Physical activity among breast and prostate cancer survivors: Barriers, facilitators and maintenance following the FRESH START trial

Research provides evidence of the positive health effects associated with regular physical activity participation in all populations. Activity may prove to be especially beneficial in those with chronic conditions such as cancer. However, the majority of cancer patients and survivors do not participate in the recommended amount of physical activity. The purpose of this dissertation was to identify factors associated with physical activity participation, describe how these factors change as result of a diet and exercise intervention, and to evaluate correlates of long term physical activity maintenance. ^ For this dissertation, I analyzed data from the FRESH START trial, a randomized, single-blind, phase II clinical trial focused on improving diet and physical activity among recently diagnosed breast and prostate cancer survivors. Analyses included both parametric and non-parametric statistical tests. Three separate studies were conducted, with sample sizes ranging from 400 to 486. ^ Common barriers to exercise, such as “no willpower,” “too busy,” and “I have pain,” were reported among breast and prostate cancer survivors; however, these barriers were not significantly associated with minutes of physical activity. Breast cancer survivors reported a greater number of total barriers to exercise as well as higher proportions reporting individual barriers, compared to prostate cancer survivors. Just less than half of participants reduced their total number of barriers to exercise from baseline to 1-year follow-up, and those who did reduce barriers reported greater increases in minutes of physical activity compared to those who reported no change in barriers to exercise. Participants in both the tailored and standardized intervention groups reported greater minutes of physical activity at 2-year follow-up compared to baseline. Overall, twelve percent of participants reached recommended levels of physical activity at both 1- and 2-year follow-up. Self-efficacy was positively associated with physical activity maintenance, and the number of total barriers to exercise was inversely associated with physical activity maintenance. ^ Results from this dissertation are novel and informative, and will help to guide future physical activity interventions among cancer survivors. Thoughtfully designed interventions may encourage greater participation in physical activity and ultimately improve overall quality of life in this population. ^

Selection bias and the cross-validation of regression models for prediction

Strategies are compared for the development of a linear regression model with stochastic (multivariate normal) regressor variables and the subsequent assessment of its predictive ability. Bias and mean squared error of four estimators of predictive performance are evaluated in simulated samples of 32 population correlation matrices. Models including all of the available predictors are compared with those obtained using selected subsets. The subset selection procedures investigated include two stopping rules, C$\sb{\rm p}$ and S$\sb{\rm p}$, each combined with an 'all possible subsets' or 'forward selection' of variables. The estimators of performance utilized include parametric (MSEP$\sb{\rm m}$) and non-parametric (PRESS) assessments in the entire sample, and two data splitting estimates restricted to a random or balanced (Snee's DUPLEX) 'validation' half sample. The simulations were performed as a designed experiment, with population correlation matrices representing a broad range of data structures.^ The techniques examined for subset selection do not generally result in improved predictions relative to the full model. Approaches using 'forward selection' result in slightly smaller prediction errors and less biased estimators of predictive accuracy than 'all possible subsets' approaches but no differences are detected between the performances of C$\sb{\rm p}$ and S$\sb{\rm p}$. In every case, prediction errors of models obtained by subset selection in either of the half splits exceed those obtained using all predictors and the entire sample.^ Only the random split estimator is conditionally (on $\\beta$) unbiased, however MSEP$\sb{\rm m}$ is unbiased on average and PRESS is nearly so in unselected (fixed form) models. When subset selection techniques are used, MSEP$\sb{\rm m}$ and PRESS always underestimate prediction errors, by as much as 27 percent (on average) in small samples. Despite their bias, the mean squared errors (MSE) of these estimators are at least 30 percent less than that of the unbiased random split estimator. The DUPLEX split estimator suffers from large MSE as well as bias, and seems of little value within the context of stochastic regressor variables.^ To maximize predictive accuracy while retaining a reliable estimate of that accuracy, it is recommended that the entire sample be used for model development, and a leave-one-out statistic (e.g. PRESS) be used for assessment. ^

Método de evaluación a campo de la resistencia al moho azul en clones de ajo tipo colorado

Con el objeto de ajustar un método de evaluación a campo para facilitar la selección de clones de ajo (Allium sativum L.) con resistencia a Penicillium allii, se realizó un ensayo replicado en el cual se midió la respuesta de tres clones experimentales a la infección, en dos épocas de plantación. Los tratamientos incluyeron combinaciones de presencia o ausencia de: a) desinfección de la "semilla", b) heridas artificiales en los bulbillos, c) inoculación artificial. Los bulbillos con la hoja envolvente se desinfectaron con una solución diluida de hipoclorito de sodio. La inoculación se realizó mediante la inmersión en una solución de 106 esporas•ml-1. Las heridas se realizaron con una lanceta (blood lancet). Los bulbillos se incubaron en cámara húmeda durante 24 horas a 20 °C, antes de plantación. Las variables respuestas computadas fueron las siguientes: número de plantas muertas, y vivas con síntomas y sin síntomas, a los 152 días de plantación en la primera época y 118 días en la segunda; número de bulbos por calibres y rendimiento a cosecha. La información obtenida se analizó a través de correspondencia simple, diferencia de proporciones y análisis paramétricos. Se detectaron mayores diferencias entre los tratamientos en la tasa de sobrevivencia y en la proporción de calibres comerciales en la época tardía. No se observaron diferencias (p < 0,05) del rendimiento en la plantación temprana. La herida fue determinante en el ingreso del patógeno. Los tratamientos quedaron limitados a un testigo: desinfectado, no inoculado y sin herida, y a un tratamiento: desinfectado, con inoculación y herida. Con respecto a la época, resultó conveniente la evaluación en plantaciones tardías porque se expresan mejor las diferencias entre los tratamientos.

Impacto de la urbanización sobre las características hidroquímicas del acuífero libre : comparación estadística con el entorno rural, Coronel Moldes, Argentina

El objetivo consistió en evaluar el impacto que la actividad urbana ocasiona sobre la calidad del agua subterránea del área de Coronel Moldes. Se realizaron consideraciones geoquímicas en relación con el cálculo de línea de base hidroquímica, comparando con muestras extraídas del mismo acuífero en el entorno rural. Los indicadores de contaminación entre las distintas zonas rural y urbana (evaluados con la prueba t para muestras independientes y prueba no paramétrica de Mann- Whitney), indicaron que los valores de las componentes resultaban diferentes. Conductividad eléctrica, bicarbonatos, cloruros y nitratos mostraron en el área urbana valores medios superiores a aquellos del entorno rural que en general corresponden a los valores representativos del fondo natural regional de la calidad del agua subterránea. Se detectó en el área urbana un aumento en la dureza y Cl-/HCO3 - con importante contaminación microbiológica. Para evaluar el fondo regional se ajustaron los datos de los componentes iónicos analizados a las distribuciones teóricas (Normal, Laplace y f1). Se encontró que la distribución empírica presentaba un mejor acercamiento a f1 que a las otras dos, determinándose así como valor característico del fondo natural para cada ion, el estimador del parámetro de localización m* (combinación lineal entre la media y la mediana).

Tissue metal concentrations and metal transfer functions of Glaucous Gulls (Larus hyperboreus) from Bjørnøya and Jan Mayen

Heavy metals (Cd, Cu, Fe, Mn and Zn) concentrations were determined in different tissues (muscle, kidney, liver, brain, gonads, heart and feathers) of Glaucous Gulls (Larus hyperboreus) from Bjornoya and Jan Mayen. The age and spatial dependent variations in heavy metals were quantified and interpreted in view of the three chemometric techniques, i.e. non-parametric Mann-Whitney U test, redundancy gradient analysis and detrended correspondence analysis. The Glaucous Gulls from Bjornoya contained significantly higher (p < 0.05) levels of Cd, Cu and Zn than those inhabited Jan Mayen. Adult birds were characterized by greater (p < 0.01) concentration of muscle, hepatic and renal heavy metals in comparison to chicks. Insignificantly higher slope constant Zn/Cd for the liver than for the kidney may reflect insignificant Cd exposure. Estimate of transfer factor (TF) allows us to assess variations in heavy metal concentrations during the individual development of Glaucous Gulls. It may be stated that there is a distinct increase of bioaccumulation of all the studied metals during subsequent stages of the bird life.

Actividad microbiológica de un suelo sometido a distintos usos y su relación con variables físico- químicas

Gran parte de los procesos microbianos que contribuyen a la fertilidad de los agroecosistemas y el ciclado de nutrientes ocurren en el suelo. Este ciclado de nutrientes depende críticamente de la actividad microbiológica de los suelos, la cual a su vez está mediada por la estructura y funcionamiento de la microbiota edáfica. En este contexto, el objetivo de este trabajo, fue determinar si la actividad microbiana puede ser buena indicadora de la intensidad de uso del suelo, analizando: 1- si las diferencias en la intensidad de uso del suelo se relacionan con diferencias en la actividad microbiológica estimada a través de la respiración edáfica y la actividad enzimática; y 2- las posibles relaciones entre estas variables microbiológicas y las variables físico-químicas. Entre 2008 y 2010 se realizaron muestreos trimestrales en campos de la provincia de Buenos Aires en suelos Argiudoles bajo diferentes usos: 1- Agricultura intensiva continua, 2- Agricultura reciente, y 3- Pastizales naturalizados. Tres sitios de muestreo se seleccionaron como réplicas para cada uso de suelo, con 5 muestras por fecha y réplica. La actividad microbiana se evaluó midiendo la respiración edáfica y la actividad de las enzimas nitrogenasas y se analizaron variables físico- químicas. Tanto las variables microbiológicas como las físico-químicas se analizaron mediante Kruskall-Wallis (P < 0,05). Se exploró la asociación entre las variables físico-químicas y microbiológicas aplicando el coeficiente de correlación no paramétrico (Spearman). Los distintos usos de un mismo suelo presentaron diferencias en la actividad microbiológica. La respiración edáfica fue significativamente mayor en los pastizales naturalizados que en los sistemas con agricultura. La actividad nitrogenasa resultó significativamente mayor en los pastizales naturalizados respecto de la agricultura continua y no se diferenció significativamente de la agricultura reciente. Las variables físico- químicas resultaron menos consistentes en detectar diferencias entre usos. Se detectaron correlaciones significativas entre la actividad microbiológica y algunas de las variables físico-químicas. Los resultados muestran que la actividad microbiológica puede resultar útil para diferenciar intensidades de usos de suelo.

Participation in farmer's cooperatives and its effects on agricultural incomes : evidence from vegetable-producing areas in China

Chinese agricultural cooperatives, called Farmer's Professional Cooperatives (FPCs), are expected to become a major tool to facilitate agro-industrialization for small farmers through the diffusion of new technologies, the supply of high-quality agricultural inputs and the marketing of their products. This study compares FPC participants with vegetable-producing non-participants and grain farmers in vegetable-producing areas in rural China to investigate the treatment effect of participation in FPCs as well as implementation of vegetable cultivation. I adopt parametric and nonparametric approaches to precisely estimate the treatment effects. Estimated results indicate no significant difference between participants and non-participants of FPCs on agricultural net income in both parametric and non-parametric estimations. In contrast, the comparison between vegetable and grain farmers using propensity score matching (PSM) reveals that the treatment effect of vegetable cultivation is significantly positive for total and agricultural incomes, although vegetable cultivation involves more labor-intensive efforts. These results indicate that it is the implementation of vegetable cultivation rather than the participation in an FPC that enhances the economic welfare of farmers, due to the non-excludability of FPCs' services as well as the risks involved in vegetable cultivation.

Estimadores bayesianos de la fiabilidad con muestreo censurado

El estudio de la fiabilidad de componentes y sistemas tiene gran importancia en diversos campos de la ingenieria, y muy concretamente en el de la informatica. Al analizar la duracion de los elementos de la muestra hay que tener en cuenta los elementos que no fallan en el tiempo que dure el experimento, o bien los que fallen por causas distintas a la que es objeto de estudio. Por ello surgen nuevos tipos de muestreo que contemplan estos casos. El mas general de ellos, el muestreo censurado, es el que consideramos en nuestro trabajo. En este muestreo tanto el tiempo hasta que falla el componente como el tiempo de censura son variables aleatorias. Con la hipotesis de que ambos tiempos se distribuyen exponencialmente, el profesor Hurt estudio el comportamiento asintotico del estimador de maxima verosimilitud de la funcion de fiabilidad. En principio parece interesante utilizar metodos Bayesianos en el estudio de la fiabilidad porque incorporan al analisis la informacion a priori de la que se dispone normalmente en problemas reales. Por ello hemos considerado dos estimadores Bayesianos de la fiabilidad de una distribucion exponencial que son la media y la moda de la distribucion a posteriori. Hemos calculado la expansion asint6tica de la media, varianza y error cuadratico medio de ambos estimadores cuando la distribuci6n de censura es exponencial. Hemos obtenido tambien la distribucion asintotica de los estimadores para el caso m3s general de que la distribucion de censura sea de Weibull. Dos tipos de intervalos de confianza para muestras grandes se han propuesto para cada estimador. Los resultados se han comparado con los del estimador de maxima verosimilitud, y con los de dos estimadores no parametricos: limite producto y Bayesiano, resultando un comportamiento superior por parte de uno de nuestros estimadores. Finalmente nemos comprobado mediante simulacion que nuestros estimadores son robustos frente a la supuesta distribuci6n de censura, y que uno de los intervalos de confianza propuestos es valido con muestras pequenas. Este estudio ha servido tambien para confirmar el mejor comportamiento de uno de nuestros estimadores. SETTING OUT AND SUMMARY OF THE THESIS When we study the lifetime of components it's necessary to take into account the elements that don't fail during the experiment, or those that fail by reasons which are desirable to exclude from consideration. The model of random censorship is very usefull for analysing these data. In this model the time to failure and the time censor are random variables. We obtain two Bayes estimators of the reliability function of an exponential distribution based on randomly censored data. We have calculated the asymptotic expansion of the mean, variance and mean square error of both estimators, when the censor's distribution is exponential. We have obtained also the asymptotic distribution of the estimators for the more general case of censor's Weibull distribution. Two large-sample confidence bands have been proposed for each estimator. The results have been compared with those of the maximum likelihood estimator, and with those of two non parametric estimators: Product-limit and Bayesian. One of our estimators has the best behaviour. Finally we have shown by simulation, that our estimators are robust against the assumed censor's distribution, and that one of our intervals does well in small sample situation.

Segmentación de Secuencias de Vídeo: análisis y desarrollo de estrategias para la detección de cambios de toma y para la detección de objetos móviles

The important technological advances experienced along the last years have resulted in an important demand for new and efficient computer vision applications. On the one hand, the increasing use of video editing software has given rise to a necessity for faster and more efficient editing tools that, in a first step, perform a temporal segmentation in shots. On the other hand, the number of electronic devices with integrated cameras has grown enormously. These devices require new, fast, and efficient computer vision applications that include moving object detection strategies. In this dissertation, we propose a temporal segmentation strategy and several moving object detection strategies, which are suitable for the last generation of computer vision applications requiring both low computational cost and high quality results. First, a novel real-time high-quality shot detection strategy is proposed. While abrupt transitions are detected through a very fast pixel-based analysis, gradual transitions are obtained from an efficient edge-based analysis. Both analyses are reinforced with a motion analysis that allows to detect and discard false detections. This analysis is carried out exclusively over a reduced amount of candidate transitions, thus maintaining the computational requirements. On the other hand, a moving object detection strategy, which is based on the popular Mixture of Gaussians method, is proposed. This strategy, taking into account the recent history of each image pixel, adapts dynamically the amount of Gaussians that are required to model its variations. As a result, we improve significantly the computational efficiency with respect to other similar methods and, additionally, we reduce the influence of the used parameters in the results. Alternatively, in order to improve the quality of the results in complex scenarios containing dynamic backgrounds, we propose different non-parametric based moving object detection strategies that model both background and foreground. To obtain high quality results regardless of the characteristics of the analyzed sequence we dynamically estimate the most adequate bandwidth matrices for the kernels that are used in the background and foreground modeling. Moreover, the application of a particle filter allows to update the spatial information and provides a priori knowledge about the areas to analyze in the following images, enabling an important reduction in the computational requirements and improving the segmentation results. Additionally, we propose the use of an innovative combination of chromaticity and gradients that allows to reduce the influence of shadows and reflects in the detections.

Comparative analysis of meta-analysis methods: when to use which?

Background: Several meta-analysis methods can be used to quantitatively combine the results of a group of experiments, including the weighted mean difference, statistical vote counting, the parametric response ratio and the non-parametric response ratio. The software engineering community has focused on the weighted mean difference method. However, other meta-analysis methods have distinct strengths, such as being able to be used when variances are not reported. There are as yet no guidelines to indicate which method is best for use in each case. Aim: Compile a set of rules that SE researchers can use to ascertain which aggregation method is best for use in the synthesis phase of a systematic review. Method: Monte Carlo simulation varying the number of experiments in the meta analyses, the number of subjects that they include, their variance and effect size. We empirically calculated the reliability and statistical power in each case Results: WMD is generally reliable if the variance is low, whereas its power depends on the effect size and number of subjects per meta-analysis; the reliability of RR is generally unaffected by changes in variance, but it does require more subjects than WMD to be powerful; NPRR is the most reliable method, but it is not very powerful; SVC behaves well when the effect size is moderate, but is less reliable with other effect sizes. Detailed tables of results are annexed. Conclusions: Before undertaking statistical aggregation in software engineering, it is worthwhile checking whether there is any appreciable difference in the reliability and power of the methods. If there is, software engineers should select the method that optimizes both parameters.

Moving Object Detection for Real-Time High-Quality Lightweight Applications on Smart Cameras

Here, a novel and efficient strategy for moving object detection by non-parametric modeling on smart cameras is presented. Whereas the background is modeled using only color information, the foreground model combines color and spatial information. The application of a particle filter allows the update of the spatial information and provides a priori information about the areas to analyze in the following images, enabling an important reduction in the computational requirements and improving the segmentation results

Ensemble transcript interaction networks: A case study on Alzheimer's disease

Systems biology techniques are a topic of recent interest within the neurological field. Computational intelligence (CI) addresses this holistic perspective by means of consensus or ensemble techniques ultimately capable of uncovering new and relevant findings. In this paper, we propose the application of a CI approach based on ensemble Bayesian network classifiers and multivariate feature subset selection to induce probabilistic dependences that could match or unveil biological relationships. The research focuses on the analysis of high-throughput Alzheimer's disease (AD) transcript profiling. The analysis is conducted from two perspectives. First, we compare the expression profiles of hippocampus subregion entorhinal cortex (EC) samples of AD patients and controls. Second, we use the ensemble approach to study four types of samples: EC and dentate gyrus (DG) samples from both patients and controls. Results disclose transcript interaction networks with remarkable structures and genes not directly related to AD by previous studies. The ensemble is able to identify a variety of transcripts that play key roles in other neurological pathologies. Classical statistical assessment by means of non-parametric tests confirms the relevance of the majority of the transcripts. The ensemble approach pinpoints key metabolic mechanisms that could lead to new findings in the pathogenesis and development of AD

Evolution and treatment of vitamin B12 deficiency as a risk factor for (cognitive and functional) neurodegenerative diseases in institutionalized elderly = Evolución y tratamiento de la deficiencia de vitamina B12 como factor de riesgo de enfermedades neurodegenerativas (cognitivas y funcionales) en las personas mayores institucionalizadas.

Prevalence of vitamin B12 deficiency is very common in elderly people and can reach values as high as 40.5% of the population. It can be the result of the interaction among several factors. Vitamin B12 deficiencies have been associated with neurological, cognitive deterioration, haematological abnormalities and cardiovascular diseases that have an important influence on the health of the elderly and their quality of life. It is necessary to approach the problems arisen from the lack of data relative to them. The main objective of this thesis was to analyse the evolution of vitamin B12 status and related parameters, lipid and haematological profiles and their relationship to health risk factors, and to functional and cognitive status over one year and to determine the effect of an oral supplementation of 500 μg of cyanocobalamin for a short period of 28 days. An additional objective was to analyze the possible effects of medicine intakes on vitamin B status. Three studies were performed: a) a one year longitudinal follow-up with four measure points; b) an intervention study providing an oral liquid supplement of 500 μg of cyanocobalamin for a 28 days period; and c) analysis of the possible effect of medication intake on vitamin B status using the ATC classification of medicines. The participants for these studies were recruited from nursing homes for the elderly in the Region of Madrid. Sixty elders (mean age 84 _ 7y, 19 men and 41 women) were recruited for Study I and 64 elders (mean age 82 _ 7y, 24 men and 40 women) for Study II. For Study III, baseline data from the initially recruited participants of the first two studies were used. An informed consent was obtained from all participants or their mentors. The studies were approved by the Ethical Committee of the University of Granada. Blood samples were obtained at each examination date and were analyzed for serum cobalamin, holoTC, serum and RBC folate and total homocysteine according to laboratory standard procedures. The haematological parameters analyzed were haematocrit, haemoglobin and MCV. For the lipid profile TG, total cholesterol, LDL- and HDLcholesterol were analyzed. Anthropometric measures (BMI, skinfolds [triceps and subscapular], waist girth and waist to hip ratio), functional tests (hand grip, arm and leg strength tests, static balance) and MMSE were obtained or administered by trained personal. The vitamin B12 supplement of Study II was administered with breakfast and the medication intake was taken from the residents’ anamnesis. Data were analyzed by parametric and non-parametric statistics depending on the obtained data. Comparisons were done using the appropriate ANOVAs or non-parametric tests. Pearsons’ partial correlations with the variable “time” as control were used to define the association of the analyzed parameters. XIII The results showed that: A) Over one year, in relationship to vitamin B status, serum cobalamin decreased, serum folate and mean corpuscular volumen increased significantly and total homocysteine concentrations were stable. Regarding blood lipid profile, triglycerides increased and HDL-cholesterol decreased significantly. Regarding selected anthropometric measurements, waist circumference increased significantly. No significant changes were observed for the rest of parameters. B) Prevalence of hyperhomocysteinemia was high in the elderly studied, ranging from 60% to 90 % over the year depending on the cut-off used for the classification. LDL-cholesterol values were high, especially among women, and showed a tendency to increase over the year. Results of the balance test showed a deficiency and a tendency to decrease; this indicates that the population studied is at high risk for falls. Lower extremity muscular function was deficient and showed a tendency to decrease. A highly significant relationship was observed between the skinfold of the triceps and blood lipid profile. C) Low cobalamin concentrations correlated significantly with low MMSE scores in the elderly studied. No correlations were observed between vitamin B12 status and functional parameters. D) Regarding vitamin B12 status, holo-transcobalamin seems to be more sensitive for diagnosis; 5-10% of the elderly had a deficiency using serum cobalamin as a criterion, and 45-52% had a deficiency when using serum holotranscobalamin as a criterion. E) 500 μg of cyanocobalamin administered orally during 28 days significantly improved vitamin B12 status and significantly decreased total homocysteine concentrations in institutionalized elderly. No effect of the intervention was observed on functional and cognitive parameters. F) The relative change (%) of improvement of vitamin B12 status was higher when using serum holo-transcobalamin as a criterion than serum cobalamin. G) Antiaenemic drug intake normalized cobalamin, urologic drugs and corticosteroids serum folate, and psychoanaleptics holo-transcobalamin levels. Drugs treating pulmonary obstruction increased total homocysteine concentration significantly. H) The daily mean drug intake was 5.1. Fiftynine percent of the elderly took medication belonging to 5 or more different ATC groups. The most prevalent were psycholeptic (53%), antiacid (53%) and antithrombotic (47%) drugs.

Regularization for sparsity in statistical analysis and machine learning

Pragmatism is the leading motivation of regularization. We can understand regularization as a modification of the maximum-likelihood estimator so that a reasonable answer could be given in an unstable or ill-posed situation. To mention some typical examples, this happens when fitting parametric or non-parametric models with more parameters than data or when estimating large covariance matrices. Regularization is usually used, in addition, to improve the bias-variance tradeoff of an estimation. Then, the definition of regularization is quite general, and, although the introduction of a penalty is probably the most popular type, it is just one out of multiple forms of regularization. In this dissertation, we focus on the applications of regularization for obtaining sparse or parsimonious representations, where only a subset of the inputs is used. A particular form of regularization, L1-regularization, plays a key role for reaching sparsity. Most of the contributions presented here revolve around L1-regularization, although other forms of regularization are explored (also pursuing sparsity in some sense). In addition to present a compact review of L1-regularization and its applications in statistical and machine learning, we devise methodology for regression, supervised classification and structure induction of graphical models. Within the regression paradigm, we focus on kernel smoothing learning, proposing techniques for kernel design that are suitable for high dimensional settings and sparse regression functions. We also present an application of regularized regression techniques for modeling the response of biological neurons. Supervised classification advances deal, on the one hand, with the application of regularization for obtaining a na¨ıve Bayes classifier and, on the other hand, with a novel algorithm for brain-computer interface design that uses group regularization in an efficient manner. Finally, we present a heuristic for inducing structures of Gaussian Bayesian networks using L1-regularization as a filter. El pragmatismo es la principal motivación de la regularización. Podemos entender la regularización como una modificación del estimador de máxima verosimilitud, de tal manera que se pueda dar una respuesta cuando la configuración del problema es inestable. A modo de ejemplo, podemos mencionar el ajuste de modelos paramétricos o no paramétricos cuando hay más parámetros que casos en el conjunto de datos, o la estimación de grandes matrices de covarianzas. Se suele recurrir a la regularización, además, para mejorar el compromiso sesgo-varianza en una estimación. Por tanto, la definición de regularización es muy general y, aunque la introducción de una función de penalización es probablemente el método más popular, éste es sólo uno de entre varias posibilidades. En esta tesis se ha trabajado en aplicaciones de regularización para obtener representaciones dispersas, donde sólo se usa un subconjunto de las entradas. En particular, la regularización L1 juega un papel clave en la búsqueda de dicha dispersión. La mayor parte de las contribuciones presentadas en la tesis giran alrededor de la regularización L1, aunque también se exploran otras formas de regularización (que igualmente persiguen un modelo disperso). Además de presentar una revisión de la regularización L1 y sus aplicaciones en estadística y aprendizaje de máquina, se ha desarrollado metodología para regresión, clasificación supervisada y aprendizaje de estructura en modelos gráficos. Dentro de la regresión, se ha trabajado principalmente en métodos de regresión local, proponiendo técnicas de diseño del kernel que sean adecuadas a configuraciones de alta dimensionalidad y funciones de regresión dispersas. También se presenta una aplicación de las técnicas de regresión regularizada para modelar la respuesta de neuronas reales. Los avances en clasificación supervisada tratan, por una parte, con el uso de regularización para obtener un clasificador naive Bayes y, por otra parte, con el desarrollo de un algoritmo que usa regularización por grupos de una manera eficiente y que se ha aplicado al diseño de interfaces cerebromáquina. Finalmente, se presenta una heurística para inducir la estructura de redes Bayesianas Gaussianas usando regularización L1 a modo de filtro.

Robust regression applied to fractal/multifractal analysis.

Fractal and multifractal are concepts that have grown increasingly popular in recent years in the soil analysis, along with the development of fractal models. One of the common steps is to calculate the slope of a linear fit commonly using least squares method. This shouldn?t be a special problem, however, in many situations using experimental data the researcher has to select the range of scales at which is going to work neglecting the rest of points to achieve the best linearity that in this type of analysis is necessary. Robust regression is a form of regression analysis designed to circumvent some limitations of traditional parametric and non-parametric methods. In this method we don?t have to assume that the outlier point is simply an extreme observation drawn from the tail of a normal distribution not compromising the validity of the regression results. In this work we have evaluated the capacity of robust regression to select the points in the experimental data used trying to avoid subjective choices. Based on this analysis we have developed a new work methodology that implies two basic steps: ? Evaluation of the improvement of linear fitting when consecutive points are eliminated based on R pvalue. In this way we consider the implications of reducing the number of points. ? Evaluation of the significance of slope difference between fitting with the two extremes points and fitted with the available points. We compare the results applying this methodology and the common used least squares one. The data selected for these comparisons are coming from experimental soil roughness transect and simulated based on middle point displacement method adding tendencies and noise. The results are discussed indicating the advantages and disadvantages of each methodology.