Time-series regression models to study the short-term effects of environmental factors on health

Time series regression models are especially suitable in epidemiology for evaluating short-term effects of time-varying exposures on health. The problem is that potential for confounding in time series regression is very high. Thus, it is important that trend and seasonality are properly accounted for. Our paper reviews the statistical models commonly used in time-series regression methods, specially allowing for serial correlation, make them potentially useful for selected epidemiological purposes. In particular, we discuss the use of time-series regression for counts using a wide range Generalised Linear Models as well as Generalised Additive Models. In addition, recently critical points in using statistical software for GAM were stressed, and reanalyses of time series data on air pollution and health were performed in order to update already published. Applications are offered through an example on the relationship between asthma emergency admissions and photochemical air pollutants

Multivariate ARIMA Compositional Time Series Analysis

A compositional time series is obtained when a compositional data vector is observed at different points in time. Inherently, then, a compositional time series is a multivariate time series with important constraints on the variables observed at any instance in time. Although this type of data frequently occurs in situations of real practical interest, a trawl through the statistical literature reveals that research in the field is very much in its infancy and that many theoretical and empirical issues still remain to be addressed. Any appropriate statistical methodology for the analysis of compositional time series must take into account the constraints which are not allowed for by the usual statistical techniques available for analysing multivariate time series. One general approach to analyzing compositional time series consists in the application of an initial transform to break the positive and unit sum constraints, followed by the analysis of the transformed time series using multivariate ARIMA models. In this paper we discuss the use of the additive log-ratio, centred log-ratio and isometric log-ratio transforms. We also present results from an empirical study designed to explore how the selection of the initial transform affects subsequent multivariate ARIMA modelling as well as the quality of the forecasts

Compositional Time Series: An Application

The composition of the labour force is an important economic factor for a country. Often the changes in proportions of different groups are of interest. I this paper we study a monthly compositional time series from the Swedish Labour Force Survey from 1994 to 2005. Three models are studied: the ILR-transformed series, the ILR-transformation of the compositional differenced series of order 1, and the ILRtransformation of the compositional differenced series of order 12. For each of the three models a VAR-model is fitted based on the data 1994-2003. We predict the time series 15 steps ahead and calculate 95 % prediction regions. The predictions of the three models are compared with actual values using MAD and MSE and the prediction regions are compared graphically in a ternary time series plot. We conclude that the first, and simplest, model possesses the best predictive power of the three models

La Enseñanza virtual cómo método para que el estudiante asimile conceptos de matemáticas empresariales

La implantación del Sistema Europeo de Transferencia de Créditos (ECTS) no se reduce a un mero cambio en la forma de computar la dedicación del estudiante a cada asignatura, sino que debe llevar aparejada una renovación de la metodología docente. Los métodos más tradicionales deben sustituirse por otros que conviertan al alumno en el verdadero protagonista del proceso de enseñanza-aprendizaje y cuyos sistemas de evaluación tengan en cuenta no sólo la adquisición de conocimientos, sino también la de destrezas genéricas así como de otras específicas de la titulación cursada e incluso de la asignatura. En ese sentido, la aplicación de las nuevas tecnologías a los procesos de enseñanza-aprendizaje puede ser un método docente innovador que resulte de gran utilidad para conseguir algunos de los objetivos que se plantean en la adaptación al ECTS; en concreto, facilitar al estudiante la adquisición de unos conocimientos mínimos y de habilidades, capacidades, aptitudes y destrezas para que sea capaz de enfrentarse a nuevos problemas y adquirir nuevos conocimientos. En la asignatura Matemáticas, que se imparte en primer curso de la Licenciatura en Administración y Dirección de Empresas y también en primer curso de las Licenciaturas conjuntas en Derecho y en Administración y Dirección de Empresas de la Universidad Pablo de Olavide, se han combinado, durante el curso 2007/2008, las clases presenciales con la docencia virtual. Se ha intentado con ello que el estudiante adquiera una mayor motivación e interés por la asignatura, así como que asimile con mayor facilidad los conceptos básicos. En este trabajo, exponemos las principales características de nuestra experiencia, mostrando el diseño del curso y analizando la aceptación que ha tenido entre nuestros estudiantes