There's nothing wrong with leaving in buggy code when there's a bug that you
just can't get (assuming it's part of your real code): I only ask for the
error message because it saves us a little bit of time if you can let us
know what errors you are getting.

Anyways, best of luck,

Michael

On Thu, Aug 25, 2011 at 3:02 PM, Rikke Knold Christensen <
lille_knold@hotmail.com> wrote:

>  Hi Michael
>
> Thank you for the quick response, it works perfectly now!
>
> You are quite right, I did get an error for the curve function, but I chose
> to insert it in the code anyway, to show what I was trying to do (wrong) in
> the y function. But you are right, it would have been more correct to show
> what I was trying to do with the line().
> Thank you for explaining and helping me with this small problem
>
> Kinds Rikke
>
> ------------------------------
> From: michael.weylandt@gmail.com
> Date: Thu, 25 Aug 2011 14:37:59 -0400
> Subject: Re: [R] Adding a normal density curve over the empirical curve
> To: lille_knold@hotmail.com
> CC: r-help@r-project.org
>
> I'm not going to download your data since it's probably irrelevant to your
> problem and I have no interest in downloading unknown files.
>
> Consider this instead:
>
> library(quantmod)
> SPY = getSymbols("SPY",auto.assign=F)
> SPY = weeklyReturn(Ad(SPY))
>
> densitySPY = density(SPY)
> plot(densitySPY,main="Kernel Density")
>
> x = seq(min(SPY),max(SPY),length=300)
> y = dnorm(x,mean=mean(SPY),sd = sd(SPY))
> lines(x,y,col=2)
>
> As you can see, for this data, the normal distribution is not a good fit
> for data with excess kurtosis 6. dnorm is the pdf for the normal
> distribution, it makes no sense to put normal random samples in it like you
> did in your code: just put in an independent variable like you would for any
> function.
>
> The problem with your code is that you hand it "curve" which expects a
> function of x, but you give just a set of points with no reference to any x.
> Better to work with plot directly and only use curve for getting a feel for
> a function, rather than "official" plots. Lines can be used to add
> additional lines to a plot.
>
> Also, I'd almost guarantee that this error was reported when you called
> curve; please mention that in your future posts.
>
> If this doesn't solve your problem, use dput() to give a sample of your
> data in a follow-up.
>
> Michael
>
> On Thu, Aug 25, 2011 at 12:45 PM, Newbie <lille_knold@hotmail.com> wrote:
>
> Hi
>
> I have created the following plot over the empirical returns.. What I now
> want to do is to overlay a curve/line with the normal density as a
> comparison of the two. Does anyone know how to do this?
> (NB the last two lines are the problem, and are wrong, I know).
>
> Thank you in advance!
> Rikke
>
> http://r.789695.n4.nabble.com/file/n3768783/S%26P_500_spot_and_return_2010.csv
> S%26P_500_spot_and_return_2010.csv
>
> setwd("F:/Data til speciale/")
>
> marketdata <- read.csv(file="S&P 500 spot and return 2010.csv",
> header=TRUE,
> sep=";")
> returns <- marketdata[,7]
>
> ### Kernel density estimator ###########################
>
> x <- density (returns)
>
> plot(density(returns), main = "Kernel density")
> y <- rnorm(209,mean=0,sd=1)
> curve(dnorm(y,mean=mean(normal1),sd=sd(normal1)))
>
> --
> View this message in context:
> http://r.789695.n4.nabble.com/Adding-a-normal-density-curve-over-the-empirical-curve-tp3768783p3768783.html
> Sent from the R help mailing list archive at Nabble.com.
>
> ______________________________________________
> R-help@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.
>
>
>

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