Possible solution of some essential zero problems in compositional data analysis

One of the tantalising remaining problems in compositional data analysis lies in how to deal with data sets in which there are components which are essential zeros. By an essential zero we mean a component which is truly zero, not something recorded as zero simply because the experimental design or the measuring instrument has not been sufficiently sensitive to detect a trace of the part. Such essential zeros occur in many compositional situations, such as household budget patterns, time budgets, palaeontological zonation studies, ecological abundance studies. Devices such as nonzero replacement and amalgamation are almost invariably ad hoc and unsuccessful in such situations. From consideration of such examples it seems sensible to build up a model in two stages, the first determining where the zeros will occur and the second how the unit available is distributed among the non-zero parts. In this paper we suggest two such models, an independent binomial conditional logistic normal model and a hierarchical dependent binomial conditional logistic normal model. The compositional data in such modelling consist of an incidence matrix and a conditional compositional matrix. Interesting statistical problems arise, such as the question of estimability of parameters, the nature of the computational process for the estimation of both the incidence and compositional parameters caused by the complexity of the subcompositional structure, the formation of meaningful hypotheses, and the devising of suitable testing methodology within a lattice of such essential zero-compositional hypotheses. The methodology is illustrated by application to both simulated and real compositional data

Compositional data analysis of archaeological glass: problems and possible solutions

Presentation in CODAWORK'03, session 4: Applications to archeometry

Validation Study of the Questionnaire on School Maladjustmet Problems (QSMP)

Resumen tomado de la publicaci??n

On the way to solve lighting problems in underwater imaging

A major obstacle to processing images of the ocean floor comes from the absorption and scattering effects of the light in the aquatic environment. Due to the absorption of the natural light, underwater vehicles often require artificial light sources attached to them to provide the adequate illumination. Unfortunately, these flashlights tend to illuminate the scene in a nonuniform fashion, and, as the vehicle moves, induce shadows in the scene. For this reason, the first step towards application of standard computer vision techniques to underwater imaging requires dealing first with these lighting problems. This paper analyses and compares existing methodologies to deal with low-contrast, nonuniform illumination in underwater image sequences. The reviewed techniques include: (i) study of the illumination-reflectance model, (ii) local histogram equalization, (iii) homomorphic filtering, and, (iv) subtraction of the illumination field. Several experiments on real data have been conducted to compare the different approaches

Corporal punishment and long-term behavior problems : The moderating role of positive parenting and psychological aggression

Resumen tomado de la publicaci??n

Problems with large groups

A list of considerations on the problems with large groups. This material was sent to Debra Morris in 2007, by David Jaques, an educationist with many years' experience of working with groups.

Desarrollo de una aplicación de computador para analizar parámetros estadísticos genético-poblacionales de microsatélites en poblaciones humanas

La información y los datos genéticos que emanan hoy de las investigaciones del genoma humano demandan el desarrollo de herramientas informáticas capaces de procesar la gran cantidad de información disponible. La mayor cantidad de datos genéticos es el resultado de equipos que realizan el análisis simultáneo de cientos o miles de polimorfismos o variaciones genéticas, de nuevas técnicas de laboratorio de mayor rendimiento que, en conjunto, ofrecen una mayor disponibilidad de información en un corto espacio de tiempo. Esta problemática conduce a la necesidad de desarrollar nuevas herramientas informáticas capaces de lidiar con este mayor volumen de datos genéticos. En el caso de la genética de poblaciones, a pesar de que existen herramientas informáticas que permiten procesar y facilitar el análisis de los datos, estas tienen limitaciones como la falta de conocimiento de los usuarios de algunos lenguajes de programación para alimentar la información y otras herramientas informáticas no realizan todas las estimaciones que se requieren y otros presentan limitaciones en cuanto al número de datos que pueden incorporar o manejar. En algunos casos hay redundancia al tener que usarse dos o más herramientas para poder procesar un conjunto de datos de información genética. El presente trabajo tiene por objetivo el desarrollo de una herramienta informática basada en aplicaciones de computador comunes, en este caso Microsoft Excel® y que resuelva todos los problemas y las limitaciones descritas antes. El desarrollo del conjunto de subprogramas que constituyen a Lustro; permiten superar lo anterior, presentar los resultados en un ambiente sencillo, conocido y fácil de operar, simplificando de esta forma el proceso de adaptación del usuario del programa, sin entrenamiento previo, obteniéndose en corto tiempo el procesamiento de la información genética de interés.

Introduction to JavaScript Programming

These are the resources for an introductory lecture in JavaScript programming. Exercises are provided to practice simple JavaScript programming, including a template for a DHTML implementation of Conway's Game of Life (with encrypted solution).

Mathematical Programming

Exam questions and solutions for a third year mathematical programming course.

Programming & Software

An overview of programming and software development.

Programming Principles: Starting Out

In this lecture we describe the structure of the Programming Principles course at Southampton, look at the definitions and paradigms of programming, and take a look ahead to the key things that we will be covering in the weeks ahead.

Programming Principles: Introduction to Java

In this lecture we look at key concepts in Java: how to write, compile and run Java programs, define a simple class, create a main method, and use if/else structures to define behaviour.

Programming Principles: Variables, Primitives, Objects and Scope

In this session we look more closely at the way that Java deals with variables, and in particular with the differences between primitives (basic types like int and char) and objects. We also take an initial look at the scoping rules in Java, which dictate the visibility of variables in your program

Programming Principles: Computational Thinking

In this session we look at how to think systematically about a problem and create a solution. We look at the definition and characteristics of an algorithm, and see how through modularisation and decomposition we can then choose a set of methods to create. We also compare this somewhat procedural approach, with the way that design works in Object Oriented Systems,

Programming Principles: Methods

In this session we look at how to create more powerful objects through more powerful methods. We look at parameters and call by value vs. call by reference; return types; and overloading.