R help - Sep 2006 - Can't mix high level and low level plot functions.

Hey R-Comunity,


I'd like to print out an histogram of some experimental data and add a
smooth curve of a normal distribution with an ideally generated
population having the same mean and standard deviation like the
experimental data.


The experimental data is set as vector x and its name is set to
group.name. I paint the histogram as follows:

hist(data, freq=FALSE, col="lightgrey", ylab="Density",
xlab=group.name)



First I did the normal distribution curve this way:

lines(x, dnorm(x, mean=mean(x), sd=sd(x)), type="l", lwd=2)

This curve just uses as many values as there are in x. When using small
amounts of sample populations the curve looks really shaky.



I tried this one using a high level plot function as well:

curve(dnorm, n=10000, add=TRUE, xlim=range(x))

The advantage is, now I can set an ideal population of 10000 to get the
ideal curve really smooth. But the big disadvantage is, I don't know how
to add "mean=mean(x),  sd=sd(x)" arguments to it? It says that it
can't
mix high level with low level plot functions when I try to set some kind
of parameter like "n=10000" to the low level function, it says that
there ain't enough x values.

So my question is, how to get a smooth curve placed of dnorm over an
histogram of sample data, ideally by using the curve method?


TIA,
Lothar Rubusch

On 9/25/2006 1:56 PM, Lothar Botelho-Machado wrote:
> Hey R-Comunity,
> 
> 
> I'd like to print out an histogram of some experimental data and add a
> smooth curve of a normal distribution with an ideally generated
> population having the same mean and standard deviation like the
> experimental data.
> 
> 
> The experimental data is set as vector x and its name is set to
> group.name. I paint the histogram as follows:
> 
> hist(data, freq=FALSE, col="lightgrey", ylab="Density",
xlab=group.name)
> 
> 
> 
> First I did the normal distribution curve this way:
> 
> lines(x, dnorm(x, mean=mean(x), sd=sd(x)), type="l", lwd=2)
> 
> This curve just uses as many values as there are in x. When using small
> amounts of sample populations the curve looks really shaky.
This is generally the right way to do it, but you likely want to use a 
different variable for the first two occurrences of x, e.g.

x0 <- seq(from=min(x), to=max(x), len=200)
lines(x0, dnorm(x0, mean=mean(x), sd=sd(x)), type="l", lwd=2)

Duncan Murdoch
> 
> 
> I tried this one using a high level plot function as well:
> 
> curve(dnorm, n=10000, add=TRUE, xlim=range(x))
> 
> The advantage is, now I can set an ideal population of 10000 to get the
> ideal curve really smooth. But the big disadvantage is, I don't know
how
> to add "mean=mean(x),  sd=sd(x)" arguments to it? It says that it
can't
> mix high level with low level plot functions when I try to set some kind
> of parameter like "n=10000" to the low level function, it says
that
> there ain't enough x values.
> 
> So my question is, how to get a smooth curve placed of dnorm over an
> histogram of sample data, ideally by using the curve method?
> 
> 
> TIA,
> Lothar Rubusch
> 
> ______________________________________________
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http://www.R-project.org/posting-guide.html
> and provide commented, minimal, self-contained, reproducible code.

On Mon, 2006-09-25 at 19:56 +0200, Lothar Botelho-Machado
wrote:
> Hey R-Comunity,
> 
> 
> I'd like to print out an histogram of some experimental data and add a
> smooth curve of a normal distribution with an ideally generated
> population having the same mean and standard deviation like the
> experimental data.
> 
> 
> The experimental data is set as vector x and its name is set to
> group.name. I paint the histogram as follows:
> 
> hist(data, freq=FALSE, col="lightgrey", ylab="Density",
xlab=group.name)
> 
> 
> 
> First I did the normal distribution curve this way:
> 
> lines(x, dnorm(x, mean=mean(x), sd=sd(x)), type="l", lwd=2)
> 
> This curve just uses as many values as there are in x. When using small
> amounts of sample populations the curve looks really shaky.
> 
> 
> 
> I tried this one using a high level plot function as well:
> 
> curve(dnorm, n=10000, add=TRUE, xlim=range(x))
> 
> The advantage is, now I can set an ideal population of 10000 to get the
> ideal curve really smooth. But the big disadvantage is, I don't know
how
> to add "mean=mean(x),  sd=sd(x)" arguments to it? It says that it
can't
> mix high level with low level plot functions when I try to set some kind
> of parameter like "n=10000" to the low level function, it says
that
> there ain't enough x values.
> 
> So my question is, how to get a smooth curve placed of dnorm over an
> histogram of sample data, ideally by using the curve method?
> 
> 
> TIA,
> Lothar Rubusch
This almost seems like it should be a FAQ. I also checked the R Graphics
Gallery (http://addictedtor.free.fr/graphiques/index.php) and didn't see
an example there either, unless I missed it.

In either case:

x <- rnorm(50)

hist(x, freq = FALSE)

# Create a sequence of x axis values with small
# increments over the range of 'x' to smooth the lines
x.hypo <- seq(min(x), max(x), length = 1000)

# Now use lines()
lines(x.hypo, dnorm(x.hypo, mean=mean(x), sd=sd(x)), type="l", lwd=2)

HTH,

Marc Schwartz