Shum Chun-Yin. / Thesis (M.Phil.)--Chinese University of Hong Kong, 2003. / Includes bibliographical references (leaves 63-64). / Abstracts in English and Chinese. / Abstract --- p.i / Acknowledgement --- p.iv / Chapter 1 --- Introduction --- p.1 / Chapter 2 --- Ordinal Contingency Table --- p.5 / Chapter 2.1 --- Model --- p.5 / Chapter 2.2 --- The Maximum Likelihood Method --- p.7 / Chapter 2.3 --- Limitation of the Maximum Likelihood Estimation in Large Sample --- p.8 / Chapter 2.4 --- The Partition Maximum Likelihood Approach --- p.9 / Chapter 3 --- Modification of the Partition Maximum Likelihood Approach --- p.12 / Chapter 3.1 --- The Modified Partition Maximum Likelihood Approach --- p.12 / Chapter 3.2 --- Mx Implementation --- p.14 / Chapter 3.2.1 --- Maximum Likelihood Procedure --- p.14 / Chapter 3.2.2 --- Modified PML Procedure --- p.15 / Chapter 3.3 --- Examples --- p.16 / Chapter 3.3.1 --- Example 1 : Attitudes of Morality and Equality --- p.16 / Chapter 3.3.2 --- Example 2 : A Panel Model for Political Efficacy --- p.17 / Chapter 3.4 --- Limitation of the Modified PML Approach --- p.19 / Chapter 3.5 --- Simulation Study for the Modified PML Approach --- p.20 / Chapter 4 --- Generalization to Structural Equation Model --- p.22 / Chapter 4.1 --- Model --- p.23 / Chapter 4.2 --- Procedure --- p.24 / Chapter 4.3 --- Examples --- p.26 / Chapter 4.3.1 --- Example 1 : Attitudes of Morality and Equality --- p.26 / Chapter 4.3.2 --- Example 2 : A Panel Model for Political Efficacy --- p.28 / Chapter 5 --- Generalization to Stochastic Constraints on Thresholds --- p.31 / Chapter 5.1 --- Model --- p.32 / Chapter 5.2 --- Bayesian Analysis of the Model --- p.33 / Chapter 5.3 --- Examples --- p.35 / Chapter 5.3.1 --- Example 1 : Attitudes of Morality and Equality --- p.35 / Chapter 5.3.2 --- Example 2 : A Panel Model for Political Efficacy --- p.36 / Chapter 6 --- Conclusion and Discussion --- p.38 / Chapter A --- Mx Script of the ML Estimation - for Example 1 --- p.40 / Chapter B --- Mx Script of the Modified PML Estimation - for Example 1 --- p.42 / Chapter C --- Mx Script of the Modified PML Estimation - for Example 2 --- p.45 / Bibliography --- p.63

Tam, Hiu Wah. / Thesis (M.Phil.)--Chinese University of Hong Kong, 2007. / Includes bibliographical references (leaves 41). / Abstracts in English and Chinese. / Chapter 1 --- Introduction --- p.1 / Chapter 2 --- Estimation with Known Misclassification Probabilities --- p.5 / Chapter 2.1 --- Model --- p.5 / Chapter 2.2 --- Maximum Likelihood Estimation --- p.7 / Chapter 2.3 --- Examples --- p.9 / Chapter 2.3.1 --- Example 1: A Real data set analysis --- p.9 / Chapter 2.3.2 --- Example 2: An Artificial Data for 3x3 Table --- p.11 / Chapter 3 --- Estimation by Double Sampling --- p.12 / Chapter 3.1 --- Estimation --- p.13 / Chapter 3.2 --- Example --- p.14 / Chapter 3.2.1 --- Example 3: An Artificial Data Example for 3x3 Table --- p.14 / Chapter 4 --- Simulation --- p.15 / Chapter 5 --- Conclusion --- p.17 / Table --- p.19 / Appendix --- p.27 / Bibliography --- p.41

Αντικείμενο της παρούσας διπλωματικής εργασίας είναι η ανάλυση του δείγματος των ερωτηματολογίων ως εργαλείο μελέτης των παραγόντων που σχετίζονται μεταξύ τους και επηρεάζουν σημαντικά στην ίδρυση μιας μικρομεσαίας επιχείρησης. Το είδος και η μορφή των ερωτήσεων, μας οδηγούν αρχικά να διερευνήσουμε τις μεταβλητές μας μέσω πινάκων συνάφειας, καθώς οι εμπλεκόμενες μεταβλητές είναι κυρίως κατηγορικές. / The topic of the present thesis is, at a first stage, the evaluation of those questionnaires on the whole, as a tool of the study of the factors that may affect the establishment of a small and medium-sized enterprise. The type and the form of the questions initially lead us to introduce mainly categorical variables (nominal or ordinal) and to cross-classify them, forming thus contingency tables.

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Neste trabalho foi realizada uma revisão bibliográfica acerca das metodologias encontradas na literatura de como são aplicados os métodos para o uso analítico de dados provenientes de pesquisas que envolvem esquemas amostrais complexos. Objetivou-se mostrar e discutir alguns estudos que avaliam o impacto de ignorar o plano amostral na análise dos dados. Foi feito também um levantamento de artigos com o objetivo de fazer um estudo de trabalhos publicados em jornais, revistas ou periódicos, cujos assuntos abordados tratam da incorporação da estrutura complexa da amostra na análise. Essa revisão evidenciou que os métodos clássicos de análise, ou seja, aqueles que supõem que os dados provém de uma amostragem aleatória simples, podem levar a resultados incorretos produzindo conclusões errôneas ou equivocadas quando os dados provém de esquemas amostrais complexos. / This work was carried out a literature review about the methodologies found in the literature of how the methods for data analytical use from research involving complex sampling schemes are applied. It was aimed to show and discuss some studies that assess the impact of ignoring the sampling scheme in the data analysis. It was also made a survey of articles in order to make a study of works published in newspapers, magazines or periodicals, which addressed issues dealing with the incorporation of the complex structure of the sample in the analysis. This review shown that the classical methods of analysis, i.e. those who assume that the data comes from a simple random sampling can lead to incorrect results producing quite erroneous and misleading conclusions when the data come from complex sample schemes.

Neste trabalho foi realizada uma revisão bibliográfica acerca das metodologias encontradas na literatura de como são aplicados os métodos para o uso analítico de dados provenientes de pesquisas que envolvem esquemas amostrais complexos. Objetivou-se mostrar e discutir alguns estudos que avaliam o impacto de ignorar o plano amostral na análise dos dados. Foi feito também um levantamento de artigos com o objetivo de fazer um estudo de trabalhos publicados em jornais, revistas ou periódicos, cujos assuntos abordados tratam da incorporação da estrutura complexa da amostra na análise. Essa revisão evidenciou que os métodos clássicos de análise, ou seja, aqueles que supõem que os dados provém de uma amostragem aleatória simples, podem levar a resultados incorretos produzindo conclusões errôneas ou equivocadas quando os dados provém de esquemas amostrais complexos. / This work was carried out a literature review about the methodologies found in the literature of how the methods for data analytical use from research involving complex sampling schemes are applied. It was aimed to show and discuss some studies that assess the impact of ignoring the sampling scheme in the data analysis. It was also made a survey of articles in order to make a study of works published in newspapers, magazines or periodicals, which addressed issues dealing with the incorporation of the complex structure of the sample in the analysis. This review shown that the classical methods of analysis, i.e. those who assume that the data comes from a simple random sampling can lead to incorrect results producing quite erroneous and misleading conclusions when the data come from complex sample schemes.

Data mining techniques, such as clustering, have become a mainstay in many applications such as bioinformatics, geographic information systems, and marketing. Over the last decade, due to new demands posed by these applications, clustering techniques have been significantly adapted and extended. One such extension is the idea of finding clusters in a dataset that preserve information about some auxiliary variable. These approaches tend to guide the clustering algorithms that are traditionally unsupervised learning techniques with the background knowledge of the auxiliary variable. The auxiliary information could be some prior class label attached to the data samples or it could be the relations between data samples across different datasets. In this dissertation, we consider the latter problem of simultaneously clustering several vector valued datasets by taking into account the relationships between the data samples. We formulate objective functions that can be used to find clusters that are local in each individual dataset and at the same time maximally similar or dissimilar with respect to clusters across datasets. We introduce diverse applications of these clustering algorithms: (1) time series segmentation (2) reconstructing temporal models from time series segmentations (3) simultaneously clustering several datasets according to database schemas using a multi-criteria optimization and (4) clustering datasets with many-many relationships between data samples. For each of the above, we demonstrate applications, including modeling the yeast cell cycle and the yeast metabolic cycle, understanding the temporal relationships between yeast biological processes, and cross-genomic studies involving multiple organisms and multiple stresses. The key contribution is to structure the design of complex clustering algorithms over a database schema in terms of clustering algorithms over the underlying entity sets. / Ph. D.

This study was designed to determine whether chis-quared based tests for independence give reliable estimates (as compared to the exact values provided by Fisher's exact probabilities test) of the probability of a relationship between the variables in 3 X 3, 3 X 4 , and 3 X 5 contingency tables when the sample size is 10, 20, or 30. In addition to the classical (uncorrected) chi-squared test, four methods for continuity correction were compared to Fisher's exact probabilities test. The four methods were Yates' correction, two corrections attributed to Cochran, and Mantel's correction. The study was modeled after a similar comparison conducted on 2 X 2 contingency tables and published by Michael Haber.

Residual-based shadings for enhancing mosaic and association plots to visualize independence models for contingency tables are extended in two directions: (a) perceptually uniform HCL colors are used and (b) the result of an associated significance test is coded by the appearance of color in the visualization. For obtaining (a), a general strategy for deriving diverging palettes in the perceptually-based HCL space is suggested. As for (b), cut offs that control the appearance of color are computed in a data-driven way based on the conditional permutation distribution of maximum-type test statistics. The shadings are first established for the case of independence in 2-way tables and then extended to more general independence models for multi-way tables, including in particular conditional independence problems. / Series: Research Report Series / Department of Statistics and Mathematics

by Wai-chuen Tso. / Thesis (M.Phil.)--Chinese University of Hong Kong, 1995. / Includes bibliographical references (leaves 90-94). / Chapter 1 --- Introduction --- p.1 / Chapter 2 --- Prior Information --- p.5 / Chapter 2.1 --- Prior Distribution --- p.6 / Chapter 2.2 --- Quantification of Prior Belief --- p.10 / Chapter 2.2.1 --- Prior Belief --- p.10 / Chapter 2.2.2 --- Some Basic Concepts of Fuzzy Set Theory --- p.12 / Chapter 2.2.3 --- Quantification --- p.16 / Chapter 2.3 --- Specification and Determination of Model Parameters --- p.20 / Chapter 2.3.1 --- A Questionnaire --- p.21 / Chapter 2.3.2 --- Parameter Value --- p.22 / Chapter 2.3.3 --- Determination of Degree of Fuzziness --- p.23 / Chapter 2.4 --- Comments --- p.26 / Chapter 2.4.1 --- Interpretation of Time Length of Poisson Process --- p.26 / Chapter 2.4.2 --- Likelihood Interpretation of Membership Value --- p.28 / Chapter 2.4.3 --- Comparison with Existing Modeling --- p.30 / Chapter 2.4.4 --- Conclusion of Prior Information --- p.31 / Chapter 3 --- Posterior Analysis --- p.33 / Chapter 3.1 --- Posterior Analysis by Monte Carlo Method --- p.34 / Chapter 3.1.1 --- Monte Carlo Method --- p.34 / Chapter 3.1.2 --- Estimation of Posterior Mean and Posterior Variance of Log-odds Ratio --- p.35 / Chapter 3.1.3 --- Construction of Credible Region of Log-odds Ratio --- p.38 / Chapter 3.1.4 --- Estimation of Posterior Mean of Cell Probability --- p.41 / Chapter 3.2 --- Sampling of Prior Cell Frequency Vector by Gibbs Sampler --- p.42 / Chapter 3.2.1 --- Gibbs Sampler --- p.42 / Chapter 3.2.2 --- Two Sampling Algorithms --- p.45 / Chapter 3.2.3 --- Acceptance-Rejection Algorithm --- p.50 / Chapter 3.3 --- Some Practical Problems --- p.51 / Chapter 3.3.1 --- Number of Iterations in Gibbs Sampler --- p.51 / Chapter 3.3.2 --- Sample Size of Gibbs Sample --- p.53 / Chapter 4 --- Simulation Study --- p.58 / Chapter 4.1 --- Multinomial Model --- p.59 / Chapter 4.1.1 --- Determination of Number of Iterations --- p.61 / Chapter 4.1.2 --- Determination of Sample Size --- p.62 / Chapter 4.1.3 --- Posterior Estimation --- p.63 / Chapter 4.1.4 --- Sensitivity Analysis --- p.64 / Chapter 4.2 --- Poisson Model --- p.71 / Chapter 4.2.1 --- Determination of Number of Iterations --- p.72 / Chapter 4.2.2 --- Determination of Sample Size --- p.73 / Chapter 4.2.3 --- Posterior Estimation --- p.74 / Chapter 4.2.4 --- Sensitivity Analysis --- p.75 / Chapter 4.3 --- Conclusion --- p.82 / Chapter 5 --- Conclusions and Discussions --- p.85 / References --- p.90