Error Bar R Plot
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Error Bars In Ggplot2
comment| 5 Answers 5 active oldest votes up vote 16 down vote accepted A Problem with csgillespie solution appears, when You have an logarithmic X axis. The you will have a different length of the small bars on the right an the left side (the epsilon follows the x-values). You should better use the errbar function from the Hmisc package: d = data.frame( x = c(1:5) , y = c(1.1, 1.5, 2.9, 3.8, 5.2) , sd = c(0.2, 0.3, 0.2, 0.0, 0.4) ) ##install.packages("Hmisc", dependencies=T) library("Hmisc") # add error bars (without adjusting yrange) plot(d$x, d$y, type="n") with ( data = d , expr = errbar(x, y, y+sd, y-sd, add=T, pch=1, cap=.1) ) # new plot (adjusts Yrange automatically) with ( data = d , expr = errbar(x, y, y+sd, y-sd, add=F, pch=1, cap=.015, log="x") ) share|improve this answer answered Sep 6 '13 at 14:21 R_User 3,18984581 add a comment| up vote 19 down vote A solution with ggplot2 : qplot(x,y)+geom_errorbar(aes(x=x, ymin=y-sd, ymax=y+sd), width=0.25) share|improve this answer answered Feb 25 '13 at 9:06 juba 24.1k56081 add a comment| up vote 18 down vote You can use segments to add the bars in base graphics. Here epsilon controls the line across the top and bottom of the line. plot (x, y, ylim=c(0, 6)) epsilon = 0.02 for(i in 1:5) { up = y[i] + sd[i] low = y[i] - sd[i] segments(x[i],low , x[i], up) segments(x[i]-epsilon, up , x[
|| is.character(x)) "" else as.character(substitute(y)), add=FALSE, lty=1, type='p', ylim=NULL, lwd=1, pch=16, Type=rep(1, length(y)), ...) Arguments x vector of numeric x-axis values (for vertical error bars) or a factor or character variable (for horizontal error bars, x representing the group labels) y vector of
R Arrows
y-axis values. yplus vector of y-axis values: the tops of the error bars. yminus vector summaryse r of y-axis values: the bottoms of the error bars. cap the width of the little lines at the tops and bottoms of the plot mean and standard deviation in r error bars in units of the width of the plot. Defaults to 0.015. main a main title for the plot, see also title. sub a sub title for the plot. xlab optional x-axis labels if add=FALSE. ylab http://stackoverflow.com/questions/15063287/add-error-bars-to-show-standard-deviation-on-a-plot-in-r optional y-axis labels if add=FALSE. Defaults to blank for horizontal charts. add set to TRUE to add bars to an existing plot (available only for vertical error bars) lty type of line for error bars type type of point. Use type="b" to connect dots. ylim y-axis limits. Default is to use range of y, yminus, and yplus. For horizonal charts, ylim is really the x-axis range, excluding differences. lwd line width for line segments (not main line) http://svitsrv25.epfl.ch/R-doc/library/Hmisc/html/errbar.html pch character to use as the point. Type used for horizontal bars only. Is an integer vector with values 1 if corresponding values represent simple estimates, 2 if they represent differences. ... other parameters passed to all graphics functions. Details errbar adds vertical error bars to an existing plot or makes a new plot with error bars. It can also make a horizontal error bar plot that shows error bars for group differences as well as bars for groups. For the latter type of plot, the lower x-axis scale corresponds to group estimates and the upper scale corresponds to differences. The spacings of the two scales are identical but the scale for differences has its origin shifted so that zero may be included. If at least one of the confidence intervals includes zero, a vertical dotted reference line at zero is drawn. Author(s) Charles Geyer, University of Chicago. Modified by Frank Harrell, Vanderbilt University, to handle missing data, to add the parameters add and lty, and to implement horizontal charts with differences. Examples set.seed(1) x <- 1:10 y <- x + rnorm(10) delta <- runif(10) errbar( x, y, y + delta, y - delta ) # Show bootstrap nonparametric CLs for 3 group means and for # pairwise differences on same graph group <- sample(c('a','b','d'), 200, TRUE) y <- runif(200) + .25*(group=='b') + .5*(group=='d') cla <- smean.cl.boot(y[group=='a'],B=100,reps=TRUE) # u
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boxplot to summarize distributions. Means and standard errors are calculated from the raw data using describe. Alternatively, plots of means +/- one standard deviation may be drawn. Usage error.bars(x,stats=NULL, ylab = "Dependent Variable",xlab="Independent Variable", main=NULL,eyes=TRUE, ylim = NULL, xlim=NULL,alpha=.05,sd=FALSE, labels = NULL, pos = NULL, arrow.len = 0.05,arrow.col="black", add = FALSE,bars=FALSE,within=FALSE, col="blue",...) Arguments x A data frame or matrix of raw data stats Alternatively, a data.frame of descriptive stats from (e.g., describe) ylab y label xlab x label main title for figure ylim if specified, the limits for the plot, otherwise based upon the data xlim if specified, the x limits for the plot, otherwise c(.5,nvar + .5) eyes should 'cats eyes' plots be drawn alpha alpha level of confidence interval – defaults to 95% confidence interval sd if TRUE, draw one standard deviation instead of standard errors at the alpha level labels X axis label pos where to place text: below, left, above, right arrow.len How long should the top of the error bars be? arrow.col What color should the error bars be? add add=FALSE, new plot, add=TRUE, just points and error bars bars bars=TRUE will draw a bar graph if you really want to do that within should the error variance of a variable be corrected by 1-SMC? col color(s) of the catseyes. Defaults to blue. ... other parameters to pass to the plot function, e.g., typ="b" to draw lines, lty="dashed" to draw dashed lines Details Drawing the mean +/- a confidence interval is a frequently used function when reporting experimental results. By default, the confidence interval is 1.96 standard errors of the t-distribution. If within=TRUE, the error bars are corrected for the correlation with the other variables by reducing the variance by a factor of (1-smc). This allows for comparisons between variables. The error bars are normally calculated from the data using the describe function. If, alternatively, a matrix o