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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Visualizing Univariate Distributionslots and box-and-whisker plots are based on (partial) estimates of . or its inverse..Although the mathematical relationships between the theoretical constructs are well-defined, there are no natural relationships between their standard estimates. Furthermore, the task of visualization comes with its

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Displaying Multiway Tabless.data.frame.table() function can be used for converting tables to suitable data frames. In addition, there are methods in lattice that work directly on tables. We focus on the latter in this chapter; examples using the formula interface can be found in Chapter 2.

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Graphical Parameters and Other Settingshe user. The latter approach has two primary benefits: it allows good global defaults to be specified, and it provides a consistent “l(fā)ook and feel” to lattice graphics while letting the user retain ultimate control..Not all parameters of interest are graphical. For example, a user may dislike the de

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New Trellis Displaysa which are in a form that is not directly usable. A typical example of this is a univariate time series; there is really only one choice for the . and . variables in the xyplot() call that produced Figure 10.17, and the need for a new function to hide the use of a formula seems wasteful..Rather tha

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