The jackknife-a review

Miller, Rupert G.

doi:10.1093/biomet/61.1.1

Cited by 560 publications

(226 citation statements)

References 32 publications

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“…4a-c below). We then performed a Bleave-one-out cross-validation^(LOOCV) procedure (see Geisser, 1975;Lachenbruch, 1967;Miller, 1974;Stone, 1974; for a review, see Arlot & Celisse, 2010) on these points using a standard feedforward-backpropagation (FFBP) network (Rumelhart, McClelland, & the PDP Research Group, 1986). This analysis worked as follows.…”

Section: Scanpath Comparisonmentioning

confidence: 99%

An evaluation of scanpath-comparison and machine-learning classification algorithms used to study the dynamics of analogy making

2016

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In recent years, eyetracking has begun to be used to study the dynamics of analogy making. Numerous scanpathcomparison algorithms and machine-learning techniques are available that can be applied to the raw eyetracking data. We show how scanpath-comparison algorithms, combined with multidimensional scaling and a classification algorithm, can be used to resolve an outstanding question in analogy making-namely, whether or not children's and adults' strategies in solving analogy problems are different. (They are.) We show which of these scanpath-comparison algorithms is best suited to the kinds of analogy problems that have formed the basis of much analogy-making research over the years. Furthermore, we use machine-learning classification algorithms to examine the item-to-item saccade vectors making up these scanpaths. We show which of these algorithms best predicts, from very early on in a trial, on the basis of the frequency of various item-to-item saccades, whether a child or an adult is doing the problem. This type of analysis can also be used to predict, on the basis of the item-to-item saccade dynamics in the first third of a trial, whether or not a problem will be solved correctly.Keywords Eyetracking algorithms . Jarodzka algorithm . LDA . SVM . Analogy strategies Traditionally, analogy making has been studied statically. Participants typically see a pair of related images (the Bbase pair^), along with a third image and a number of candidate target images. One of these target images-the Bcorrect analogical match^-is supposed to be related to the third image in the same way that the base items were related to one another. The participant's task is to identify the correct analogical match. Correct and incorrect answers (and, sometimes, reaction times) are recorded and analyzed. However, these studies could not capture-and in fairness, were not designed to capture-the dynamic aspects of solving an analogy problem. As such, they shed essentially no light on the question of what strategies were adopted during the course of solving analogy problems.In this article, we introduce a novel means of studying the dynamic aspects of analogy making in both children and adults. The proposed methodology involves combining eyetracking, multidimensional scaling (MDS), and neuralnetwork classification algorithms, as well as using machinelearning algorithms to analyze the component vectors making up participants' scanpaths. In what follows, we will briefly describe each of these techniques and show how they can be combined successfully in the context of analogy making.Although the purpose of this article is, first and foremost, a methodological one, it is important to note that the development of these techniques has allowed us (French & Thibaut, 2014;Thibaut & French, 2016;Thibaut, French, Missault, Gérard, & Glady, 2011) to answer, for what we believe to be the first time, a long-standing question in the field of analogymaking-namely, do children and adults use the same (or very similar) search-space strategies when...

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Section: Scanpath Comparisonmentioning

confidence: 99%

An evaluation of scanpath-comparison and machine-learning classification algorithms used to study the dynamics of analogy making

2016

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“…The adjusted unbiased prediction method was adopted to estimate different effects (Zhu and Weir, 1996). The Jackknife resampling method (Miller, 1974) was used to calculate the standard errors of the estimated values for t-test, and the significance of differences was tested by t-test.…”

Section: Resultsmentioning

confidence: 99%

Genetic variation in alkaloid accumulation in leaves of Nicotiana

Sun

Zhang

Guang-hong

et al. 2013

J. Zhejiang Univ. Sci. B

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Alkaloids are plant secondary metabolites that are widely distributed in Nicotiana species and contribute greatly to the quality of tobacco leaves. Some alkaloids, such as nornicotine and myosmine, have adverse effects on human health. To reduce the content of harmful alkaloids in tobacco leaves through conventional breeding, a genetic study of the alkaloid variation among different genotypes is required. In this study, alkaloid profiles in leaves of five Nicotiana tabacum cultivars and Nicotiana tomentosiformis were investigated. Six alkaloids were identified from all six genotypes via gas chromatograph-mass spectrometry (GC-MS). Significant differences in alkaloid content were observed both among different leaf positions and among cultivars. The contents of nornicotine and myosmine were positively and significantly correlated (R 2 =0.881), and were also separated from those of other alkaloids by clustering. Thus, the genotype plays a major role in alkaloid accumulation, indicating a high potential for manipulation of alkaloid content through traditional breeding.

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“…To compare with experimental data the scalar product method [57,58] is used to calculate the 2 and 4-particle cumulants with the inclusion of multiplicity weighting and centrality class rebinning as described in [18,59]. We have at least a couple of thousand hydrodynamic events in each centrality class and we checked that our statistical error bars (computed using jackknife resampling [60]) are on the order of 10 −4 . The free parameters ξ and α that define our two energy loss scenarios are determined by matching our model calculations for D 0 R AA to experimental data at p T 10 GeV in the 0-10% centrality class.…”

Section: Details Of the Modelmentioning

confidence: 99%

Event-by-event correlations between soft hadrons and D0 mesons in 5.02 TeV PbPb collisions at the CERN Large Hadron Collider

et al. 2017

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In this paper heavy quark energy loss models are embedded in full event-by-event viscous hydrodynamic simulations to investigate the nuclear suppression factor and the azimuthal anisotropy of D 0 mesons in PbPb collisions at √ sNN = 5.02 TeV in the pT range 8-40 GeV. In our model calculations, the RAA of D 0 mesons is consistent with experimental data from the cms experiment. We present the first calculations of heavy flavor cumulants v2{2} and v3{2} (and also discuss v2{4}), which is also consistent with experimental data. Event-shape engineering techniques are used to compute the event-by-event correlation between the soft hadron vn and the heavy meson vn. We predict a linear correlation between these observables on an event-by-event basis.

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The jackknife-a review

Cited by 560 publications

References 32 publications

An evaluation of scanpath-comparison and machine-learning classification algorithms used to study the dynamics of analogy making

An evaluation of scanpath-comparison and machine-learning classification algorithms used to study the dynamics of analogy making

Genetic variation in alkaloid accumulation in leaves of Nicotiana

Event-by-event correlations between soft hadrons and D0 mesons in 5.02 TeV PbPb collisions at the CERN Large Hadron Collider

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