The lattice package is meant to improve upon the base R graphics by giving better defaults and has the ability to display multivariate relationships easily.
The lattice package in R is a powerful and flexible plotting system for creating various types of statistical graphics. It is part of the “Trellis” graphics system, which is based on the idea of dividing plots into multiple panels or “trellis” displays. The lattice package provides a high-level interface for creating conditioned plots, which means creating separate plots for different subsets of the data based on one or more conditioning variables.
Here are some key features and concepts associated with the lattice package:
Formula Interface: Lattice graphics use a formula interface similar to that of base R plotting functions. The formula typically includes the response variable and one or more conditioning variables.
library(lattice)
xyplot(y ~ x | group, data = mydata)
Panel Functions: Lattice graphics use panel functions to define the content of each individual panel in a conditioned plot. These functions specify how the data should be displayed within each subset defined by the conditioning variables.
xyplot(y ~ x | group, data = mydata,
panel = function(x, y) {
panel.points(x, y)
panel.abline(h = mean(y), col = “red”)
})
Conditional Plots: The lattice package excels at creating conditional plots, allowing you to visualize relationships between variables within different subsets of the data. This is particularly useful for exploring interactions in multivariate data.
Customization: Lattice graphics provide a high level of customization, allowing you to modify various aspects of the plot, including axis labels, titles, colors, and more.
xyplot(y ~ x | group, data = mydata,
main = “Conditional Scatterplot”,
xlab = “X-axis Label”, ylab = “Y-axis Label”,
col = c(“blue”, “green”, “orange”))
Trellis Layout: The lattice package automatically arranges multiple panels in a trellis layout based on the conditioning variables, making it easy to compare subsets of the data.
xyplot(y ~ x | group, data = mydata, layout = c(2, 2))
Overall, the lattice package is widely used for its ability to create informative and visually appealing conditioned plots, making it a valuable tool for exploratory data analysis and data visualization in R.