📉Graphical Representation: Trellis (Just the Quotes)

"In general, Trellis displays consist of one or more panels, arranged in a regular grid-like structure of columns, rows, and pages. Simple displays are usually easy to create; multi-panel displays take little more effort. A wide range of graphs can be drawn inside each panel, although all panels in a particular Trellis display must be alike. Each panel displays a subset of the data, determined by the values of the given variables." (Richard A Becker et al, "A Tour of Trellis Graphics", 1996)

"Trellis displays are plots which contain one or more panels, arranged in a regular grid-like structure (a trellis). Each panel graphs a subset of the data. All panels in a Trellis display contain the same type of graph but these graphs are general enough to encompass a wide variety of 2-D and 3-D displays: histogram, scatter plot, dot plot, contour plot, wireframe, 3-D point cloud and more. The data subsets are chosen in a regular manner, conditioning on continuous or discrete variables in the data, thus providing a coordinated series of views of high-dimensional data." (Richard A Becker et al, "A Tour of Trellis Graphics", 1996)

"Trellis display is a framework for the visualization of data. Its most prominent aspect is an overall visual design, reminiscent of a garden trelliswork, in which panels are laid out into rows, columns, and pages. On each panel of the trellis, a subset of the data is graphed by a display method such as a scatterplot, curve plot, boxplot, 3-D wireframe, normal quantile plot, or dot plot. Each panel shows the relationship of certain variables conditional on the values of other variables. A number of display methods employed in the visual design of Trellis display enable it to succeed in uncovering the structure of data even when the structure is quite complicated." (Richard A Becker et al, "The Visual Design and Control of Trellis Display", Journal of Computational and Graphical Statistics Vol. 5 (2), 1996)

"The salient visual aspect of Trellis display is a three-way rectangular array of panels with columns, rows, and pages. [...] Each panel of a trellis display shows a subset of the values of panel variables; these values are formed by conditioning on the values of conditioning variables." (Richard A Becker et al, "The Visual Design and Control of Trellis Display", Journal of Computational and Graphical Statistics Vol. 5 (2), 1996)

"Shingling is the process of dividing a continuous variable into - possibly overlapping - intervals in order to convert a continuous variable into a discrete variable. Shingling is quite different from conditioning on categorical variables. Overlapping shingles/intervals lead to multiple representation of data within a trellis display, which is not the case for categorical variables. Furthermore, it is challenging to judge which intervals/cases have been chosen to build a shingle. Trellis displays represent the shingle interval visually by an interval of the strip label. Although no plotting space is wasted, the information on the intervals is difficult to read from the strip label. Despite these drawbacks, there is a valid motivation for shingling […]." (Martin Theus & Simon Urbanek, "Interactive Graphics for Data Analysis: Principles and Examples", 2009)

"Trellis displays introduce the concept of shingling. Shingling is the process of dividing a continuous variable into - possibly overlapping - intervals in order to convert a continuous variable into a discrete variable. Shingling is quite different from conditioning on categorical variables. Overlapping shingles/intervals lead to multiple representation of data within a trellis display, which is not the case for categorical variables. Furthermore, it is challenging to judge which intervals/cases have been chosen to build a shingle. Trellis displays represent the shingle interval visually by an interval of the strip label. Although no plotting space is wasted, the information on the intervals is difficult to read from the strip label. Despite these drawbacks, there is a valid motivation for shingling [...]" (Martin Theus & Simon Urbanek, "Interactive Graphics for Data Analysis: Principles and Examples", 2009)

"Trellis displays use a lattice-like arrangement to place plots onto so-called panels. Each plot in a trellis display is conditioned upon at least one other variable. The same scales are used in all the panel plots in order to make them comparable across rows and columns. […] Trellis displays are an ideal tool to compare models for different subsets. " (Martin Theus & Simon Urbanek, "Interactive Graphics for Data Analysis: Principles and Examples", 2009)

"The trellis plot allows examination of heterogeneity within databases by holding method constant and looking down each column. The plot also allows for side-by-side comparison of different methods, which enables examination of how methods vary both in point estimate and standard error. The trellis forest plot provides a multidimensional approach to sensitivity analysis that should allow more comprehensive examination of heterogeneity, a more robust assessment of key factors influencing an observation, and better context for drawing inferences when interpreting effect estimates. (Patrick Ryan, "Using Exploratory Visualization in the Analysis of Medical Product Safety in Observational Healthcare Data" [in "A Picture is Worth a Thousand Tables: Graphics in Life Sciences", Andreas Krause & Michael O’Connell], 2012)

"One problem for visualizing multiple views is that of laying out the plots. Indeed, there are some plots, such as scatterplot matrixes and trellis displays, that are formed just by arranging simpler plots according to certain rules. Scatterplot matrices, for example, arrange scatterplots side by side so that each variable in a dataset is graphed against the other variables, with the graphs being displayed as a row or a column of the matrix. This lets the user rapidly inspect all of the bivariate relationships among the variables, permitting the detection of outliers, nonlinearities, and other features of the data." (Forrest W Young et al, "Visual Statistics: Seeing data with dynamic interactive graphics", 2016)

"A trellis is a graph whose nodes are ordered into vertical slices (time) with every node at almost every time connected to at least one node at an earlier and at least one node at a later time. The earliest and latest times in the trellis have only one node (hence the 'almost in the preceding sentence)." (Wikipedia) [link]