histogram-like plot with two variables

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Try:

plot(x,y,type='s')
lines(x,y, type='h')
Hi,

I want to plot a binomial propability distribution.

I know how to generate the data;

  x <- seq(from=0, to=14, by=1)
  y <- dbinom(x, 14, 0.7, log = FALSE)

but what I don't know is how to plot this within a histogram like plot.
Because the histogram function only accepts one variable.

Is there a way to get the look of "hist()" with two variables?

I tried:
plot(x,y, type="h")
 but the bars are very thin -is there a way to define the width?

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Jim Holtman
Cincinnati, OH
+1 513 646 9390

What is the problem that you are trying to solve?
Hi,

I want to plot a binomial propability distribution.

I know how to generate the data;

   x <- seq(from=0, to=14, by=1)
   y <- dbinom(x, 14, 0.7, log = FALSE)

but what I don't know is how to plot this within a histogram like plot.
Because the histogram function only accepts one variable.

Is there a way to get the look of "hist()" with two variables?

I tried:
plot(x,y, type="h")
  but the bars are very thin -is there a way to define the width?
You could use barplot():

barplot(y,names=x)

You could also do it with plot.histogram, but it's trickier, because 
it's designed for continuous data.  For example,

dat <- hist(x, plot=FALSE, breaks=c(-1,x)+0.5)
dat$density <- y
plot(dat, freq=FALSE)

Duncan Murdoch
Hi,

I want to plot a binomial propability distribution.

I know how to generate the data;

   x <- seq(from=0, to=14, by=1)
   y <- dbinom(x, 14, 0.7, log = FALSE)

but what I don't know is how to plot this within a histogram like plot.
Because the histogram function only accepts one variable.

Is there a way to get the look of "hist()" with two variables?

I tried:
plot(x,y, type="h")
  but the bars are very thin -is there a way to define the width?

Hi Jorg,
Does this do what you want?

library(plotrix)
barp(y,names.arg=0:14)

Jim
Hi,

I want to plot a binomial propability distribution.

I know how to generate the data;

   x <- seq(from=0, to=14, by=1)
   y <- dbinom(x, 14, 0.7, log = FALSE)

I tried:
plot(x,y, type="h")
  but the bars are very thin -is there a way to define the width?
yes - the lwd parameter controls line width. E.g.:

plot(x,y, type='h', lwd=5)

This is the way I usually plot count data - I prefer this over something
that looks like a normal histogram, because it reminds me that I am
looking at discrete values.

cu
	Philipp
Dr. Philipp Pagel
Lehrstuhl f?r Genomorientierte Bioinformatik
Technische Universit?t M?nchen
Wissenschaftszentrum Weihenstephan
85350 Freising, Germany
http://mips.gsf.de/staff/pagel
An added note, if you use this approach, then you should probably set the lend parameter as well (becomes more important with wider lines).  See ?par and scroll down to lend for options/details.

--
Gregory (Greg) L. Snow Ph.D.
Statistical Data Center
Intermountain Healthcare
greg.snow at imail.org
801.408.8111
-----Original Message-----
From: r-help-bounces at r-project.org [mailto:r-help-bounces at r-
project.org] On Behalf Of Philipp Pagel
Sent: Monday, September 29, 2008 5:40 AM
To: r-help at r-project.org
Subject: Re: [R] histogram-like plot with two variables

On Mon, Sep 29, 2008 at 04:02:05AM +0200, J?rg Gro? wrote:
Hi,

I want to plot a binomial propability distribution.

I know how to generate the data;

   x <- seq(from=0, to=14, by=1)
   y <- dbinom(x, 14, 0.7, log = FALSE)

I tried:
plot(x,y, type="h")
  but the bars are very thin -is there a way to define the width?
yes - the lwd parameter controls line width. E.g.:

plot(x,y, type='h', lwd=5)

This is the way I usually plot count data - I prefer this over
something
that looks like a normal histogram, because it reminds me that I am
looking at discrete values.

cu
        Philipp

--
Dr. Philipp Pagel
Lehrstuhl f?r Genomorientierte Bioinformatik
Technische Universit?t M?nchen
Wissenschaftszentrum Weihenstephan
85350 Freising, Germany
http://mips.gsf.de/staff/pagel

______________________________________________
R-help at r-project.org mailing list
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.