R Error Bars Arrows
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Error.bar Function R
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Scatter Plot With Error Bars In R
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That's certainly a simpler solution. It might be worth wrapping a few arrows() calls up in some kind of simple errorbar function (just so it's slightly more accessible to newcomers). The only two r ggplot error bars things my function did that these calls don't do is (1) to size the plot r arrows appropriately so the upper and lower limits of the errors are within the plot, (2) to draw the segments/arrows first so that one can barplot with error bars matlab add points with pch=19 and bg=par("bg") to get open points without lines going through them. On Thu, 9 Nov 2000, Emmanuel Paradis wrote: > At 14:07 08/11/00 -0500, Ben Bolker wrote: > > > > I'm going to take https://www.r-bloggers.com/building-barplots-with-error-bars/ the liberty of reposting this function, which is based > >on one that Bill Venables posted a while back. I've tweaked with it a bit > >to add functionality. It will do horizontal bars or vertical bars, but > >not (yet) both simultaneously (the hardest thing about that is deciding on > >what format you want the data supplied in). > > > > There's also a help file supplied below. > > > > Should this (after appropriate https://stat.ethz.ch/pipermail/r-help/2000-November/009029.html tweaking/polishing/testing/revision) go > >into the main R code base? It seems like a pretty basic function to me > >... > > [...] > > >On Wed, 8 Nov 2000, Mike Beddo wrote: > > > >> I'm a newcomer to R. I can't seem to find any documentation how to add > >> error bars to points in scatter plots. I guess I could plot the points, > >> then compute and plot line segments in the X and/or Y directions to > >> represent the errors? > >> > >> - Mike > > I think using arrows(..., code=3, angle=90, ...) is quite simple, e.g.: > > x <- rnorm(10) > y <- rnorm(10) > se.x <- runif(10) > se.y <- runif(10) > plot(x, y, pch=22) > arrows(x, y-se.y, x, y+se.y, code=3, angle=90, length=0.1) > arrows(x-se.x, y, x+se.x, y, code=3, angle=90, length=0.1) > > The first arrows() draws the error bars for y, and the second one for x, > 'code=3' draws a head at both ends of the arrow, 'angle=' is the angle of > the head with the main axis of the arrow, and 'length=' is the length of > the head. You can also add usual graphic parameters (col, lwd, ...). > > > Emmanuel Paradis > -.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.- > r-help mailing list -- Read http://www.ci.tuwien.ac.at/~hornik/R/R-FAQ.html > Send "info", "help", or "[un]subscribe" > (in the "body", not the subject !) To
way to illustrate this quantity is with error bars. R has a function named arrows that can simplify this task. arrows requires at least four arguments, the https://cran.r-project.org/doc/contrib/Lemon-kickstart/kr_erbar.html x/y start and end points of each arrow (if each argument is a http://davetang.org/muse/2014/06/25/plotting-error-bars-with-r/ vector, an arrow will be drawn for each value in the vector). Note that the points will be specified in user units, that is, the units that are actually illustrated on the graph. Start with the start points. These are usually separated from the points marking the values by a small amount. I error bar use the current height of a lower case "m". In order to get bars going up and down, there will have to be two sets of starting points. Similarly, two sets of end points will be needed, calculated by adding and subtracting the value of the standard errors for each of the data points - see plot.dstat(). First, the function checks that its argument is error bars in there, and is an object of class "dstat". Now have a look at the arguments to arrows. In addition to the first four arguments specifying the start and end points of the arrows, the length argument specifies the length of the arms in (blush) inches and the angle argument specifies the angle of the arms from the stem. R has inherited a lot of things from S. Some of them aren't the greatest, like the default units of inches and points. Well, nobody's perfect. Notice that the function will do its best to work out missing arguments from the data. If error bars are requested, get.dstat.ylim() is called to work out the maximum range of the entire dstat object. Notice the offset= option in plot.dstat. This allows you to ask for additional points and error bars produced by add.pointline() to be moved side to side so that they don't overlap. Your idea of a great point/line plot may be somewhat different. By now you should have an idea of the tools that can be used to get that plot. For more information, see An Introduction to R: High-level plotting commands. Back to Table of Contents
25, 2014 by Davo Error bars may show confidence intervals, standard errors, and standard deviations. Each feature conveys a different message and this paper on error bars in experimental biology explains it very nicely. For this post I will demonstrate how to plot error bars that show the standard error (SE) or standard error of the mean (SEM). I found two nice resources that demonstrate the plotting of error bars with R and in this post I illustrate them with simple examples. The first method is from the website of James Holland Jones, where he wrote an R function that plots arrows to a bar plot. #generate some random numbers set.seed(31) a <- runif(10, 0, 10) b <- runif(10, 0, 10) c <- runif(10, 0, 10) #store them as a data.frame df <- data.frame(a=a, b=b, c=c) #function for error bars error.bar <- function(x, y, upper, lower=upper, length=0.1,...){ if(length(x) != length(y) | length(y) !=length(lower) | length(lower) != length(upper)) stop("vectors must be same length") arrows(x,y+upper, x, y-lower, angle=90, code=3, length=length, ...) } #function for standard error of the mean sem <- function(x){ sd(x)/sqrt(length(x)) } #calculate means my_mean <- apply(df, 2, mean) #calculate sem my_sem <- apply(df, 2, sem) #barplot barx <- barplot(my_mean, names.arg=names(df), ylim=c(0,ceiling(max(df))), xlab='Class', ylab='Unit of measure') error.bar(barx, my_mean, my_sem) The second resource I found on plotting error bars with R was from the Cookbook for R, which showed many examples using the R package ggplot2. Here is a simple example I adapted from their cookbook, using the same set of random numbers I generated above: #install if necessary install.packages('ggplot2') #load library library(ggplot2) set.seed(31) a <- runif(10, 0, 10) b <- runif(10, 0, 10) c <- runif(10, 0, 10) df <- data.frame(a=a, b=b, c=c) sem <- function(x){ sd(x)/sqrt(length(x)) } my_mean <- apply(df, 2, mean) my_sem <- apply(df, 2, sem) #new data frame for storing the mean and sem mean_sem <- data.frame(mean=my_mean, sem=my_sem, group=names(df)) #larger font theme_set(theme_gray(base_size = 20)) #plot using ggplot ggplot(mean_sem, aes(x=group, y=mean)) + geom_bar(stat='identity') + geom_errorbar(aes(ymin=mean-sem, ymax=mean+sem), width=.2) + xlab('Class') + ylab('Unit of measure') I had been using the first approach for plotting error bars with R but I think the ggplot2 plot looks much better (with less eff