Topics in life history analysis, inference and prediction

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The objectives of the research are to provide statistical methods for studying complex processes and data sets, and for predicting outcomes within complex processes. Many applications of the research are in the area known as life history analysis, which deals with events and other phenomena that occur in populations or systems. For example, in medicine and public health we consider the occurrence and treatment of diseases, and their associated causes and consequences. In socioeconomic studies, events related to education, employment, conjugal status and parenthood are studied. In technological systems used in manufacturing or telecommunications, it is important to track events triggering system failures and to determine their causes. Considerable amounts of data are collected in complex processes, but to extract information from them requires sophisticated analysis. In addition, the data have missing elements and suffer from inaccuracy, further complicating its analysis. The proposed research aims to develop models for complex processes and then to analyze the processes using available data. The methods developed will be used to understand and predict events that occur in medicine, public health, manufacturing, and other areas. Applications of the applicant's previous research include the prediction of new cases of AIDS, and the prediction of warranty claims for manufactured products.