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knitr: A Comprehensive Tool for Reproducible Research in R

Published on Dec 14, 2018
· DOI :10.1201/9781315373461-1
Yihui Xie7
Estimated H-index: 7
Abstract
  • References (1)
  • Citations (71)
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Our visual system extracts the emotional meaning of human facial expressions rapidly and automatically. Novel paradigms using fast periodic stimulations have provided insights into the electrophysiological processes underlying emotional content extraction: the regular occurrence of specific identities and/or emotional expressions alone can drive diagnostic brain responses. Consistent with a processing advantage for social cues of threat, we expected angry facial expressions to drive larger respo...
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Tissues are often heterogeneous in their single-cell molecular expression, and this can govern the regulation of cell fate. For the understanding of development and disease, it is important to quantify heterogeneity in a given tissue. We introduce the \proglang{R} package \pkg{stochprofML} which is designed to parameterize heterogeneity from the cumulative expression of small random pools of cells. This method outweighs the demixing of mixed samples with a saving in cost and effort and less meas...
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Within the field of biomedical research in the United States, the proportion of underrepresented minorities at the Full Professor level has remained consistently low, even though trainee demographics are becoming more diverse. Underrepresented groups face a complex set of barriers to achieving faculty status, including imposter syndrome, increased performance expectations, and patterns of exclusion. Institutionalized racism and sexism have contributed to these barriers and perpetuated policy tha...
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#1Lucas J. Koerner (University of St. Thomas (Minnesota))H-Index: 11
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Tools that standardize and automate experimental data collection are needed for greater confidence in research results. The National Synchrotron Light Source-II (NSLS-II) has generated an open-source Python data acquisition, management, and analysis software suite that automates X-ray experiments and collects an experimental record that facilitates complete reproducibility. Here, we show that the NSLS-II tools are not only useful for X-ray science at large-scale facilities by presenting an add-o...
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Abstract Accessibility is a central concept in transport geography research that has been described as a holistic measure of transportation and land use systems. This concept has numerous implementations, but virtually all share the way accessibility is measured as an attribute of pairs of origins and destinations. Borrowing from concepts in network science, in this paper we propose a new centrality measure called betweenness-accessibility. This measure couples the familiar betweenness indicator...
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Studies of the photometric variability of astronomical sources from ground-based telescopes must overcome atmospheric extinction effects. Differential photometry by reference to an ensemble of reference stars which closely match the target in terms of magnitude and colour can mitigate these effects. This Paper describes the design, implementation and operation of a new algorithm, The Locus Algorithm; which enables optimised differential photometry. The Algorithm is intended to identify, for a gi...
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Abstract Preventing the inclusion of oxygen bearing compounds from the organic fraction of skeletal tissues is often considered key to obtaining faithful δ18O measurements of the mineral fraction, which are widely used across the archaeological, forensic and geochemical sciences. Here we re-explore the contentious issue of organic removal pretreatments by establishing how different silver phosphate preparation methods perform in producing pure silver phosphates with a faithful biogenic isotopic ...
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#1Georgia Papacharalampous (NTUA: National Technical University of Athens)H-Index: 9
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Abstract Predictive hydrological uncertainty can be quantified by using ensemble methods. If properly formulated, these methods can offer improved predictive performance by combining multiple predictions. In this work, we use 50-year-long monthly time series observed in 270 catchments in the United States to explore the performances provided by an ensemble learning post-processing methodology for issuing probabilistic hydrological predictions. This methodology allows the utilization of flexible ...
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#1Georgia Papacharalampous (NTUA: National Technical University of Athens)H-Index: 9
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Abstract We introduce an ensemble learning post-processing methodology for probabilistic hydrological modelling. This methodology generates numerous point predictions by applying a single hydrological model, yet with different parameter values drawn from the respective simulated posterior distribution. We call these predictions “sister predictions”. Each sister prediction extending in the period of interest is converted into a probabilistic prediction using information about the hydrological mod...
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#1Georgia Papacharalampous (NTUA: National Technical University of Athens)H-Index: 9
#2Hristos Tyralis (Hellenic Air Force)H-Index: 12
Delivering useful hydrological forecasts is critical for urban and agricultural water management, hydropower generation, flood protection and management, drought mitigation and alleviation, and river basin planning and management, among others. In this work, we present and appraise a new methodology for hydrological time series forecasting. This methodology is based on simple combinations. The appraisal is made by using a big dataset consisted of 90-year-long mean annual river flow time series f...