899 resultados para ree software environment for statistical computing and graphics R


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2010 Mathematics Subject Classification: 62J99.

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The correlated probit model is frequently used for multiple ordered data since it allows to incorporate seamlessly different correlation structures. The estimation of the probit model parameters based on direct maximization of the limited information maximum likelihood is a numerically intensive procedure. We propose an extension of the EM algorithm for obtaining maximum likelihood estimates for a correlated probit model for multiple ordinal outcomes. The algorithm is implemented in the free software environment for statistical computing and graphics R. We present two simulation studies to examine the performance of the developed algorithm. We apply the model to data on 121 women with cervical or endometrial cancer. Patients developed normal tissue reactions as a result of post-operative external beam pelvic radiotherapy. In this work we focused on modeling the effects of a genetic factor on early skin and early urogenital tissue reactions and on assessing the strength of association between the two types of reactions. We established that there was an association between skin reactions and polymorphism XRCC3 codon 241 (C>T) (rs861539) and that skin and urogenital reactions were positively correlated. ACM Computing Classification System (1998): G.3.

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Stratigraphic Columns (SC) are the most useful and common ways to represent the eld descriptions (e.g., grain size, thickness of rock packages, and fossil and lithological components) of rock sequences and well logs. In these representations the width of SC vary according to the grain size (i.e., the wider the strata, the coarser the rocks (Miall 1990; Tucker 2011)), and the thickness of each layer is represented at the vertical axis of the diagram. Typically these representations are drawn 'manually' using vector graphic editors (e.g., Adobe Illustrator®, CorelDRAW®, Inskape). Nowadays there are various software which automatically plot SCs, but there are not versatile open-source tools and it is very di cult to both store and analyse stratigraphic information. This document presents Stratigraphic Data Analysis in R (SDAR), an analytical package1 designed for both plotting and facilitate the analysis of Stratigraphic Data in R (R Core Team 2014). SDAR, uses simple stratigraphic data and takes advantage of the exible plotting tools available in R to produce detailed SCs. The main bene ts of SDAR are: (i) used to generate accurate and complete SC plot including multiple features (e.g., sedimentary structures, samples, fossil content, color, structural data, contacts between beds), (ii) developed in a free software environment for statistical computing and graphics, (iii) run on a wide variety of platforms (i.e., UNIX, Windows, and MacOS), (iv) both plotting and analysing functions can be executed directly on R's command-line interface (CLI), consequently this feature enables users to integrate SDAR's functions with several others add-on packages available for R from The Comprehensive R Archive Network (CRAN).

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A lightweight Java application suite has been developed and deployed allowing collaborative learning between students and tutors at remote locations. Students can engage in group activities online and also collaborate with tutors. A generic Java framework has been developed and applied to electronics, computing and mathematics education. The applications are respectively: (a) a digital circuit simulator, which allows students to collaborate in building simple or complex electronic circuits; (b) a Java programming environment where the paradigm is behavioural-based robotics, and (c) a differential equation solver useful in modelling of any complex and nonlinear dynamic system. Each student sees a common shared window on which may be added text or graphical objects and which can then be shared online. A built-in chat room supports collaborative dialogue. Students can work either in collaborative groups or else in teams as directed by the tutor. This paper summarises the technical architecture of the system as well as the pedagogical implications of the suite. A report of student evaluation is also presented distilled from use over a period of twelve months. We intend this suite to facilitate learning between groups at one or many institutions and to facilitate international collaboration. We also intend to use the suite as a tool to research the establishment and behaviour of collaborative learning groups. We shall make our software freely available to interested researchers.

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Examples of compositional data. The simplex, a suitable sample space for compositional data and Aitchison's geometry. R, a free language and environment for statistical computing and graphics

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Examples of compositional data. The simplex, a suitable sample space for compositional data and Aitchison's geometry. R, a free language and environment for statistical computing and graphics

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R from http://www.r-project.org/ is ‘GNU S’ – a language and environment for statistical computing and graphics. The environment in which many classical and modern statistical techniques have been implemented, but many are supplied as packages. There are 8 standard packages and many more are available through the cran family of Internet sites http://cran.r-project.org . We started to develop a library of functions in R to support the analysis of mixtures and our goal is a MixeR package for compositional data analysis that provides support for operations on compositions: perturbation and power multiplication, subcomposition with or without residuals, centering of the data, computing Aitchison’s, Euclidean, Bhattacharyya distances, compositional Kullback-Leibler divergence etc. graphical presentation of compositions in ternary diagrams and tetrahedrons with additional features: barycenter, geometric mean of the data set, the percentiles lines, marking and coloring of subsets of the data set, theirs geometric means, notation of individual data in the set . . . dealing with zeros and missing values in compositional data sets with R procedures for simple and multiplicative replacement strategy, the time series analysis of compositional data. We’ll present the current status of MixeR development and illustrate its use on selected data sets

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Protective factors are neglected in risk assessment in adult psychiatric and criminal justice populations. This review investigated the predictive efficacy of selected tools that assess protective factors. Five databases were searched using comprehensive terms for records up to June 2014, resulting in 17 studies (n = 2,198). Results were combined in a multilevel meta-analysis using the R (R Core Team, R: A Language and Environment for Statistical Computing, Vienna, Austria: R Foundation for Statistical Computing, 2015) metafor package (Viechtbauer, Journal of Statistical Software, 2010, 36, 1). Prediction of outcomes was poor relative to a reference category of violent offending, with the exception of prediction of discharge from secure units. There were no significant differences between the predictive efficacy of risk scales, protective scales, and summary judgments. Protective factor assessment may be clinically useful, but more development is required. Claims that use of these tools is therapeutically beneficial require testing.

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The analysis of rockfall characteristics and spatial distribution is fundamental to understand and model the main factors that predispose to failure. In our study we analysed LiDAR point clouds aiming to: (1) detect and characterise single rockfalls; (2) investigate their spatial distribution. To this end, different cluster algorithms were applied: 1a) Nearest Neighbour Clutter Removal (NNCR) in combination with the Expectation?Maximization (EM) in order to separate feature points from clutter; 1b) a density based algorithm (DBSCAN) was applied to isolate the single clusters (i.e. the rockfall events); 2) finally we computed the Ripley's K-function to investigate the global spatial pattern of the extracted rockfalls. The method allowed proper identification and characterization of more than 600 rockfalls occurred on a cliff located in Puigcercos (Catalonia, Spain) during a time span of six months. The spatial distribution of these events proved that rockfall were clustered distributed at a welldefined distance-range. Computations were carried out using R free software for statistical computing and graphics. The understanding of the spatial distribution of precursory rockfalls may shed light on the forecasting of future failures.

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Since 1991 Colombia has had a market-determined Peso - US Dollar Nominal Exchange Rate (NER), after more than 20 years of controlled and multiple exchange rates. The behavior (revaluation / devaluation) of the NER is constantly reported in news, editorials and op-eds of major newspapers of the nation with particular attention to revaluation. The uneven reporting of revaluation episodes can be explained by the existence of an interest group particulary affected by revaluation, looking to increase awareness and sympathy for help from public institutions. Using the number of news and op-eds from a major Colombian newspaper, it is shown that there is an over-reporting of revaluation episodes in contrast to devaluation ones. Secondly, using text analysis upon the content of the news, it is also shown that the words devaluation and revaluation are far apart in the distribution of words within the news; and revaluation is highly correlated with words related to: public institutions, exporters and the need of assistance. Finally it is also shown that the probability of the central bank buying US dollars to lessen revaluation effects increases with the number of news; even though the central bank allegedly intervenes in the exchange rate market only to tame volatility or accumulate international reserves.

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Introducción: La enfermedad cardiovascular es la principal causa de muerte a nivel mundial, afectando principalmente la salud pública de países pobres con economías emergentes. La transición epidemiológica en Colombia ha incrementado la proporción de pacientes ancianos con enfermedad cardiovascular y que requieren cirugía cardíaca. Sin embargo, no existe consenso sobre la conducta para la selección de pacientes añosos para este tipo de intervenciones. El objetivo de este estudio fue definir el riesgo mortalidad asociado a cirugía cardíaca en este grupo de pacientes, basados en una revisión sistemática de la literatura. Materiales y Métodos: Se diseñó una revisión sistemática empleando las plataformas PubMed (Medline), EBSCO Discovery Service, Ovid SP-EBMR, Sciverse y MDConsult. Los términos de búsqueda fueron “Aged”, “Cardiac surgery” and “Mortality”, conjugados de acuerdo con el lenguaje de cada buscador. Las publicaciones fueron seleccionadas por consenso. Los resultados se analizaron en un modelo de Mantel-Haenszel. Resultados: La búsqueda arrojó un total de 8.565 publicaciones. Los datos analizados en el modelo incluyeron 81.547 pacientes (7.855 octogenarios y 73.692 más jóvenes). El riesgo de mortalidad asociado a cirugía cardíaca en octogenarios fue de 125% (OR=2,35, IC 95% [2,15 - 2,57]). Discusión: El sometimiento de pacientes octogenarios a cirugías cardíacas mayores es una decisión que requiere un juicio clínico minucioso en el que es importante destacar que la probabilidad de un resultado francamente desfavorable es alta. Se necesitan más estudios diseñados que permitan aumentar la solidez de la evidencia actual en cuanto al riesgo aquí encontrado.

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Introducción: el lupus eritematoso sistémico (LES) es considerado una enfermedad de alto costo. La expresión clínica de la enfermedad depende de la ubicación geografía y la etnicidad. El objetivo de este estudio fue el calcular los costos ambulatorios relacionado al LES en una cohorte colombiana, identificar los predictores de costos y comparar nuestro resultados con otras poblaciones. Métodos: Se realizó una aproximación de tipo prevalencia en 100 pacientes LES en quienes se evaluaron los costos directos médicos, directos no médicos, indirectos e intangibles. Todos los costos médicos fueron evaluados usando una metodología abajo hacia arriba. Los costos directos fueron valorados desde una perspectiva social usando una metodología de micro-costeo. Los costos indirectos se evaluaron mediante una aproximación de capital humano, y los costos intangibles calculados a partir de los años de vida ajustados por calidad (AVAC). Se analizaron los datos por medio de un análisis multivariado. Para comparaciones con otras poblaciones todos los costos fueron expresados como la razón entre los costos y producto interno bruto nacional per cápita. Resultados: La media de costos totales fue 13.031±9.215 USD (ajustados por el factor de conversión de paridad del poder adquisitivo), lo cual representa el 1,66 del PIB per capita de Colombia. Los costos directos son el 64% de los costos totales. Los costos médicos representan el 80% de los costos directos,. Los costos indirectos fueron el 10% y los costos intangibles el 25% de los costos totales. Los medicamentos representaron el 45% de los costos directos. Mayores costos se relacionaron con el estrato socioeconómico, seguro médico privado, AVAC, alopecia, micofenolato mofetilo, y terapia anticoagulante. Los costos directos ajustados de los pacientes con LES en Colombia fueron mayores que en Norte América y en Europa. Conclusiones: el LES impone una carga económica importante para la sociedad. Los costos relacionados con la atención médica y AVAC fueron los principales contribuyentes al alto costo de la enfermedad. Estos resultados pueden ser referencia para determinar políticas en salud pública así como comparar el gasto en salud de forma internacional.

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In this article we introduce JULIDE, a software toolkit developed to perform the 3D reconstruction, intensity normalization, volume standardization by 3D image registration and voxel-wise statistical analysis of autoradiographs of mouse brain sections. This software tool has been developed in the open-source ITK software framework and is freely available under a GPL license. The article presents the complete image processing chain from raw data acquisition to 3D statistical group analysis. Results of the group comparison in the context of a study on spatial learning are shown as an illustration of the data that can be obtained with this tool.

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The technologies are rapidly developing, but some of them present in the computers, as for instance their processing capacity, are reaching their physical limits. It is up to quantum computation offer solutions to these limitations and issues that may arise. In the field of information security, encryption is of paramount importance, being then the development of quantum methods instead of the classics, given the computational power offered by quantum computing. In the quantum world, the physical states are interrelated, thus occurring phenomenon called entanglement. This study presents both a theoretical essay on the merits of quantum mechanics, computing, information, cryptography and quantum entropy, and some simulations, implementing in C language the effects of entropy of entanglement of photons in a data transmission, using Von Neumann entropy and Tsallis entropy.