.1 --- Terms and Factors --- p.41 / Chapter 3.3.2 --- Procedure --- p.45 / Chapter 3.3.3 --- Results --- p.47 / Chapter Chapter 4 --- Robust Version of the New Procedure --- p.51 / Chapter 4.1 --- Procedure --- p.52 / Chapter 4.2 --- Examples --- p.58 / Chapter 4.3 --- Simulation Study --- p.62 / Chapter 4.3.1 --- Procedure --- p.63 / Chapter 4.3.2 --- Results --- p.65 / Chapter Chapter 5 --- The New Procedure with Random Initial Subset --- p.68 / Chapter 5.1 --- The Elements --- p.69 / Chapter 5.2 --- Procedure --- p.71 / Chapter 5.3 --- Examples --- p.77 / Chapter Chapter 6 --- Discussion --- p.91 / Chapter Chapter 7 --- Conclusion --- p.102 / Appendix --- p.105 / References --- p.114
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On Measuring agreement for categorical data.January 2002 (has links)
Tang Pik-Ha. / Thesis (M.Phil.)--Chinese University of Hong Kong, 2002. / Includes bibliographical references (leaves 51-54). / Abstracts in English and Chinese. / Chapter 1 --- Introduction --- p.1 / Chapter 1.1 --- Agreement analysis --- p.2 / Chapter 1.2 --- Outline of the thesis --- p.6 / Chapter 2 --- Review --- p.8 / Chapter 2.1 --- Chance-corrected measures --- p.8 / Chapter 2.2 --- Statistical Modelling Approach --- p.15 / Chapter 3 --- Model-based kappa --- p.17 / Chapter 3.1 --- An agreement model with kappa as parameter --- p.17 / Chapter 3.2 --- Parameter Estimation --- p.21 / Chapter 3.3 --- Asymptotic variance-covariance matrix --- p.25 / Chapter 3.3.1 --- Fisher Information --- p.25 / Chapter 3.3.2 --- Computational detail --- p.27 / Chapter 3.4 --- Illustrative Example --- p.30 / Chapter 4 --- Simulation Study --- p.33 / Chapter 4.1 --- Design --- p.33 / Chapter 4.2 --- Results --- p.37 / Chapter 4.3 --- Discussion --- p.40 / Chapter 5 --- Conclusion --- p.42 / Tables --- p.44 / Figures --- p.49 / Bibliography --- p.51
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Detection of location shift outliers with ordinal categorical variables.January 2000 (has links)
Ng Sau-chun. / Thesis (M.Phil.)--Chinese University of Hong Kong, 2000. / Includes bibliographical references (leaves 53-54). / Abstracts in English and Chinese. / Chapter Chapter 1 --- Introduction --- p.1 / Chapter Chapter 2 --- The Local Influence Approach --- p.5 / Chapter 2.1 --- Review of the local influence approach / Chapter 2.2 --- Recent modification of the approach / Chapter Chapter 3 --- Detection of Outliers --- p.9 / Chapter 3.1 --- A measure to identify multivariate outliers / Chapter 3.2 --- Identification of outliers in the presence of ordinal categorical variables / Chapter 3.3 --- Examples / Chapter 3.3.1 --- Example --- p.1 / Chapter 3.3.2 --- Example --- p.2 / Chapter 3.3.3 --- Example --- p.3 / Chapter 3.4 --- Behavior of the measure under different patterns / Chapter 3.5 --- Outlying observations and their influence on the estimate of polychoric correlation / Chapter 3.5.1 --- Example / Chapter 3.5.2 --- The simulation studies / Chapter Chapter 4 --- Influential Cells in A Contingency Table --- p.28 / Chapter 4.1 --- The model and its estimation / Chapter 4.2 --- The perturbation of observed frequency / Chapter 4.3 --- Normal curvatures as an influence measures / Chapter 4.4 --- Some numerical results / Chapter 4.4.1 --- 2-Dimensional data examples / Chapter 4.4.2 --- Examples on m-Dimensional data / Chapter Chapter 5 --- Discussion --- p.51 / Bibliography / Appendix
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Local influence and multivariate outliers. / CUHK electronic theses & dissertations collectionJanuary 1999 (has links)
by Terry Shing-fong Lew. / "July 1999." / Thesis (Ph.D.)--Chinese University of Hong Kong, 1999. / Includes bibliographical references (p. 52-54). / Electronic reproduction. Hong Kong : Chinese University of Hong Kong, [2012] System requirements: Adobe Acrobat Reader. Available via World Wide Web. / Mode of access: World Wide Web. / Abstracts in English and Chinese.
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Influential observations in the analysis of additive ipsative data.January 2003 (has links)
Wong Wai-Wan. / Thesis (M.Phil.)--Chinese University of Hong Kong, 2003. / Includes bibliographical references (leaves 45-46). / Abstracts in English and Chinese. / Abstract --- p.i / Acknowledgement --- p.iii / Chapter 1 --- Introduction --- p.1 / Chapter 1.1 --- Ipsative Data --- p.1 / Chapter 1.2 --- Transformation --- p.2 / Chapter 1.3 --- Influence Analysis --- p.3 / Chapter 2 --- Ipsative Data --- p.5 / Chapter 2.1 --- Additive Ipsative Data (AID) and Multiplicative Ipsative Data (MID) --- p.6 / Chapter 2.1.1 --- Additive Ipsative Data (AID) --- p.6 / Chapter 2.1.2 --- Multiplicative Ipsative Data (MID) --- p.7 / Chapter 2.2 --- Partially Additive Ipsative Data (PAID) --- p.7 / Chapter 2.2.1 --- Vector of PAID --- p.8 / Chapter 2.2.2 --- Special Cases of PAID --- p.9 / Chapter 3 --- Transformation --- p.10 / Chapter 3.1 --- Distribution of AID --- p.10 / Chapter 3.2 --- Transformation --- p.11 / Chapter 3.3 --- Relationship between Parameters of AID and the Transformed Vector --- p.13 / Chapter 4 --- Influence Analysis of Ipsative Data --- p.14 / Chapter 4.1 --- The Postulated Model --- p.15 / Chapter 4.2 --- Perturbation --- p.16 / Chapter 4.3 --- Likelihood Displacement --- p.17 / Chapter 4.4 --- Normal Curvature --- p.18 / Chapter 4.5 --- Computation of the Normal Curvature --- p.20 / Chapter 4.6 --- Diagnostic Measures --- p.21 / Chapter 4.6.1 --- Observations influencing the estimates of μ and Σ --- p.22 / Chapter 4.6.2 --- Observations influencing the estimate of μ or Σ --- p.22 / Chapter 4.7 --- Examples --- p.24 / Chapter 4.7.1 --- Example 1: Foraminiferal Compositions Data Set (AID) . --- p.24 / Chapter 4.7.2 --- Example 2: Compositions of Sediments Data Set (PAID) . --- p.25 / Chapter 5 --- Discussion --- p.31 / Chapter A --- Proof of Propositions --- p.34 / Chapter A.1 --- Proof of Proposition 3 --- p.34 / Chapter A.2 --- Proof of Proposition 4 --- p.35 / Chapter B --- "Analytical Expressions of (Lθ*)-1, Δ* and Lc" --- p.37 / Chapter B.1 --- Analytical Expression of (Lθ*)-1 --- p.37 / Chapter B.2 --- Analytical Expression of Δ* --- p.38 / Chapter B.3 --- Analytical Expression of Lc --- p.38 / Chapter C --- Calculation of aθ- --- p.39 / Chapter D --- Matlab Commands of Example 1 --- p.42 / Bibliography --- p.44
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Analysis of multivariate ordinal categorical variables with misclassified data.January 2007 (has links)
Zhang, Xinmiao. / Thesis (M.Phil.)--Chinese University of Hong Kong, 2007. / Includes bibliographical references (leaves 48). / Abstracts in English and Chinese. / Acknowledgement --- p.i / Abstract --- p.ii / Chapter 1 --- Introduction --- p.1 / Chapter 2 --- Estimation with Known Misclassification Probabilities --- p.3 / Chapter 2.1 --- Model --- p.3 / Chapter 2.2 --- Maximum Likelihood Estimation --- p.5 / Chapter 2.3 --- Statistical Property --- p.6 / Chapter 2.4 --- Mx Estimation --- p.7 / Chapter 2.5 --- Partition Maximum Likelihood (PML) Estimation --- p.9 / Chapter 2.6 --- Starting Value --- p.10 / Chapter 2.7 --- Examples --- p.11 / Chapter 2.7.1 --- Example 1 --- p.11 / Chapter 2.7.2 --- Example 2 --- p.12 / Chapter 2.7.3 --- Example 3 --- p.13 / Chapter 3 --- Estimation by Double Sampling --- p.15 / Chapter 3.1 --- Model and Analysis --- p.16 / Chapter 3.2 --- Statistical Property --- p.17 / Chapter 3.3 --- Mx Estimation and PML Estimation --- p.18 / Chapter 3.4 --- Starting Value --- p.19 / Chapter 3.5 --- Examples --- p.19 / Chapter 3.5.1 --- Example 4 --- p.19 / Chapter 4 --- Simulation --- p.20 / Chapter 4.1 --- Simulation with Known Misclassification Probability --- p.20 / Chapter 4.2 --- Simulation with Double Sampling --- p.22 / Chapter 5 --- Conclusion --- p.24 / Appendix and Tables --- p.26 / References --- p.48
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Likelihood analysis of the multivariate ordinal probit model for repeated and spatial ordered categorical responses /Li, Yonghai. January 1900 (has links)
Thesis (Ph. D.)--Oregon State University, 2007. / Printout. Includes bibliographical references (leaves 61-65). Also available on the World Wide Web.
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