Hang on, maybe you mean something like this: erupt_dens<-density(faithful$eruptions) plot(erupt_dens,ylim=c(0,0.65)) dispersion(erupt_dens$x,erupt_dens$y,ulim=erupt_dens$y/5, type="l",fill="lightgray",interval=TRUE) lines(erupt_dens)
Jim On Fri, Dec 2, 2016 at 9:36 PM, Jim Lemon <drjimle...@gmail.com> wrote: > In order to display a polygon, you need x/y pairs for each point. If > you just want a rectangle, you only need four x/y pairs, e.g.: > > plot(0,xlim=x(2.44,2.57),ylim=c(0,1),type="n") > polygon(c(2.44,2.57,2.57,2.44),c(0,0,1,1),col="lightgray") > > Now if you have a series of x values and want to display a band of > constant width around it: > > y_values<-runif(14) > plot(seq(2.44,2.57,by=0.01),y_values,ylim=c(-2,3)) > dispersion(seq(2.44,2.57,by=0.01),y_values,ulim=rep(0.5,14), > type="l",interval=TRUE,col="lightgray") > lines(seq(2.44,2.57,by=0.01),y_values) > > Jim > > On Fri, Dec 2, 2016 at 8:59 PM, Elysa Mitova <elysa.mit...@gmail.com> wrote: >> Thank you, >> >> this seems to work, but it is not exactly what I need (it indeed looks >> great, but a bit beyond my understanding) >> >> I just need a shaded area between 2.44 to 2.57 along the x-axis - a polygon >> inserted into my density plot (and not a confidence line along a scatter >> plot like your suggested solution) >> >> My x-axis is an index (a data frame), my y-axis is the automatically >> constructed density >> >> On Fri, Dec 2, 2016 at 10:01 AM, Jim Lemon <drjimle...@gmail.com> wrote: >>> >>> Hi Elysa, >>> I think you are going a bit off course in your example. Try this and >>> see if it is close to what you want: >>> >>> data<-rnorm(100)+runif(100,0,15) >>> smu_data<-supsmu(1:100,data) >>> rollfun<-function(x,window=10,FUN=sd) { >>> xlen<-length(x) >>> xout<-NA >>> forward<-window%/%2 >>> backward<-window-forward >>> for(i in 1:xlen) { >>> xstart<-i-backward >>> if(xstart < 1) xstart<-1 >>> xend<-i+forward-1 >>> if(xend > xlen) xend<-xlen >>> xout[i]<-do.call(FUN,list(x[xstart:xend],na.rm=TRUE)) >>> } >>> return(xout) >>> } >>> mad_data<-rollfun(data,10,mad) >>> plot(data,ylim=c(0,17)) >>> library(plotrix) >>> dispersion(smu_data$x,smu_data$y,mad_data,type="l",interval=TRUE, >>> fill="lightgray") >>> lines(smu_data,lwd=2) >>> points(1:100,data) >>> >>> Jim >>> >>> >>> On Fri, Dec 2, 2016 at 7:18 PM, Elysa Mitova <elysa.mit...@gmail.com> >>> wrote: >>> > Hi, thank you! >>> > >>> > I've constructed the upper and lower bounds with >>> > >>> > a <- 2.505766 >>> > s <- 0.7789832 >>> > n <- 607 >>> > error <- qnorm(0.975)*s/sqrt(n) >>> > left <- a-error >>> > right <- a+error >>> > left >>> > right >>> > >>> > Now, I have the numbers I need, but I have no idea how to plot them. I >>> > was >>> > thinking of using a polygon, but somehow it doesn't work out, because my >>> > y-axis shows only density and is in itself not a variable? >>> > >>> > xx <- data >>> > >>> > fit1 <- density(data,na.rm=TRUE) >>> > >>> > fit2 <- replicate(10000, { x <- sample(xx, replace=TRUE); >>> > density(x, na.rm=TRUE, from=min(fit1$x), to=max(fit1$x))$y } ) >>> > >>> > fit3 <- apply(fit2, 1, quantile, c(0.025,0.975) ) - Probably herein >>> > lies the problem? >>> > >>> > plot(fit1, ylim=range(fit3)) >>> > polygon( c(fit1$x, rev(fit1$x)), c(fit3[1,], rev(fit3[2,])), >>> > col='grey', border=F) >>> > lines(fit1) >>> > >>> > I tried working with this solution I found on the internet, but >>> > somehow now the lines the shaded areas sporadically everywhere around >>> > my density plot? I just want a polygon spreading from 2.44 to 2.57 >>> > along the x-axis. >>> > >>> > >>> > Any tipps? >>> > >>> > >>> > >>> > >>> > On Fri, Dec 2, 2016 at 1:24 AM, David Winsemius <dwinsem...@comcast.net> >>> > wrote: >>> > >>> >> >>> >> > On Dec 1, 2016, at 12:10 PM, Elysa Mitova <elysa.mit...@gmail.com> >>> >> wrote: >>> >> > >>> >> > Hi, >>> >> > >>> >> > I am desperately looking for a way to plot confidence intervals into >>> >> > a >>> >> > density plot of only one variable (not a scatter plot etc.) >>> >> > >>> >> > Have you any advice how to do this? >>> >> > >>> >> > I've only found manual ways to do with "abline", but this is a rather >>> >> > bothersome method and only works with ggplot (and not ggplot2). >>> >> >>> >> This makes it appear that you expect this to be done in ggplot2 >>> >> automagically. I suspect you must instead first find the right approach >>> >> to >>> >> construction of those upper and lower bounds before plotting. It's not >>> >> clear what methods you expect to be needed. Your desperation is not a >>> >> guide. Perhaps trying a bit of searching? >>> >> >>> >> install.packages("sos") >>> >> library(sos) >>> >> findFn("confidence intervals density estimates") >>> >> >>> >> >>> >> Delivers quite a few results. Then searching on the text within that >>> >> webpage you find >>> >> >>> >> >>> >> 208 2 27 54 nprobust kdrobust >>> >> 2016-11-14 >>> >> 16:41:50 27 Kernel Density Estimation with Robust Confidence >>> >> Intervals >>> >> 209 2 27 54 nprobust lprobust >>> >> 2016-11-14 >>> >> 16:41:50 27 Local-Polynomial Estimation with Robust Confidence >>> >> Intervals >>> >> >>> >> Is that what you seek? >>> >> >>> >> > >>> >> > Thank you! >>> >> > >>> >> > [[alternative HTML version deleted]] >>> >> I know you just subscribed, so now is the time to read the Posing >>> >> Guide. >>> >> >>> >> == >>> >> >>> >> David Winsemius >>> >> Alameda, CA, USA >>> >> >>> >> >>> > >>> > [[alternative HTML version deleted]] >>> > >>> > ______________________________________________ >>> > R-help@r-project.org mailing list -- To UNSUBSCRIBE and more, see >>> > https://stat.ethz.ch/mailman/listinfo/r-help >>> > PLEASE do read the posting guide >>> > http://www.R-project.org/posting-guide.html >>> > and provide commented, minimal, self-contained, reproducible code. >> >> ______________________________________________ R-help@r-project.org mailing list -- To UNSUBSCRIBE and more, see https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.