R help - Mar 2007 - distribution graph

I am looking for a way to produce a "distribution graph" as in the
example:

(http://cecsweb.dartmouth.edu/release1.1/datatools/dgraph.php?year=2003&geotype=STD_HRR&event=A01_DIS&eventtype=UTIL

Anybody who can help?

Christian von Plessen
Department of Pulmonary Medicine
Haukeland university hospital 
Bergen
Norway

?violinplot (You need to install the UsingR package first.)

On Mar 23, 2007, at 4:06 AM, Plessen, Christian von wrote:
> I am looking for a way to produce a "distribution graph" as in
the
> example:
>
> (http://cecsweb.dartmouth.edu/release1.1/datatools/dgraph.php? 
> year=2003&geotype=STD_HRR&event=A01_DIS&eventtype=UTIL
>
> Anybody who can help?

[Apologies -- there were errors in the code I posted previously.
 A corrected version is below]

On 23-Mar-07 11:06:49, Plessen, Christian von wrote:
> 
> I am looking for a way to produce a "distribution graph" as in
the
> example: 
> 
>
(http://cecsweb.dartmouth.edu/release1.1/datatools/dgraph.php?year=2003&
> geotype=STD_HRR&event=A01_DIS&eventtype=UTIL
> 
> Anybody who can help?
> 
> Christian von Plessen
> Department of Pulmonary Medicine
> Haukeland university hospital 
> Bergen
> Norway
The following (which anyway needs refinement, and can very
probably be done better) provides a basis (illustrated using
a sample from a log-normal distribution):


X<-exp(rnorm(200,sd=0.25)+2)/5

H<-hist(X,breaks=20)
C<-H$counts
Y<-H$mids
C1<-C/2

C0<-(-(C1[1]-1/2)):(C1[1]-1/2); n0<-length(C0)
plot(C0,rep(Y[1],n0),xlim=c(-max(C)/2,max(C)/2),ylim=c(min(Y),max(Y)))

for(i in (2:length(Y))){
  if(C[i]==0) next
  C0 <- (-(C1[i] - 1/2)):(C1[i] - 1/2); n0<-length(C0)
  points(C0,rep(Y[i],n0))
}


Hoping this helps!
Ted.

--------------------------------------------------------------------
E-Mail: (Ted Harding) <ted.harding at nessie.mcc.ac.uk>
Fax-to-email: +44 (0)870 094 0861
Date: 23-Mar-07                                       Time: 13:04:51
------------------------------ XFMail ------------------------------

--------------------------------------------------------------------
E-Mail: (Ted Harding) <ted.harding at nessie.mcc.ac.uk>
Fax-to-email: +44 (0)870 094 0861
Date: 23-Mar-07                                       Time: 14:22:50
------------------------------ XFMail ------------------------------

On Fri, 2007-03-23 at 14:22 +0000, ted.harding at nessie.mcc.ac.uk
wrote:
> [Apologies -- there were errors in the code I posted previously.
>  A corrected version is below]
> 
> On 23-Mar-07 11:06:49, Plessen, Christian von wrote:
> > 
> > I am looking for a way to produce a "distribution graph" as
in the
> > example: 
> > 
> >
(http://cecsweb.dartmouth.edu/release1.1/datatools/dgraph.php?year=2003&
> > geotype=STD_HRR&event=A01_DIS&eventtype=UTIL
> > 
> > Anybody who can help?
> > 
> 
> The following (which anyway needs refinement, and can very
> probably be done better) provides a basis (illustrated using
> a sample from a log-normal distribution):
> 
> 
> X<-exp(rnorm(200,sd=0.25)+2)/5
> 
> H<-hist(X,breaks=20)
> C<-H$counts
> Y<-H$mids
> C1<-C/2
> 
> C0<-(-(C1[1]-1/2)):(C1[1]-1/2); n0<-length(C0)
> plot(C0,rep(Y[1],n0),xlim=c(-max(C)/2,max(C)/2),ylim=c(min(Y),max(Y)))
> 
> for(i in (2:length(Y))){
>   if(C[i]==0) next
>   C0 <- (-(C1[i] - 1/2)):(C1[i] - 1/2); n0<-length(C0)
>   points(C0,rep(Y[i],n0))
> }
> 
> 
> Hoping this helps!
> Ted.

How about something like this:


DistPlot <- function(x, digits = 1, ...)
{
  x <- round(x, digits)
  
  Tab <- table(x)

  Vals <- sapply(Tab, function(x) seq(x) - mean(seq(x)))

  X.Vals <- unlist(Vals, use.names = FALSE)
  tmp <- sapply(Vals, length)
  Y.Vals <- rep(names(tmp), tmp)

  plot(X.Vals, Y.Vals, ...)
}


Vec <- exp(rnorm(200, sd = 0.25) + 2) / 5

DistPlot(Vec, pch = 19)



HTH,

Marc Schwartz