Plotting only highest R squared panels #37
Description
Is it possible to plot only the highest R squared panels in lattice without preprocessing the data to remove them? In aphalo/ggpmisc#46 it is suggested that it is not possible in ggplot2 so I thought I would ask regarding lattice. Below are examples of doing it with preprocessing using lattice/latticeExtra and using tidyverse/ggplot2.
library(latticeExtra)
# all trees except 4 have R squared >= 0.97
is.highR2 <- function(tree)
summary(lm(age ~ circumference, Orange, subset = Tree == tree))$r.squared >= 0.97
Trees <- Filter(is.highR2, levels(Orange$Tree)); Trees
## [1] "3" "1" "5" "2"
if (length(Trees)) {
p1 <- xyplot(age ~ circumference | Tree, Orange, subset = Tree %in% Trees) +
layer(panel.ablineq(lm(y ~ x), r.squared = TRUE, label = "", sep = "", adj = c(0.75, -4)))
plot(p1)
}
##################################################################
library(broom)
library(dplyr)
library(ggplot2)
library(ggpmisc)
# all Trees except 4 have R squared >= 0.97
Trees <- Orange %>%
nest_by(Tree) %>%
summarize(model = list(lm(age ~ circumference, data)), glance(model)) %>%
filter(r.squared >= 0.97) %>%
pull(Tree)
# plot
if (length(Trees)) {
p2 <- Orange %>%
filter(Tree %in% Trees) %>%
ggplot(aes(circumference, age)) +
geom_point() +
stat_poly_eq() +
geom_smooth(method = "lm", se = FALSE) +
facet_wrap(~ Tree)
plot(p2)
}