R help - Dec 2019 - Plotting confidence intervals

Thanks for these helpful suggestions.

These options don't work in my case because I don't know the individual 
observations (the dots). A statistical agency collects the observations 
and keeps them confidential. It provides the mean value and the standard 
deviation, plus the fact that the observations are normally distributed. 
So I have enough information to draw the distribution function.  Mean 
values and standard deviations are provided for several cases 
(geographies). I can plot the mean values for all cases in a bar chart. 
I can show the confidence intervals as I-beams, as in my example. But I 
would prefer to show the confidence intervals as truncated bell curves, 
referring to, say, 95% of the unseen observations.

Philip

On 2019-12-07 22:07, Ben Tupper wrote:
> Hi,
> 
> Would something like yarrr do the trick?
> https://ndphillips.github.io/yarrr.html
> 
> Or gghalves?  https://github.com/erocoar/gghalves
> 
> Cheers,
> Ben
> 
> On Sat, Dec 7, 2019 at 9:32 PM <phil at philipsmith.ca> wrote:
> 
>> I want to show little bell curves on my bar chart to illustrate the
>> confidence ranges. The following example from Paul Teetor's "R
>> Cookbook"
>> does what I want, but shows I-beams instead of bell curves. The
>> I-beams
>> suggest uniform, rather than normal distributions. So I am looking
>> for a
>> way to plot normal distribution curves instead.
>> 
>> # Example from Paul Teetor, "R Cookbook", page 238.
>> library(gplots)
>> attach(airquality)
>> heights <- tapply(Temp,Month,mean)
>> lower <- tapply(Temp,Month,function(v) t.test(v)$conf.int [1][1])
>> upper <- tapply(Temp,Month,function(v) t.test(v)$conf.int [1][2])
>> barplot2(heights,plot.ci [2]=TRUE,ci.l=lower,ci.u=upper,
>> ylim=c(50,90),xpd=FALSE,
>> main="Mean Temp. By Month",
>>
names.arg=c("May","Jun","Jul","Aug","Sep"),
>> ylab="Temp (deg. F)")
>> 
>> Does anyone know a package that does this or, alternatively, can
>> anyone
>> suggest a direction to go in if one were to write R code to do this?
>> 
>> Philip
>> 
>> ______________________________________________
>> R-help at 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.
> 
> --
> 
> Ben Tupper
> Bigelow Laboratory for Ocean Science
> West Boothbay Harbor, Maine
> http://www.bigelow.org/
> 
> https://eco.bigelow.org
> 
> 
> 
> Links:
> ------
> [1] http://conf.int
> [2] http://plot.ci

Hi Philip,
This may be a starter:

attach(airquality)
heights <- tapply(Temp,Month,mean)
temp_sd<-tapply(Temp,Month,sd)
lower <- tapply(Temp,Month,function(v) t.test(v)$conf.int[1])
upper <- tapply(Temp,Month,function(v) t.test(v)$conf.int[2])
library(plotrix)
barp(heights,ylim=c(0,100),names.arg=month.abb[5:9],
 main="Air quality
(May-Sep)",xlab="Month",ylab="Temperature")
dispersion(1:5,y=heights,ulim=upper,llim=lower,intervals=FALSE)
ci95<-seq(-1.96,1.96,length.out=40)
norm_curve<-rescale(dnorm(ci95),c(0,0.4))
for(i in 1:5)
 polygon(c(i-norm_curve,i+norm_curve),
  c(heights[i]+ci95*temp_sd[i],heights[i]+rev(ci95*temp_sd[i])))

Jim

On Sun, Dec 8, 2019 at 8:18 PM <phil at philipsmith.ca>
wrote:
> >> I want to show little bell curves on my bar chart to illustrate
the
> >> confidence ranges. The following example from Paul Teetor's
"R
> >> Cookbook"
> >> does what I want, but shows I-beams instead of bell curves. The
> >> I-beams
> >> suggest uniform, rather than normal distributions. So I am looking
> >> for a
> >> way to plot normal distribution curves instead.

Thanks so much Jim. Yes, this is giving me what I want.

Philip

On 2019-12-08 05:00, Jim Lemon wrote:
> Hi Philip,
> This may be a starter:
> 
> attach(airquality)
> heights <- tapply(Temp,Month,mean)
> temp_sd<-tapply(Temp,Month,sd)
> lower <- tapply(Temp,Month,function(v) t.test(v)$conf.int[1])
> upper <- tapply(Temp,Month,function(v) t.test(v)$conf.int[2])
> library(plotrix)
> barp(heights,ylim=c(0,100),names.arg=month.abb[5:9],
>  main="Air quality
(May-Sep)",xlab="Month",ylab="Temperature")
> dispersion(1:5,y=heights,ulim=upper,llim=lower,intervals=FALSE)
> ci95<-seq(-1.96,1.96,length.out=40)
> norm_curve<-rescale(dnorm(ci95),c(0,0.4))
> for(i in 1:5)
>  polygon(c(i-norm_curve,i+norm_curve),
>   c(heights[i]+ci95*temp_sd[i],heights[i]+rev(ci95*temp_sd[i])))
> 
> Jim
> 
> On Sun, Dec 8, 2019 at 8:18 PM <phil at philipsmith.ca> wrote:
>> >> I want to show little bell curves on my bar chart to
illustrate the
>> >> confidence ranges. The following example from Paul
Teetor's "R
>> >> Cookbook"
>> >> does what I want, but shows I-beams instead of bell curves.
The
>> >> I-beams
>> >> suggest uniform, rather than normal distributions. So I am
looking
>> >> for a
>> >> way to plot normal distribution curves instead.