978 resultados para Longitudinal Data Analysis and Time Series


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The program PanPlot 2 was developed as a visualization tool for the information system PANGAEA. It can be used as a stand-alone application to plot data versus depth or time. Data input format is tab-delimited ASCII (e.g. by export from MS-Excel or from PANGAEA). The default scales and graphic features can individualy be modified. PanPlot 2 graphs can be exported in several image formats (BMP, PNG, PDF, and SVG) which can be imported by graphic software for further processing.

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The Lomb periodogram has been traditionally a tool that allows us to elucidate if a frequency turns out to be important for explaining the behaviour of a given time series. Many linear and nonlinear reiterative harmonic processes that are used for studying the spectral content of a time series take into account this periodogram in order to avoid including spurious frequencies in their models due to the leakage problem of energy from one frequency to others. However, the estimation of the periodogram requires long computation time that makes the harmonic analysis slower when we deal with certain time series. Here we propose an algorithm that accelerates the extraction of the most remarkable frequencies from the periodogram, avoiding its whole estimation of the harmonic process at each iteration. This algorithm allows the user to perform a specific analysis of a given scalar time series. As a result, we obtain a functional model made of (1) a trend component, (2) a linear combination of Fourier terms, and (3) the so-called mixed secular terms by reducing the computation time of the estimation of the periodogram.

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This study focuses on soft boot snowboard bindings by looking at how users interact with their binding and proposes a possible solution to overcome such issues. Snowboarding is a multibillion-dollar sport that has only reached mainstream in the last 30 years its levels of progression in technology have evolved in that time. However, snowboard bindings for the most part still consist of the same basic architecture in the last 20 years. This study was aimed at taking a user centric point of view and using additive manufacturing technologies to be able to generate a new snowboard binding that is completely adaptable to the user. The initial part of the study was a survey of 280 snowboarders focussing on preferences, style and habits. This survey was generated from over 15 nations with the vast majority of boarders on the snow for five to fifty days a year. Significant emphasis was placed on the relationship between boarder binding set-up and occurrence of pain and/or injury. From the detailed survey it was found that boarder's experienced pain in the front foot/toe area as a result from the toe strap being too tight. However boarders wanted tighter bindings to increase responsiveness. Survey data was compared to ankle and foot biomechanics to build a relationship to assess the problem of pain versus responsiveness. The design stage of the study was to develop a binding that overcame the over-tightening of the binding but still maintain equivalent or better responsiveness compared to traditional bindings. The resulting design integrated the snowboard boot much more into the design, by using the sole as a "semi-rigid" platform and locking it in laterally between the heel cup and the new toe strap arrangement. The new design developed using additive manufacturing techniques was tested via qualitative and quantitative measures in the snow and in the lab. It was found that using the new arrangement in a system resulted in no loss of performance or responsiveness to the user. Due to the design and manufacturing approach users have the ability to customise the design to their specific needs.

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To the Editor—In a recent review article in Infection Control and Hospital Epidemiology, Umscheid et al1 summarized published data on incidence rates of catheter-associated bloodstream infection (CABSI), catheter-associated urinary tract infection (CAUTI), surgical site infection (SSI), and ventilator- associated pneumonia (VAP); estimated how many cases are preventable; and calculated the savings in hospital costs and lives that would result from preventing all preventable cases. Providing these estimates to policy makers, political leaders, and health officials helps to galvanize their support for infection prevention programs. Our concern is that important limitations of the published studies on which Umscheid and colleagues built their findings are incompletely addressed in this review. More attention needs to be drawn to the techniques applied to generate these estimates...

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Book review of: Chance Encounters: A First Course in Data Analysis and Inference by Christopher J. Wild and George A.F. Seber 2000, John Wiley & Sons Inc. Hard-bound, xviii + 612 pp ISBN 0-471-32936-3

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The application of compositional data analysis through log ratio trans- formations corresponds to a multinomial logit model for the shares themselves. This model is characterized by the property of Independence of Irrelevant Alter- natives (IIA). IIA states that the odds ratio in this case the ratio of shares is invariant to the addition or deletion of outcomes to the problem. It is exactly this invariance of the ratio that underlies the commonly used zero replacement procedure in compositional data analysis. In this paper we investigate using the nested logit model that does not embody IIA and an associated zero replacement procedure and compare its performance with that of the more usual approach of using the multinomial logit model. Our comparisons exploit a data set that com- bines voting data by electoral division with corresponding census data for each division for the 2001 Federal election in Australia