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Change-point detection in hazard rate function is an important research topic in survival analysis. In this dissertation, we firstly review existing methods for single change-point detection in piecewise exponential hazard model. Then we consider the problem of estimating the change point in the presence of right censoring and long-term survivors while using Kaplan-Meier estimator for the susceptible proportion. The maximum likelihood estimators are shown to be consistent. Taking one step further, we propose an counting process based and least squares based change-point detection algorithm. For single change-point case, consistency results are obtained. We then consider the detection of multiple change-points in the presence of long-term survivors via maximum likelihood based and counting process based method. Last but not least, we use a weighted least squares based and counting process based method for detection of multiple change-points with long-term survivors and covariates. For multiple change-points detection, simulation studies show good performances of our estimators under various parameters settings for both methods. All methods are applied to real data analyses. / Includes bibliography. / Dissertation (Ph.D.)--Florida Atlantic University, 2014. / FAU Electronic Theses and Dissertations Collection

This thesis focuses on the area of competitive intelligence with the emphasis on new possibilities and opportunities in relation to modern social networks. First it gives general analysis of the current state of competitive intelligence market as a whole and then deals with individual major leaders and their products, thus providing detailed overview of this business segment. It also discusses the possibilities of using social networks and other social or soft sources for competitive intelligence. Practical part of the thesis then demonstrates the theoretical knowledge on a real life CI project, which took place in early 2012 in cooperation with experts from IBM, including some interesting results and findings in appendix. The whole chapter can be used as a reference model for future projects with similar goals.

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Thesis (Ph.D.) -- Mississippi State University. Department of Computer Science and Engineering. / Title from title screen. Includes bibliographical references.

Made available in DSpace on 2014-12-17T14:13:35Z (GMT). No. of bitstreams: 1 JoseWQ_TESE.pdf: 1778874 bytes, checksum: 7ff2c9f470b5b3873803d39a321ee362 (MD5) Previous issue date: 2009-10-05 / This work demonstrates the importance of using tools used in geographic information systems (GIS) and spatial data analysis (SDA) for the study of infectious diseases. Analysis methods were used to describe more fully the spatial distribution of a particular disease by incorporating the geographical element in the analysis. In Chapter 1, we report the historical evolution of these techniques in the field of human health and use Hansen s disease (leprosy) in Rio Grande do Norte as an example. In Chapter 2, we introduced a few basic theoretical concepts on the methodology and classified the types of spatial data commonly treated. Chapters 3 and 4 defined and demonstrated the use of the two most important techniques for analysis of health data, which are data point processes and data area. We modelled the case distribution of Hansen s disease in the city of Mossor? - RN. In the analysis, we used R scripts and made available routines and analitical procedures developed by the author. This approach can be easily used by researchers in several areas. As practical results, major risk areas in Mossor? leprosy were detected, and its association with the socioeconomic profile of the population at risk was found. Moreover, it is clearly shown that his approach could be of great help to be used continuously in data analysis and processing, allowing the development of new strategies to work might increase the use of such techniques in data analysis in health care / O presente trabalho demonstra a import?ncia do uso de ferramentas relacionadas ? sistemas de informa??o geogr?fica (SIG) e an?lise espacial de dados (AED) em estudos de doen?as infecciosas. M?todos de an?lise foram usados para descrever de forma mais abrangente a distribui??o espacial de doen?as a partir da incorpora??o do elemento geogr?fico na an?lise. No Cap?tulo 1 relata-se a evolu??o hist?rica da aplica??o destas t?cnicas no campo da sa?de humana e elege-se a hansen?ase no estado do Rio Grande do Norte como exemplo de aplica??o. No Cap?tulo 2 introduzem-se alguns conceitos te?ricos b?sicos sobre a metodologia e classificam-se os tipos de dados espaciais comumente tratados. Os Cap?tulos 3 e 4 definem e demonstram a utiliza??o das mais importantes t?cnicas de an?lise para os dois principais tipos de dados encontrados na sa?de, quais sejam dados de processos pontuais e dados de ?rea, focalizando como estudo de caso a hansen?ase na cidade de Mossor? RN. Na an?lise, ? priorizada a utiliza??o do sistema R, disponibilizando-se scripts de rotinas e procedimentos de an?lise desenvolvidos pelo autor que podem ser facilmente utilizados por pesquisadores de diversas ?reas. Como resultados pr?ticos, importantes ?reas de risco da hansen?ase em Mossor? foram detectadas e sua forte associa??o com o perfil socioecon?mico da popula??o sob risco foi constatada. Al?m disso, estima-se que este trabalho possa vir a incrementar a utiliza??o de tais t?cnicas na an?lise de dados na ?rea de sa?de

This thesis introduces methods used in time-to-date analysis. It is written generally and so usable in dealing with any example. The thesis deals with problem of censoring, which means, that some observations occurred after the following, which is typical for the lifetime analysis. Methods mentioned in the thesis are nonparametric and parametric estimates of the survival function and their characteristics, and regression models, concretely Cox model and accelerated failure time model, which examine effect of the covariates on survival function. In the thesis is beside survival function presented hazard function, which express intensity of the analyzed event and cumulative hazard function, which is created as the name suggests by cumulative summation of the hazard function. Estimates of these functions are obtainable from survival function and for parametric estimate often exists formula resulting from parameters of used distribution. Empirical part of the thesis introduces influence of several different types and degrees of censoring on parametric and nonparametric estimates of the survival function, mean and median. The other empirical example is the usage of regression analysis on the data from the lungs cancer research made by Mayo Clinic.

There is a growing volume of global data, which is offering new possibilities for those market participants, who know to take advantage of it. Data, information and knowledge are new highly regarded commodity especially in the banking industry. Traditional data analytics is intended for processing data with known structure and meaning. But how can we get knowledge from data with no such structure? The thesis focuses on Big Data analytics and its use in banking and financial industry. Definition of specific applications in this area and description of benefits for international and Czech banking institutions are the main goals of the thesis. The thesis is divided in four parts. The first part defines Big Data trend, the second part specifies activities and tools in banking. The purpose of the third part is to apply Big Data analytics on those activities and shows its possible benefits. The last part focuses on the particularities of Czech banking and shows what actual situation about Big Data in Czech banks is. The thesis gives complex description of possibilities of using Big Data analytics. I see my personal contribution in detailed characterization of the application in real banking activities.

The thesis is focused on three basic parts – description of the theoretical and practical parts of measurements of LED modules front automotive headlamps, then design and realization of system for collecting and storing measurement data source and finally creation of server applications allowing via a web interface selection and display the required data.

The thesis is focused on values of the Czech society in 1990 - 2011, especially on hedonism value. It uses the method of a secondary analysis of quantitative data. We deal with the presumption that the social transformation which started in 1989, influenced value area as well. Our aim is to answer following questions: 1) Has an emphasis of hedonism in the Czech society changed during the social transformation? If yes, in what way? Can we observe continual rising of this value? 2) What is the influence of socio-demographic variables on hedonism? Is diferentiating influence of these variables on hedonism changing in time? An empirical part of this thesis is anticipated by the theoretical one, which is focused on research of values by social sciences and sociology, deals with questions about value stability and dynamism, presents a model of value dynamism by D. Slejška and draws up some consideration about influence of life circumstances - especially those which are related to the transformation of totalitarian society to freedom society - on the field of values. Keywords values - dynamism of values - hedonism - social transformation - public opinion surveys - secondary analysis of data