Lognormal and gamma mixed negative binomial regression

In regression analysis of counts, a lack of simple and efficient algorithms for posterior computation has made Bayesian approaches appear unattractive and thus underdeveloped. We propose a lognormal and gamma mixed negative binomial (NB) regression model for counts, and present efficient closed-form Bayesian inference; unlike conventional Poisson models, the proposed approach has two free parameters to include two different kinds of random effects, and allows the incorporation of prior information, such as sparsity in the regression coefficients. By placing a gamma distribution prior on the NB dispersion parameter r, and connecting a log-normal distribution prior with the logit of the NB probability parameter p, efficient Gibbs sampling and variational Bayes inference are both developed. The closed-form updates are obtained by exploiting conditional conjugacy via both a compound Poisson representation and a Polya-Gamma distribution based data augmentation approach. The proposed Bayesian inference can be implemented routinely, while being easily generalizable to more complex settings involving multivariate dependence structures. The algorithms are illustrated using real examples. Copyright 2012 by the author(s)/owner(s).

The effect of differences in methodology among some recent applications of shearing quotients.

A shearing quotient (SQ) is a way of quantitatively representing the Phase I shearing edges on a molar tooth. Ordinary or phylogenetic least squares regression is fit to data on log molar length (independent variable) and log sum of measured shearing crests (dependent variable). The derived linear equation is used to generate an 'expected' shearing crest length from molar length of included individuals or taxa. Following conversion of all variables to real space, the expected value is subtracted from the observed value for each individual or taxon. The result is then divided by the expected value and multiplied by 100. SQs have long been the metric of choice for assessing dietary adaptations in fossil primates. Not all studies using SQ have used the same tooth position or crests, nor have all computed regression equations using the same approach. Here we focus on re-analyzing the data of one recent study to investigate the magnitude of effects of variation in 1) shearing crest inclusion, and 2) details of the regression setup. We assess the significance of these effects by the degree to which they improve or degrade the association between computed SQs and diet categories. Though altering regression parameters for SQ calculation has a visible effect on plots, numerous iterations of statistical analyses vary surprisingly little in the success of the resulting variables for assigning taxa to dietary preference. This is promising for the comparability of patterns (if not casewise values) in SQ between studies. We suggest that differences in apparent dietary fidelity of recent studies are attributable principally to tooth position examined.

A dimensionless number for understanding the evolutionary dynamics of antigenically variable RNA viruses.

Antigenically variable RNA viruses are significant contributors to the burden of infectious disease worldwide. One reason for their ubiquity is their ability to escape herd immunity through rapid antigenic evolution and thereby to reinfect previously infected hosts. However, the ways in which these viruses evolve antigenically are highly diverse. Some have only limited diversity in the long-run, with every emergence of a new antigenic variant coupled with a replacement of the older variant. Other viruses rapidly accumulate antigenic diversity over time. Others still exhibit dynamics that can be considered evolutionary intermediates between these two extremes. Here, we present a theoretical framework that aims to understand these differences in evolutionary patterns by considering a virus's epidemiological dynamics in a given host population. Our framework, based on a dimensionless number, probabilistically anticipates patterns of viral antigenic diversification and thereby quantifies a virus's evolutionary potential. It is therefore similar in spirit to the basic reproduction number, the well-known dimensionless number which quantifies a pathogen's reproductive potential. We further outline how our theoretical framework can be applied to empirical viral systems, using influenza A/H3N2 as a case study. We end with predictions of our framework and work that remains to be done to further integrate viral evolutionary dynamics with disease ecology.

Physical Activity, Central Adiposity, and Functional Limitations in Community-Dwelling Older Adults.

BACKGROUND AND PURPOSE: Obesity and physical inactivity are independently associated with physical and functional limitations in older adults. The current study examines the impact of physical activity on odds of physical and functional limitations in older adults with central and general obesity. METHODS: Data from 6279 community-dwelling adults aged 60 years or more from the Health and Retirement Study 2006 and 2008 waves were used to calculate prevalence and odds of physical and functional limitation among obese older adults with high waist circumference (waist circumference ≥88 cm in females and ≥102 cm in males) who were physically active versus inactive (engaging in moderate/vigorous activity less than once per week). Logistic regression models were adjusted for age, sex, race/ethnicity, education, smoking status, body mass index, and number of comorbidities. RESULTS: Physical activity was associated with lower odds of physical and functional limitations among older adults with high waist circumference (odds ratio [OR], 0.59; confidence interval [CI], 0.52-0.68, for physical limitations; OR, 0.52; CI, 0.44-0.62, for activities of daily living; and OR, 0.44; CI, 0.39-0.50, for instrumental activities of daily living). CONCLUSIONS: Physical activity is associated with significantly lower odds of physical and functional limitations in obese older adults regardless of how obesity is classified. Additional research is needed to determine whether physical activity moderates long-term physical and functional limitations.

Are the reference values of B cell subpopulations used in adults for classification of common variable immunodeficiencies appropriate for children?

Detailed phenotypic characterization of B cell subpopulations is of utmost importance for the diagnosis and management of humoral immunodeficiencies, as they are used for classification of common variable immunodeficiencies. Since age-specific reference values remain scarce in the literature, we analysed by flow cytometry the proportions and absolute values of total, memory, switched memory and CD21(-/low) B cells in blood samples from 168 healthy children (1 day to 18 years) with special attention to the different subpopulations of CD21(low) B cells. The percentages of total memory B cells and their subsets significantly increased up to 5-10 years. In contrast, the percentages of immature CD21(-) B cells and of immature transitional CD21(low)CD38(hi) B cells decreased progressively with age, whereas the percentage of CD21(low) CD38(low) B cells remained stable during childhood. Our data stress the importance of age-specific reference values for the correct interpretation of B cell subsets in children as a diagnostic tool in immunodeficiencies.

Promedio bayesiano de modelos para la predicción del consumo máximo de oxígeno en deportistas con datos de no-ejercicio

Históricamente, los modelos de no-ejercicio para predecir el consumo máximo de oxígeno (VO2max) han sido construidos mediante regresión lineal frecuentista, usando técnicas estándar de selección de modelos. Sin embargo, existe incertidumbre acerca de la estructura estadística en el proceso de selección del modelo. En este estudio se propuso construir un modelo de no-ejercicio para predecir el VO2max en deportistas orientados al rendimiento, considerando la incertidumbre de modelo a través del Promedio Bayesiano de Modelos (BMA). Un objetivo adicional fue comparar la performance predictiva del BMA con las de los modelos derivados de varias técnicas frecuentistas usuales de selección de variables. Con tal fin, se implementó un submuestreo aleatorio estratificado repetido. Los datos incluyeron observaciones de la variable respuesta (en L·min-1), así como registros de Género, Deporte, Edad, Peso, Talla e Índice de masa corporal (BMI) (Edad = 22.1 ± 4.9 años, media ± SD; n = 272). Se propuso una clasificación de deportes con el objetivo de incluirla dentro del proceso de construcción del modelo: Combate, Juego, Resistencia 1 y Resistencia 2. El enfoque BMA se implementó en base a dos métodos: Occam's window y Composición de Modelo mediante el método de Monte Carlo con Cadenas de Markov (MC²). Se observaron discrepancias en la selección de variables entre los procedimientos frecuentistas. Ambos métodos de BMA produjeron resultados muy similares. Los modelos que incluyeron Género y las variables dummies para Resistencia 1 y Resistencia 2 acumularon virtualmente toda la probabilidad de modelo a posteriori. El Peso fue el predictor continuo con la más alta probabilidad de inclusión a posteriori (menor a 0.8). Las combinaciones de variables que involucraron predictores con un alto nivel de multicolinealidad fueron desacreditadas. Los modelos con sustancial contribución para el BMA presentaron un ajuste apreciable (R² ajustado menor a 0.8). Entre los modelos seleccionados por estrategias frecuentistas, el obtenido mediante el método de regresión por pasos (Stepwise regression method) con alfa igual a 0.05 fue el más respaldado por los datos, en términos de probabilidad de modelo a posteriori. En concordancia con la literatura, el BMA tuvo mejor performance predictiva de los datos fuera de la muestra que los modelos seleccionados por técnicas frecuentistas, medida por la cobertura del intervalo de predicción de 90 por ciento. La clasificación de deportes reveló resultados consistentes.

Desarrollo instrumental y medición de la resistencia a la rotura de costras de suelo

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El dominio de la variable: variable didáctica en el álgebra escolar

En el análisis del discurso matemático manifiesto en un texto de álgebra escolar, hemos encontrado que el dominio de la variable es un concepto presente desde la aparición de las expresiones generalizadoras de operaciones, relaciones y propiedades de los números reales, que tan sólo se explicita en el estudio del álgebra de las expresiones algebraicas. Este concepto, junto con el de conjunto de referencia de una expresión y con el de conjunto solución, juega un papel protagónico en diferentes contextos del álgebra escolar, que le permiten configurarse como una variable didáctica imprescindible en la significación de muchos otros conceptos algebraicos.

Desarrollo del pensamiento covariacional en un ambiente gráfico dinámico. Hacia una génesis instrumental

La tecnología puede resultar un recurso didáctico para que los estudiantes examinen situaciones y problemas desde diversos ángulos, específicamente, el uso de software dinámico ofrece un medio útil para que ellos visualicen, exploren y construyan relaciones matemáticas. Estos apoyos modifican tan fuertemente el medio ambiente de trabajo que no basta con adaptar situaciones matemáticas clásicas, hay que concebir nuevas situaciones que tomen en consideración las potencialidades y las restricciones de la tecnología. Esto ha llevado a la creación de una génesis instrumental que estudia la construcción hecha por el estudiante cuando interactúa con un artefacto, convirtiéndolo en instrumento, a través de un proceso, de manera tal que se lo apropia y lo hace parte de su actividad matemática, actividad que en esta investigación está relacionada con el desarrollo del pensamiento covariacional.

La construcción social de la noción de variable

Este documento centra su atención en la noción de variable como elemento básico de la construcción de conceptos relacionados a fenómenos de variación y cambio. Partimos de que la variable no es una idea construida como un objeto o proceso aislado, sino que surge necesariamente de la relación de al menos dos entidades cambiantes que en la mayoría de los casos una de ellas es la variable tiempo. Pretendemos realizar el estudio de la variable desde diferentes dimensiones: la epistemológica, la cognitiva, la didáctica y la sociocultural, para poder tener elementos que nos permitan determinar qué procesos favorecen la construcción de esta noción y asimismo realizar su caracterización.

Acerca de la enseñanza de inecuaciones de una variable

En el artículo se exponen dos métodos de resolución de inecuaciones. Se comparan desde varios puntos de vista y se comentan algunos aspectos del trabajo realizado a partir de 1983 en la enseñanza de dicho tópico en la facultad de ciencias de la Universidad Central de Venezuela.

Performance analysis of a register insertion ring with a variable size buffer

There has been a recent revival of interest in the register insertion (RI) protocol because of its high throughput and low delay characteristics. Several variants of the protocol have been investigated with a view to integrating voice and data applications on a single local area network (LAN). In this paper the performance of an RI ring with a variable size buffer is studied by modelling and simulation. The chief advantage of the proposed scheme is that an efficient but simple bandwidth allocation scheme is easily incorporated. Approximate formulas are derived for queue lengths, queueing times, and total end-to-end transfer delays. The results are compared with previous analyses and with simulation estimates. The effectiveness of the proposed protocol in ensuring fairness of access under conditions of heavy and unequal loading is investigated.

Support vector machines for regression and applications to software quality prediction

Software metrics are the key tool in software quality management. In this paper, we propose to use support vector machines for regression applied to software metrics to predict software quality. In experiments we compare this method with other regression techniques such as Multivariate Linear Regression, Conjunctive Rule and Locally Weighted Regression. Results on benchmark dataset MIS, using mean absolute error, and correlation coefficient as regression performance measures, indicate that support vector machines regression is a promising technique for software quality prediction. In addition, our investigation of PCA based metrics extraction shows that using the first few Principal Components (PC) we can still get relatively good performance.

Variable frequency microwave curing of polymer materials in microelectronics packaging applications

The use of variable frequency microwave technology in curing of polymer materials used in microelectronics applications is discussed. A revolutionary open-ended microwave curing system is outlined and assessed using experimental and numerical approaches. Experimental and numerical results are presented, demonstrating the feasibility of the system

Numerical simulation of encapsulant curing within a variable frequency microwave processing system

Curing of encapsulant material in a simplified microelectronics package using an open oven Variable Frequency Microwave (VFM) system is numerically simulated using a coupled solver approach. A numerical framework capable of simulating electromagnetic field distribution within the oven system, plus heat transfer, cure rate, degree of cure and thermally induced stresses within the encapsulant material is presented. The discrete physical processes have been integrated into a fully coupled solution, enabling usefully accurate results to be generated. Numerical results showing the heating and curing of the encapsulant material have been obtained and are presented in this contribution. The requirement to capture inter-process coupling and the variation in dielectric and thermophysical material properties is discussed and illustrated with simulation results.