User’s Guide to ADMB2R: A Set of AD Model Builder Output Routines Compatible with the R Statistics Language

ADMB2R is a collection of AD Model Builder routines for saving complex data structures into a file that can be read in the R statistics environment with a single command.1 ADMB2R provides both the means to transfer data structures significantly more complex than simple tables, and an archive mechanism to store data for future reference. We developed this software because we write and run computationally intensive numerical models in Fortran, C++, and AD Model Builder. We then analyse results with R. We desired to automate data transfer to speed diagnostics during working-group meetings. We thus developed the ADMB2R interface to write an R data object (of type list) to a plain-text file. The master list can contain any number of matrices, values, dataframes, vectors or lists, all of which can be read into R with a single call to the dget function. This allows easy transfer of structured data from compiled models to R. Having the capacity to transfer model data, metadata, and results has sharply reduced the time spent on diagnostics, and at the same time, our diagnostic capabilities have improved tremendously. The simplicity of this interface and the capabilities of R have enabled us to automate graph and table creation for formal reports. Finally, the persistent storage in files makes it easier to treat model results in analyses or meta-analyses devised months—or even years—later. We offer ADMB2R to others in the hope that they will find it useful. (PDF contains 30 pages)

User’s Guide to C2R: A Set of C Language Output Routines Compatible with the R Statistics Language

C2R is a collection of C routines for saving complex data structures into a file that can be read in the R statistics environment with a single command.1 C2R provides both the means to transfer data structures significantly more complex than simple tables, and an archive mechanism to store data for future reference. We developed this software because we write and run computationally intensive numerical models in Fortran, C++, and AD Model Builder. We then analyse results with R. We desired to automate data transfer to speed diagnostics during working-group meetings. We thus developed the C2R interface to write an R data object (of type list) to a plain-text file. The master list can contain any number of matrices, values, dataframes, vectors or lists, all of which can be read into R with a single call to the dget function. This allows easy transfer of structured data from compiled models to R. Having the capacity to transfer model data, metadata, and results has sharply reduced the time spent on diagnostics, and at the same time, our diagnostic capabilities have improved tremendously. The simplicity of this interface and the capabilities of R have enabled us to automate graph and table creation for formal reports. Finally, the persistent storage in files makes it easier to treat model results in analyses or meta-analyses devised months—or even years—later. We offer C2R to others in the hope that they will find it useful. (PDF contains 27 pages)

User’s Guide to For2R: A Module of Fortran 95 Output Routines Compatible with the R Statistics Language

For2R is a collection of Fortran routines for saving complex data structures into a file that can be read in the R statistics environment with a single command.1 For2R provides both the means to transfer data structures significantly more complex than simple tables, and an archive mechanism to store data for future reference. We developed this software because we write and run computationally intensive numerical models in Fortran, C++, and AD Model Builder. We then analyse results with R. We desired to automate data transfer to speed diagnostics during working-group meetings. We thus developed the For2R interface to write an R data object (of type list) to a plain-text file. The master list can contain any number of matrices, values, dataframes, vectors or lists, all of which can be read into R with a single call to the dget function. This allows easy transfer of structured data from compiled models to R. Having the capacity to transfer model data, metadata, and results has sharply reduced the time spent on diagnostics, and at the same time, our diagnostic capabilities have improved tremendously. The simplicity of this interface and the capabilities of R have enabled us to automate graph and table creation for formal reports. Finally, the persistent storage in files makes it easier to treat model results in analyses or meta-analyses devised months—or even years—later. We offer For2R to others in the hope that they will find it useful. (PDF contains 31 pages)

Kalman Filtering in R

Support in R for state space estimation via Kalman filtering was limited to one package, until fairly recently. In the last five years, the situation has changed with no less than four additional packages offering general implementations of the Kalman filter, including in some cases smoothing, simulation smoothing and other functionality. This paper reviews some of the offerings in R to help the prospective user to make an informed choice.

Introducción al entorno R

R puede entenderse como un lenguaje de programación, como un potente software de análisis estadísticos o incluso como un generador de gráficos. Cualquiera de las tres acepciones es compatible con una definición de R. Estas páginas ofrecen al lector interesado y no iniciado en programación, los conceptos básicos y necesarios de la sintaxis de R que le permitirán trabajar en un entorno pensado para su uso con interfaces de códigos. Si bien es cierto que existen interfaces gráficas (R Commander) que facilitan el uso de R como software para el análisis de datos, no es menos cierto que la adquisición de destrezas en el manejo de unas normas de sintaxis básicas permitirán al usuario de R beneficiarse aún más de la potencia y de las ventajas que ofrece este entorno.

Psicometría. Conceptos básicos y aplicaciones prácticas con R Commander

El estudio de una escala de actitudes, un inventario de personalidad o una prueba de aptitud numérica comprende un conjunto de análisis cuya finalidad es garantizar la fiabilidad de los datos y la validez de las inferencias derivadas de ellos. El corpus que da sustento teórico, aplicado y ético a tales menesteres se cimienta sobre la disciplina denominada psicometría. La psicometría se ocupa del proceso de construcción y validación de escalas cuyo objetivo es medir variables de naturaleza psicológica. El libro trata en profundidad y de forma actualizada los dos grandes temas de la medición empírica, la fiabilidad y las validez, así como la tecnología implicada en su análisis: regresión simple y múltiple, análisis factorial, equiparación de puntuaciones, funcionamiento diferencial del ítem, análisis de varianza. Todo ello se aborda desde una doble perspectiva teórica y aplicada. La primera aporta las bases necesarias para su comprensión y la segunda contribuye a su asimilación por medio de un ejemplo real que se ilustra con la ayuda del mejor software disponible para el análisis de datos y la psicometría, R.

Software como un Servicio: Solución Business Intelligence

El propóosito del proyecto aquíı descrito radica en, por una parte, sentar una base de un sistema de Business Inteligence adaptable a diversos casos de negocio, y por otra, diseñar e implementar una solución completa para una empresa especíıfica fácilmente adaptable a otro caso, incluyendo desde los procesos de Extracción, Transformación y Carga, pasando por el data warehouse hasta el Business Analysis y la Minería de Datos.

Dividing population genetic distance data with the software Partitioning Optimization with Restricted Growth Strings (PORGS): an application for Chinook salmon (Oncorhynchus tshawytscha), Vancouver Island, British Columbia

A new method of finding the optimal group membership and number of groupings to partition population genetic distance data is presented. The software program Partitioning Optimization with Restricted Growth Strings (PORGS), visits all possible set partitions and deems acceptable partitions to be those that reduce mean intracluster distance. The optimal number of groups is determined with the gap statistic which compares PORGS results with a reference distribution. The PORGS method was validated by a simulated data set with a known distribution. For efficiency, where values of n were larger, restricted growth strings (RGS) were used to bipartition populations during a nested search (bi-PORGS). Bi-PORGS was applied to a set of genetic data from 18 Chinook salmon (Oncorhynchus tshawytscha) populations from the west coast of Vancouver Island. The optimal grouping of these populations corresponded to four geographic locations: 1) Quatsino Sound, 2) Nootka Sound, 3) Clayoquot +Barkley sounds, and 4) southwest Vancouver Island. However, assignment of populations to groups did not strictly reflect the geographical divisions; fish of Barkley Sound origin that had strayed into the Gold River and close genetic similarity between transferred and donor populations meant groupings crossed geographic boundaries. Overall, stock structure determined by this partitioning method was similar to that determined by the unweighted pair-group method with arithmetic averages (UPGMA), an agglomerative clustering algorithm.

Utilização do software GRASP para gerar arquivo de coordenadas com valores de potencial eletrostático.

Com o intuito de disponibilizar um banco de dados de valores de potencial eletrostático para todas as estruturas de proteínas depositadas no PDB, foi utilizado o programa GRASP (Graphical Representation and Analysis of Structural Properties) (Nicholls et al., 1991) para geração deste banco de dados.

Arquitetura de software para a manutenção de dados da Agência de Informação Embrapa.

A agencia de informação Embrapa disponibiliza na internet informação qualificada e organizada e, muitas vezes, também aquelas geradas pela própria Embrapa. As soluções de software esposta neste trabalho são dirigidas ao gerenciamento dessas informações, que são armazenadas em base de dados centralizada e atualizada via internet por aplicativos deste sistema. O objetivo de apresentar essas soluções é contribuir para o desenvolvimento de sistemas com orientação metodológica similar. Este sistema teve como principal identificação de requisitos as falhas existentes na primeira versão do mesmo, que foi orientada exclusivamente para manipulação de dados formatados em XML. A nova versão traz uma arquitetura baseada nas orientações Java 2 Enterprise Editon (J2EE): modelo em camadas (orientação Model View Controler-MVC), uso de containers e sistema gerenciador de banco de dados. O resultado é um sistema mais robusto em seu todo, além das melhorias de manutenabilidade. Termos para indexação:J2EE, XML, PDOM, Model view controller- MVC, Oracle.

Cálculo de possíveis contatos atômicos internos a uma proteína ou entre proteínas no software SMS.

Contatos interatômicos são definidos no contexto deste trabalho como as forças de atração ou de repulsão existentes entre átomos distintos.

Uma proposta de plataforma de software para integração e interoperabilidade de serviços Web - Webagritec: estudo de caso.

Este trabalho tem por finalidade apresentar os resultados obtidos no contexto do projeto de pesquisa, cujo objetivo foi definir uma infraestrutura de software para implantação de um portal de integração e interoperabilidade de serviços desenvolvidos pela Embrapa Informática Agropecuária denominado WebAgritec.