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Tese de mestrado integrado. Engenharia Civil (Especialização em Construções Civis). Faculdade de Engenharia. Universidade do Porto. 2010

Este trabajo de tesis se realizó con el objetivo de proyectar las exportaciones mensuales del Perú mediante el Análisis Factorial Dinámico, modelo que consiste en la reducción de la dimensionalidad de las series a ser utilizadas como variables explicativas en la proyección de una serie macroeconómica desde un número grande a un número más pequeño de indicadores o factores. Este modelo fue desarrollado por Sargent y Sims (1977) e implementado por Aguirre y Céspedes (2004). En el Perú, las variables bajo estudio se concentraron en el primer factor al que se le denominó factor macroeconómico, posteriormente, se aplicó un modelo SARIMA para suavizar los errores de estimación y un Análisis de Intervención con el objetivo de disminuir el efecto producido por la caída de las exportaciones peruanas en el 2009 debido a la crisis mundial en ese periodo. Finalmente se obtuvo un modelo interesante el cual otorgaba mayor exactitud en la proyección de las exportaciones en el Perú explicando su variabilidad en un 97.5%. / Tesis

Thesis (Ph.D.)--McMaster University, 2004. / Supervisor: N. Balakrishnan. Includes bibliographical references (p. 98-101).

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Men commit the majority of violent crime, yet the majority of men do not commit violent crime. Why is this? Research connecting men and violence cannot fully explain this phenomenon, namely, the variation among men regarding violence. This research study seeks to empirically measure masculinity and to study its relationship to perceptions of violence. My primary hypothesis is that men who measure as more `masculine' will be more accepting of violence. My secondary hypothesis is that situational contexts are also important for the acceptance of violence. These hypotheses are examined using the Conformity to Masculine Norms Inventory and randomized factorial vignettes. Results indicate that those who more strongly conform to masculine norms are more likely to be accepting of the violence represented in these vignettes.

Uniform design has found successful applications in manufacturing, system engineering, pharmaceutics and natural sciences since it appeared in 1980's. Recently, research related to uniform design is emerging. Discussions are mainly focusing on the construction and the theoretical properties of uniform design. On one hand, new construction methods can help researchers to search for uniform designs in more efficient and effective ways. On the other hand, since uniformity has been accepted as an essential criterion for comparing fractional factorial designs, it is interesting to explore its relationship with other criteria, such as aberration, orthogonality, confounding, etc. The first goal of this thesis is to propose new uniform design construction methods and recommend designs with good uniformity. A novel stochastic heuristic technique, the adjusted threshold accepting algorithm, is proposed for searching uniform designs. This algorithm has successfully generated a number of uniform designs, which outperforms the existing uniform design tables in the website https://uic.edu.hk/~isci/UniformDesign/UD%20Tables.html. In addition, designs with good uniformity are recommended for screening either qualitative or quantitative factors via a comprehensive study of symmetric orthogonal designs with 27 runs, 3 levels and 13 factors. These designs are also outstanding under other traditional criteria. The second goal of this thesis is to give an in-depth study of the uniformity property of fractional factorial designs. Close connections between different criteria and lower bounds of the average uniformity have been revealed, which can be used as benchmarks for selecting the best designs. Moreover, we find non-isomorphic designs have different combinatorial and geometric properties in their projected and level permutated designs. Two new non-isomorphic detection methods are proposed and utilized for classifying fractional factorial designs. The new methods take advantages over the existing ones in terms of computation efficiency and classification capability. Finally, the relationship between uniformity and isomorphism of fractional factorial designs has been discussed in detail. We find isomorphic designs may have different geometric structure and propose a new isomorphic identification method. This method significantly reduces the computational complexity of the procedure. A new uniformity criterion, the uniformity pattern, is proposed to evaluate the overall uniformity performance of an isomorphic design set.

Uniform design has found successful applications in manufacturing, system engineering, pharmaceutics and natural sciences since it appeared in 1980's. Recently, research related to uniform design is emerging. Discussions are mainly focusing on the construction and the theoretical properties of uniform design. On one hand, new construction methods can help researchers to search for uniform designs in more efficient and effective ways. On the other hand, since uniformity has been accepted as an essential criterion for comparing fractional factorial designs, it is interesting to explore its relationship with other criteria, such as aberration, orthogonality, confounding, etc. The first goal of this thesis is to propose new uniform design construction methods and recommend designs with good uniformity. A novel stochastic heuristic technique, the adjusted threshold accepting algorithm, is proposed for searching uniform designs. This algorithm has successfully generated a number of uniform designs, which outperforms the existing uniform design tables in the website https://uic.edu.hk/~isci/UniformDesign/UD%20Tables.html. In addition, designs with good uniformity are recommended for screening either qualitative or quantitative factors via a comprehensive study of symmetric orthogonal designs with 27 runs, 3 levels and 13 factors. These designs are also outstanding under other traditional criteria. The second goal of this thesis is to give an in-depth study of the uniformity property of fractional factorial designs. Close connections between different criteria and lower bounds of the average uniformity have been revealed, which can be used as benchmarks for selecting the best designs. Moreover, we find non-isomorphic designs have different combinatorial and geometric properties in their projected and level permutated designs. Two new non-isomorphic detection methods are proposed and utilized for classifying fractional factorial designs. The new methods take advantages over the existing ones in terms of computation efficiency and classification capability. Finally, the relationship between uniformity and isomorphism of fractional factorial designs has been discussed in detail. We find isomorphic designs may have different geometric structure and propose a new isomorphic identification method. This method significantly reduces the computational complexity of the procedure. A new uniformity criterion, the uniformity pattern, is proposed to evaluate the overall uniformity performance of an isomorphic design set.

Master of Science / Department of Statistics / James J. Higgins / Completely random and randomized block designs involving n factors at each of two levels are used to screen for the effects of a large number of factors. With such designs it may not be possible either because of costs or because of time to run each treatment combination more than once. In some cases, only a fraction of all the treatments may be run. With a large number of factors and limited observations, even one outlier can adversely affect the results. Robust regression methods are designed to down-weight the adverse affects of outliers. However, to our knowledge practitioners do not routinely apply robust regression methods in the context of fractional replication of 2^n factorial treatment structures. The purpose of this report is examine how robust regression methods perform in this context.

In previous work (Olshausen & Field 1996), an algorithm was described for learning linear sparse codes which, when trained on natural images, produces a set of basis functions that are spatially localized, oriented, and bandpass (i.e., wavelet-like). This note shows how the algorithm may be interpreted within a maximum-likelihood framework. Several useful insights emerge from this connection: it makes explicit the relation to statistical independence (i.e., factorial coding), it shows a formal relationship to the algorithm of Bell and Sejnowski (1995), and it suggests how to adapt parameters that were previously fixed.