[R] hist(x, ...) with normal distribution curve

[Peter Dalgaard]

Knut Krueger <Knut.Krueger at usa.com> writes:

> Petr Pikal schrieb:
> 
> >Hi
> >
> >answered hundered times.
> >
> >  
> >
> >>Dear R people: 
> >>
> >>I would like to superimpose a normal curve on a histogram. 
> >>    
> >>
> >x<-rnorm(150) 
> >h<-hist(x,breaks=15) 
> >xhist<-c(min(h$breaks),h$breaks) 
> >yhist<-c(0,h$density,0) 
> >xfit<-seq(min(x),max(x),length=40) 
> >yfit<-dnorm(xfit,mean=mean(x),sd=sd(x)) 
> >plot(xhist,yhist,type="s",ylim=c(0,max(yhist,yfit))) 
> >lines(xfit,yfit) 
> >
> >
> >Bill 
> >
> >above is e.g. Bill Simpson's answer from 2001. Found from R-site 
> >search  ***histogram density normal***.
> >  
> >
> Ok If I merge both of your answers I get the graph like in SPSS but
> the ylab is density instead frequency:

Many people consider that a feature, since histograms are supposed to
be density estimates....

> and I do not have the clicks in SPSS to redo the same graph :-(
> I hav only the Data file and the SPSS plot.
> 
> 
> x<-5+rnorm(150) 
> 
> h<-hist(x,breaks=10,freq = TRUE) 
> #I need this histogramm  with...
> 
> xfit<-seq(min(x),max(x),length=40) 
> yfit<-dnorm(xfit,mean=mean(x),sd=sd(x)) 
> 
> lines(xfit,yfit) 
> 
> 
> 
> h<-hist(x,breaks=10,prob=T) 
> 
> xfit<-seq(min(x),max(x),length=40) 
> yfit<-dnorm(xfit,mean=mean(x),sd=sd(x)) 
> # ... this line 
> lines(xfit,yfit)


Er, something got duplicated in there? 

Anyways, if you want the normal curve blown up to the scale of
counts/bin, just multiply yfit by the number of observations times the
bin width.

To find the bin width take, e.g. diff(h$mids[1:2]). If they're not all
equal, then you're in deeper trouble.


-- 
   O__  ---- Peter Dalgaard             Øster Farimagsgade 5, Entr.B
  c/ /'_ --- Dept. of Biostatistics     PO Box 2099, 1014 Cph. K
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