Titlebook: Lattice; Multivariate Data Vi Deepayan Sarkar Book 2008 Springer-Verlag New York 2008 Data Visualization.Graph.Lattice.R Graphics.Trellis.d

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rials emerged only in the 1990s. The quest for organic photorefractive materials was driven by their electronic optical nonlinearity, which leads to materials that combine high electro-optic coefficient and low dielectric constant, a property that improves the figure of merit for photorefractivity .

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actical implementation of the technology [1]. As discussed in the chapter entitled “Media Requirement for Digital Holographic Data Storage,” the ideal material must simultaneously possess many properties such as good sensitivity, large dynamic range, long data retention times and excellent optical q

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Visualizing Univariate Distributionsbution of a random variable . is defined by the corresponding cumulative distribution function (CDF) .(.) = .(.). For continuous random variables, or more precisely, random variables with an absolutely continuous CDF, an equivalent representation is the density .(.) = .(.). One is often also interes

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Displaying Multiway Tablesa particular category or combination of categories. They could also encode some other summary measure such as a rate (of binary events) or mean (of a continuous variable). In R, tables are usually represented by arrays of one (vectors), two (matrices), or more dimensions. To distinguish them from ot