[R] Plotting Confidence Intervals into a density plot

[Jim Lemon]

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.mitova at 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 <dwinsemius at comcast.net>
> wrote:
>
>>
>> > On Dec 1, 2016, at 12:10 PM, Elysa Mitova <elysa.mitova at 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]]
>
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