Someone asked about plotting something like this today
I wrote a few functions previously to do something like this. However, since then ggplot2 has changed, and one of the functions no longer works.
Hence, I fixed opts() to theme(), theme_blank() to element_blank(), and panel.background = element_blank() to plot.background = element_blank() to get the histograms to show up with the line plot and not cover it.
The new functions:
loghistplot <- function(data) { names(data) <- c('x','y') # rename columns # get min and max axis values min_x <- min(data$x) max_x <- max(data$x) min_y <- min(data$y) max_y <- max(data$y) # get bin numbers bin_no <- max(hist(data$x, plot = FALSE)$counts) + 5 # create plots a <- ggplot(data, aes(x = x, y = y)) + theme_bw(base_size=16) + geom_smooth(method = "glm", family = "binomial", se = TRUE, colour='black', size=1.5, alpha = 0.3) + scale_x_continuous(limits=c(min_x,max_x)) + theme(panel.grid.major = element_blank(), panel.grid.minor=element_blank(), panel.background = element_blank(), plot.background = element_blank()) + labs(y = "Probability\n", x = "\nYour X Variable") theme_loghist <- list( theme(panel.grid.major = element_blank(), panel.grid.minor=element_blank(), axis.text.y = element_blank(), axis.text.x = element_blank(), axis.ticks = element_blank(), panel.border = element_blank(), panel.background = element_blank(), plot.background = element_blank()) ) b <- ggplot(data[data$y == unique(data$y)[1], ], aes(x = x)) + theme_bw(base_size=16) + geom_histogram(fill = "grey") + scale_y_continuous(limits=c(0,bin_no)) + scale_x_continuous(limits=c(min_x,max_x)) + theme_loghist + labs(y='\n', x='\n') c <- ggplot(data[data$y == unique(data$y)[2], ], aes(x = x)) + theme_bw(base_size=16) + geom_histogram(fill = "grey") + scale_y_continuous(trans='reverse', limits=c(bin_no,0)) + scale_x_continuous(limits=c(min_x,max_x)) + theme_loghist + labs(y='\n', x='\n') grid.newpage() pushViewport(viewport(layout = grid.layout(1,1))) vpa_ <- viewport(width = 1, height = 1, x = 0.5, y = 0.5) vpb_ <- viewport(width = 1, height = 1, x = 0.5, y = 0.5) vpc_ <- viewport(width = 1, height = 1, x = 0.5, y = 0.5) print(b, vp = vpb_) print(c, vp = vpc_) print(a, vp = vpa_) } logpointplot <- function(data) { names(data) <- c('x','y') # rename columns # get min and max axis values min_x <- min(data$x) max_x <- max(data$x) min_y <- min(data$y) max_y <- max(data$y) # create plots ggplot(data, aes(x = x, y = y)) + theme_bw(base_size=16) + geom_point(size = 3, alpha = 0.5, position = position_jitter(w=0, h=0.02)) + geom_smooth(method = "glm", family = "binomial", se = TRUE, colour='black', size=1.5, alpha = 0.3) + scale_x_continuous(limits=c(min_x,max_x)) + theme(panel.grid.major = element_blank(), panel.grid.minor=element_blank(), panel.background = element_blank()) + labs(y = "Probability\n", x = "\nYour X Variable") } Install ggplot2 and gridExtra if you don’t have them:
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