# [R] graph

Greg Snow 538280 at gmail.com
Thu Jun 26 20:50:53 CEST 2014

```Does this do what you want?

d1 <- density(mu1)
d2 <- density(mu2)
d3 <- density(mu3)
d4 <- density(mu4)

matplot( cbind( d1\$x, d2\$x, d3\$x, d4\$x ), cbind( d1\$y, d2\$y, d3\$y,
d4\$y ), type='l')

Or in a more expandable way:

mus <- mget( ls(pat='^mu') )
ds <- lapply( mus, density )
xs <- sapply( ds, `[[`, "x" )
ys <- sapply( ds, `[[`, "y" )
matplot(xs,ys, type='l')

You could also combine the data into a single data frame and use
lattice or ggplot2 tools to create a similar graph.

If not, then please give more details on what you want, what the graph
should look like, what you have tried and how it differs from what you
want.

On Thu, Jun 26, 2014 at 12:47 AM, IZHAK shabsogh <ishaqbaba at yahoo.com> wrote:
> kindly guide me on how i can plot the following data on the same graph using the kernel density. i will like to use as to compare performance
>
> mu1<-c(500.0035, 501.2213, 500.7532, 500.2622, 500.3391, 500.1618, 499.9511, 500.1843, 499.8945, 499.8467)
> mu2<-c(498.9623, 504.7938, 506.8957, 495.6634, 506.2751, 503.4344, 503.9103, 512.3021,492.3065, 500.8908)
> mu3<-c(498.9352, 501.3470, 506.7885, 497.3446, 505.6911, 500.0000, 503.9103, 512.0994,492.3065, 500.0001)
> mu4<-c(498.5626, 501.3469, 506.7781, 497.3466, 505.6723, 500.0000, 503.9103, 512.0936,492.3065, 500.0000)
>
>
> thanks
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