Bayesian change-point analysis in linear regression model with scale mixtures of normal distributions

In this thesis, we consider Bayesian inference on the detection of variance change-point models with scale mixtures of normal (for short SMN) distributions. This class of distributions is symmetric and thick-tailed and includes as special cases: Gaussian, Student-t, contaminated normal, and slash distributions. The proposed models provide greater flexibility to analyze a lot of practical data, which often show heavy-tail and may not satisfy the normal assumption. As to the Bayesian analysis, we specify some prior distributions for the unknown parameters in the variance change-point models with the SMN distributions. Due to the complexity of the joint posterior distribution, we propose an efficient Gibbs-type with Metropolis- Hastings sampling algorithm for posterior Bayesian inference. Thereafter, following the idea of [1], we consider the problems of the single and multiple change-point detections. The performance of the proposed procedures is illustrated and analyzed by simulation studies. A real application to the closing price data of U.S. stock market has been analyzed for illustrative purposes.

Quantitative 1H-magnetic resonance spectroscopy of human brain: Influence of composition and parameterization of the basis set in linear combination model-fitting

Localized short-echo-time (1)H-MR spectra of human brain contain contributions of many low-molecular-weight metabolites and baseline contributions of macromolecules. Two approaches to model such spectra are compared and the data acquisition sequence, optimized for reproducibility, is presented. Modeling relies on prior knowledge constraints and linear combination of metabolite spectra. Investigated was what can be gained by basis parameterization, i.e., description of basis spectra as sums of parametric lineshapes. Effects of basis composition and addition of experimentally measured macromolecular baselines were investigated also. Both fitting methods yielded quantitatively similar values, model deviations, error estimates, and reproducibility in the evaluation of 64 spectra of human gray and white matter from 40 subjects. Major advantages of parameterized basis functions are the possibilities to evaluate fitting parameters separately, to treat subgroup spectra as independent moieties, and to incorporate deviations from straightforward metabolite models. It was found that most of the 22 basis metabolites used may provide meaningful data when comparing patient cohorts. In individual spectra, sums of closely related metabolites are often more meaningful. Inclusion of a macromolecular basis component leads to relatively small, but significantly different tissue content for most metabolites. It provides a means to quantitate baseline contributions that may contain crucial clinical information.

Detecting genetic and nutritional lung cancer risk factors related to folate metabolism using Bayesian generalized linear models

Complex diseases, such as cancer, are caused by various genetic and environmental factors, and their interactions. Joint analysis of these factors and their interactions would increase the power to detect risk factors but is statistically. Bayesian generalized linear models using student-t prior distributions on coefficients, is a novel method to simultaneously analyze genetic factors, environmental factors, and interactions. I performed simulation studies using three different disease models and demonstrated that the variable selection performance of Bayesian generalized linear models is comparable to that of Bayesian stochastic search variable selection, an improved method for variable selection when compared to standard methods. I further evaluated the variable selection performance of Bayesian generalized linear models using different numbers of candidate covariates and different sample sizes, and provided a guideline for required sample size to achieve a high power of variable selection using Bayesian generalize linear models, considering different scales of number of candidate covariates. ^ Polymorphisms in folate metabolism genes and nutritional factors have been previously associated with lung cancer risk. In this study, I simultaneously analyzed 115 tag SNPs in folate metabolism genes, 14 nutritional factors, and all possible genetic-nutritional interactions from 1239 lung cancer cases and 1692 controls using Bayesian generalized linear models stratified by never, former, and current smoking status. SNPs in MTRR were significantly associated with lung cancer risk across never, former, and current smokers. In never smokers, three SNPs in TYMS and three gene-nutrient interactions, including an interaction between SHMT1 and vitamin B12, an interaction between MTRR and total fat intake, and an interaction between MTR and alcohol use, were also identified as associated with lung cancer risk. These lung cancer risk factors are worthy of further investigation.^

Robust effect sizes and their confidence intervals for group difference between trajectories in hierarchical linear growth model

Hierarchical linear growth model (HLGM), as a flexible and powerful analytic method, has played an increased important role in psychology, public health and medical sciences in recent decades. Mostly, researchers who conduct HLGM are interested in the treatment effect on individual trajectories, which can be indicated by the cross-level interaction effects. However, the statistical hypothesis test for the effect of cross-level interaction in HLGM only show us whether there is a significant group difference in the average rate of change, rate of acceleration or higher polynomial effect; it fails to convey information about the magnitude of the difference between the group trajectories at specific time point. Thus, reporting and interpreting effect sizes have been increased emphases in HLGM in recent years, due to the limitations and increased criticisms for statistical hypothesis testing. However, most researchers fail to report these model-implied effect sizes for group trajectories comparison and their corresponding confidence intervals in HLGM analysis, since lack of appropriate and standard functions to estimate effect sizes associated with the model-implied difference between grouping trajectories in HLGM, and also lack of computing packages in the popular statistical software to automatically calculate them. ^ The present project is the first to establish the appropriate computing functions to assess the standard difference between grouping trajectories in HLGM. We proposed the two functions to estimate effect sizes on model-based grouping trajectories difference at specific time, we also suggested the robust effect sizes to reduce the bias of estimated effect sizes. Then, we applied the proposed functions to estimate the population effect sizes (d ) and robust effect sizes (du) on the cross-level interaction in HLGM by using the three simulated datasets, and also we compared the three methods of constructing confidence intervals around d and du recommended the best one for application. At the end, we constructed 95% confidence intervals with the suitable method for the effect sizes what we obtained with the three simulated datasets. ^ The effect sizes between grouping trajectories for the three simulated longitudinal datasets indicated that even though the statistical hypothesis test shows no significant difference between grouping trajectories, effect sizes between these grouping trajectories can still be large at some time points. Therefore, effect sizes between grouping trajectories in HLGM analysis provide us additional and meaningful information to assess group effect on individual trajectories. In addition, we also compared the three methods to construct 95% confident intervals around corresponding effect sizes in this project, which handled with the uncertainty of effect sizes to population parameter. We suggested the noncentral t-distribution based method when the assumptions held, and the bootstrap bias-corrected and accelerated method when the assumptions are not met.^

Fine spatial pattern of an epiphytic lichen species is affected by habitat conditions in two forest types in the Iberian Mediterranean region

Persistence and abundance of species is determined by habitat availability and the ability to disperse and colonize habitats at contrasting spatial scales. Favourable habitat fragments are also heterogeneous in quality, providing differing opportunities for establishment and affecting the population dynamics of a species. Based on these principles, we suggest that the presence and abundance of epiphytes may reflect their dispersal ability, which is primarily determined by the spatial structure of host trees, but also by host quality. To our knowledge there has been no explicit test of the importance of host tree spatial pattern for epiphytes in Mediterranean forests. We hypothesized that performance and host occupancy in a favourable habitat depend on the spatial pattern of host trees, because this pattern affects the dispersal ability of each epiphyte and it also determines the availability of suitable sites for establishment. We tested this hypothesis using new point pattern analysis tools and generalized linear mixed models to investigate the spatial distribution and performance of the epiphytic lichen Lobaria pulmonaria, which inhabits two types of host trees (beeches and Iberian oaks). We tested the effects on L. pulmonaria distribution of tree size, spatial configuration, and host tree identity. We built a model including tree size, stand structure, and several neighbourhood predictors to understand the effect of host tree on L. pulmonaria. We also investigated the relative importance of spatial patterning on the presence and abundance of the species, independently of the host tree configuration. L. pulmonaria distribution was highly dependent on habitat quality for successful establishment, i.e., tree species identity, tree diameter, and several forest stand structure surrogates. For beech trees, tree diameter was the main factor influencing presence and cover of the lichen, although larger lichen-colonized trees were located close to focal trees, i.e., young trees. However, oak diameter was not an important factor, suggesting that bark roughness at all diameters favoured lichen establishment. Our results indicate that L. pulmonaria dispersal is not spatially restricted, but it is dependent on habitat quality. Furthermore, new spatial analysis tools suggested that L. pulmonaria cover exhibits a distinct pattern, although the spatial pattern of tree position and size was random.

Fine spatial pattern of an epiphytic lichen species is affected by habitat conditions in two forest types in the Iberian Mediterranean region

Persistence and abundance of species is determined by habitat availability and the ability to disperse and colonize habitats at contrasting spatial scales. Favourable habitat fragments are also heterogeneous in quality, providing differing opportunities for establishment and affecting the population dynamics of a species. Based on these principles, we suggest that the presence and abundance of epiphytes may reflect their dispersal ability, which is primarily determined by the spatial structure of host trees, but also by host quality. To our knowledge there has been no explicit test of the importance of host tree spatial pattern for epiphytes in Mediterranean forests. We hypothesized that performance and host occupancy in a favourable habitat depend on the spatial pattern of host trees, because this pattern affects the dispersal ability of each epiphyte and it also determines the availability of suitable sites for establishment. We tested this hypothesis using new point pattern analysis tools and generalized linear mixed models to investigate the spatial distribution and performance of the epiphytic lichen Lobaria pulmonaria, which inhabits two types of host trees (beeches and Iberian oaks). We tested the effects on L. pulmonaria distribution of tree size, spatial configuration, and host tree identity. We built a model including tree size, stand structure, and several neighbourhood predictors to understand the effect of host tree on L. pulmonaria. We also investigated the relative importance of spatial patterning on the presence and abundance of the species, independently of the host tree configuration. L. pulmonaria distribution was highly dependent on habitat quality for successful establishment, i.e., tree species identity, tree diameter, and several forest stand structure surrogates. For beech trees, tree diameter was the main factor influencing presence and cover of the lichen, although larger lichen-colonized trees were located close to focal trees, i.e., young trees. However, oak diameter was not an important factor, suggesting that bark roughness at all diameters favoured lichen establishment. Our results indicate that L. pulmonaria dispersal is not spatially restricted, but it is dependent on habitat quality. Furthermore, new spatial analysis tools suggested that L. pulmonaria cover exhibits a distinct pattern, although the spatial pattern of tree position and size was random.

An empirical mixed model to quantify climate influence on the growth of Pinus halepensis Mill. stands in South-Eastern Spain

The influence of climate on forest stand composition, development and growth is undeniable. Many studies have tried to quantify the effect of climatic variables on forest growth and yield. These works become especially important because there is a need to predict the effects of climate change on the development of forest ecosystems. One of the ways of facing this problem is the inclusion of climatic variables into the classic empirical growth models. The work has a double objective: (i) to identify the indicators which best describe the effect of climate on Pinus halepensis growth and (ii) to quantify such effect in several scenarios of rainfall decrease which are likely to occur in the Mediterranean area. A growth mixed model for P. halepensis including climatic variables is presented in this work. Growth estimates are based on data from the Spanish National Forest Inventory (SNFI). The best results are obtained for the indices including rainfall, or rainfall and temperature together, with annual precipitation, precipitation effectiveness, Emberger?s index or free bioclimatic intensity standing out among them. The final model includes Emberger?s index, free bioclimatic intensity and interactions between competition and climate indices. The results obtained show that a rainfall decrease about 5% leads to a decrease in volume growth of 5.5?7.5% depending on site quality.

Deforestación y Pérdida de hábitat en Bosques de montaña en la Cuenca alta del Río Zamora (Loja, Ecuador)

Los bosques húmedos de montaña se encuentran reconocidos como uno de los ecosistemas más amenazados en el mundo, llegando inclusive a ser considerado como un “hotspot” por su alta diversidad y endemismo. La acelerada pérdida de cobertura vegetal de estos bosques ha ocasionado que, en la actualidad, se encuentren restringidos a una pequeña fracción de su área de distribución histórica. Pese a esto, los estudios realizados sobre cual es efecto de la deforestación, fragmentación, cambios de uso de suelo y su efecto en las comunidades de plantas presentes en este tipo de vegetación aún son muy escuetos, en comparación a los realizados con sus similares amazónicos. En este trabajo, el cual se encuentra dividido en seis capítulos, abordaremos los siguientes objetivos: a) Comprender cuál es la dinámica que han seguido los diferentes tipos de bosques montanos andinos de la cuenca del Rio Zamora, Sur de Ecuador durante entre 1976 y 2002. b) Proveer de evidencia de las tasas de deforestación y fragmentación de todos los tipos diferentes de bosques montanos andinos presentes en la cuenca del Rio Zamora, Sur de Ecuador entre 1976 y 2002. c) Determinar qué factores inducen a la fragmentación de bosques de montaña en la cuenca alta del río Zamora entre 1976 y 2002. d) Determinar cuáles son y cómo afectan los factores ambientales y socioeconómicos a la dinámica de la deforestación y regeneración (pérdida y recuperación del hábitat) sufrida por los bosques de montaña dentro de la zona de estudio y e) Determinar si la deforestación y fragmentación actúan sobre la diversidad y estructura de las comunidades de tres tipos de organismos (comunidades de árboles, comunidades de líquenes epífitos y comunidades de hepáticas epífitas). Este estudio se centró en el cuenca alta del río Zamora, localizada al sur de Ecuador entre las coordenadas 3º 00´ 53” a 4º 20´ 24.65” de latitud sur y 79º 49´58” a 78º 35´ 38” de longitud oeste, que cubre alrededor de 4300 km2 de territorio situado entre las capitales de las provincias de Loja y Zamora-Chinchipe. Con objeto de predecir la dinámica futura de la deforestación en la región de Loja y cómo se verán afectados los diferentes tipos de hábitat, así como para detectar los factores que más influyen en dicha dinámica, se han construido modelos basados en la historia de la deforestación derivados de fotografías aéreas e imágenes satelitales de tres fechas (1976, 1989 y 2002). La cuantificación de la deforestación se realizó mediante la tasa de interés compuesto y para la caracterización de la configuración espacial de los fragmentos de bosque nativo se calcularon índices de paisaje los cuales fueron calculados utilizando el programa Fragstats 3.3. Se ha clasificado el recubrimiento del terreno en forestal y no forestal y se ha modelado su evolución temporal con Modelos Lineales Generalizados Mixtos (GLMM), empleando como variables explicativas tanto variables ambientales espacialmente explícitas (altitud, orientación, pendiente, etc) como antrópicas (distancia a zonas urbanizadas, deforestadas, caminos, entre otras). Para medir el efecto de la deforestación sobre las comunidades modelo (de árboles, líquenes y hepáticas) se monitorearon 11 fragmentos de vegetación de distinto tamaño: dos fragmentos de más de cien hectáreas, tres fragmentos de entre diez y noventa ha y seis fragmentos de menos de diez hectáreas. En ellos se instalaron un total de 38 transectos y 113 cuadrantes de 20 x 20 m a distancias que se alejaban progresivamente del borde en 10, 40 y 80 m. Nuestros resultados muestran una tasa media anual de deforestación del 1,16% para todo el período de estudio, que el tipo de vegetación que más alta tasa de destrucción ha sufrido, es el páramo herbáceo, con un 2,45% anual. El análisis de los patrones de fragmentación determinó un aumento en 2002 de más del doble de fragmentos presentes en 1976, lo cual se repite en el análisis del índice de densidad promedio. El índice de proximidad media entre fragmentos muestra una reducción progresiva de la continuidad de las áreas forestadas. Si bien las formas de los fragmentos se han mantenido bastante similares a lo largo del período de estudio, la conectividad entre estos ha disminuido en un 84%. Por otro lado, de nuestros análisis se desprende que las zonas con mayor probabilidad de deforestarse son aquellas que están cercanas a zonas previamente deforestadas; la cercanía a las vías también influye significativamente en la deforestación, causando un efecto directo en la composición y estructura de las comunidades estudiadas, que en el caso de los árboles viene mediado por el tamaño del fragmento y en el caso del componente epífito (hepáticas y líquenes), viene mediado tanto por el tamaño del fragmento como por la distancia al borde del mismo. Se concluye la posibilidad de que, de mantenerse esta tendencia, este tipo de bosques desaparecerá en corto tiempo y los servicios ecosistémicos que prestan, se verán seriamente comprometidos. ABSTRACT Mountain rainforests are recognized as one of the most threatened ecosystems in the world, and have even come to be considered as a “hotspot” due to their high degree of diversity and endemism. The accelerated loss of plant cover of these forests has caused them to be restricted today to a small fraction of their area of historic distribution. In spite of this, studies done on the effect of deforestation, fragmentation, changes in soil use and their effect on the plant communities present in this type of vegetation are very brief compared to those done on their analogues in the Amazon region. In this study, which is divided into six chapters, we will address the following objectives: a) To understand what the dynamic followed by the different types of Andean mountain forests in the Zamora River watershed of southern Ecuador has been between 1976 and 2002. b) To provide evidence of the rates of deforestation and fragmentation of all the different types of Andean mountain forests existing in the upper watershed of the Zamora River between 1976 and 2002. c) To determine the factors that induces fragmentation of all different types of Andean mountain forests existing in the upper watershed of the Zamora River between 1976 and 2002. d) To determine what the environmental and anthropogenic factors are driving the dynamic of deforestation and regeneration (loss and recuperation of the habitat) suffered by the mountain forests in the area of the study and e) To determine if the deforestation and fragmentation act upon the diversity and structure of three model communities: trees, epiphytic lichens and epiphytic liverworts. This study is centered on the upper Zamora River watershed, located in southern Ecuador between 3º 00´ 53” and 4º 20´ 24.65 south latitude and 79º 49´ 58” to 78º 35´ 38” west longitude, and covers around 4,300 km2 of territory located between Loja and Zamora-Chinchipe provinces. For the purpose of predicting the future dynamic of deforestation in the Loja region and how different types of habitats will be affected, as well as detecting the environmental and socioeconomic factors that influence landscape dynamics, models were constructed based on deforestation history, derived from aerial photographs and satellite images for three dates (1976, 1989 and 2002). Quantifying the deforestation was done using the compound interest rate; to characterize the spatial configuration of fragments of native forest, landscape indices were calculated with Fragstats 3.3 program. Land cover was classified as forested and not forested and its evolution over time was modeled with Generalized Linear Mixed Models (GLMM), using spatially explicit environmental variables (altitude, orientation, slope, etc.) as well as anthropic variables (distance to urbanized, deforested areas and roads, among others) as explanatory variables. To measure the effects of fragmentation on three types of model communities (forest trees and epiphytic lichen and liverworts), 11 vegetation fragments of different sizes were monitored: two fragments of more than one hundred hectares, three fragments of between ten and ninety ha and six fragments of fewer than ten hectares . In these fragments, a total of 38 transects and 113 20 x 20 m quadrats were installed at distances that progressively moved away from the edge of the fragment by 10, 40 and 80 m. Our results show an average annual rate of deforestation of 1.16% for the entire period of the study, and that the type of vegetation that suffered the highest rate of destruction was grassy paramo, with an annual rate of 2.45%. The analysis of fragmentation patterns determined the number of fragments in 2002 more than doubled the number of fragments present in 1976, and the same occurred for the average density index. The variation of the average proximity index among fragments showed a progressive reduction of the continuity of forested areas. Although fragment shapes have remained quite similar over the period of the study, connectivity among them has diminished by 84%. On the other hand, it emerged from our analysis that the areas of greatest probability of deforestation were those that are close to previously deforested areas; proximity to roads also significantly favored the deforestation causing a direct effect on the composition of our model communities, that in the case of forest trees is determined by the size of the fragment, and in the case of the epiphyte communities (liverworts and lichens), is determined, by the size of the fragment as well as the distance to edge. A subject under discussion is the possibility that if this tendency continues, this type of forest will disappear in a short time, and the ecological services it provides, will be seriously endangered.

Análise genética da produção in vitro de embriões em bovinos Guzerá

O objetivo dessa pesquisa foi avaliar aspectos genéticos que relacionados à produção in vitro de embriões na raça Guzerá. O primeiro estudo focou na estimação de (co) variâncias genéticas e fenotípicas em características relacionadas a produção de embriões e na detecção de possível associação com a idade ao primeiro parto (AFC). Foi detectada baixa e média herdabilidade para características relacionadas à produção de oócitos e embriões. Houve fraca associação genética entre características ligadas a reprodução artificial e a idade ao primeiro parto. O segundo estudo avaliou tendências genéticas e de endogamia em uma população Guzerá no Brasil. Doadoras e embriões produzidos in vitro foram considerados como duas subpopulações de forma a realizar comparações acerca das diferenças de variação anual genética e do coeficiente de endogamia. A tendência anual do coeficiente de endogamia (F) foi superior para a população geral, sendo detectado efeito quadrático. No entanto, a média de F para a sub- população de embriões foi maior do que na população geral e das doadoras. Foi observado ganho genético anual superior para a idade ao primeiro parto e para a produção de leite (305 dias) entre embriões produzidos in vitro do que entre doadoras ou entre a população geral. O terceiro estudo examinou os efeitos do coeficiente de endogamia da doadora, do reprodutor (usado na fertilização in vitro) e dos embriões sobre resultados de produção in vitro de embriões na raça Guzerá. Foi detectado efeito da endogamia da doadora e dos embriões sobre as características estudadas. O quarto (e último) estudo foi elaborado para comparar a adequação de modelos mistos lineares e generalizados sob método de Máxima Verossimilhança Restrita (REML) e sua adequação a variáveis discretas. Quatro modelos hierárquicos assumindo diferentes distribuições para dados de contagem encontrados no banco. Inferência foi realizada com base em diagnósticos de resíduo e comparação de razões entre componentes de variância para os modelos em cada variável. Modelos Poisson superaram tanto o modelo linear (com e sem transformação da variável) quanto binomial negativo à qualidade do ajuste e capacidade preditiva, apesar de claras diferenças observadas na distribuição das variáveis. Entre os modelos testados, a pior qualidade de ajuste foi obtida para o modelo linear mediante transformação logarítmica (Log10 X +1) da variável resposta.

Assessment of University External Internships. Towards a Mixed Model for Measuring the Acquisition of Skills and the Satisfaction of Parties Involved

The continuous improvement of management and assessment processes for curricular external internships has led a group of university teachers specialised in this area to develop a mixed model of measurement that combines the verification of skill acquisition by those students choosing external internships with the satisfaction of the parties involved in that process. They included academics, educational tutors of companies and organisations and administration and services personnel in the latter category. The experience, developed within University of Alicante, has been carried out in the degrees of Business Administration and Management, Business Studies, Economics, Advertising and Public Relations, Sociology and Social Work, all part of the Faculty of Economics and Business. By designing and managing closed standardised interviews and other research tools, validated outside the centre, a system of continuous improvement and quality assurance has been created, clearly contributing to the gradual increase in the number of students with internships in this Faculty, as well as to the improvement in satisfaction, efficiency and efficacy indicators at a global level. As this experience of educational innovation has shown, the acquisition of curricular knowledge, skills, abilities and competences by the students is directly correlated with the satisfaction of those parties involved in a process that takes the student beyond the physical borders of a university campus. Ensuring the latter is a task made easier by the implementation of a mixed assessment method, combining continuous and final assessment, and characterised by its rigorousness and simple management. This report presents that model, subject in turn to a persistent and continuous control, a model all parties involved in the external internships are taking part of. Its short-term results imply an increase, estimated at 15% for the last course, in the number of students choosing curricular internships and, for the medium and long-term, a major interweaving between the academic world and its social and productive environment, both in the business and institutional areas. The potentiality of this assessment model does not lie only in the quality of its measurement tools, but also in the effects from its use in the various groups and in the actions that are carried out as a result of its implementation and which, without any doubt and as it is shown below, are the real guarantee of a continuous improvement.

RRREG: Stata module to estimate linear probability model for randomized response data

rrreg fits a linear probability model for randomized response data

A non-linear dynamic model for primates. Final report.

National Highway Traffic Safety Administration, Washington, D.C.