Stewart,

I am replying to the graphical part of your query.

## This was constructed with
##       dump("scriptham2","")
## sso it can be copied directly from the email into an R session.


scriptham2 <-
structure(list(size = c(2500, 2000, 1700, 1400, 1000, 800, 600,
300, 180, 100), mass = c(0, 0.2, 1.8, 5, 13, 40, 20, 15, 3, 2
)), .Names = c("size", "mass"), row.names = c(NA, 10L), class =
"data.frame")


xyplot(mass ~ size, data=scriptham2,
       scales=list(x=list(log=TRUE)),
       horizontal=FALSE, panel=panel.barchart, box.width=.05, origin=0)


xyplot(mass ~ size, data=scriptham2,
       scales=list(x=list(log=TRUE)),
       type="b", pch=16)

I think you are asking for the first graph.  I also think that a line
graph, as in the second graph,
is more appropriate for this type of data.

I arbitrarily assigned the "<180" to 100, as it has to have a numerical
value on the x-axis.

Rich
On Wed, Nov 23, 2011 at 10:50 AM, scriptham2 <stewart.porteous@permarock.com
> wrote:

> Hi
>
> I would like to plot bar charts in a particular way. The intervals are not
> evenly distributed and are in a data frame column called size and the
> relative frequencies are in a second column called mass. Both size and mass
> are continuous ratio data to all intents and purposes. The data actually
> represents sieving of sand where $size is sieve aperture and where $mass is
> the amount remaining on the sieve.
>
> So if I sieve 100g of sand through increasingly fine sieves nothing remains
> on the coarsest sieve say 2500 microns. Between 2000 and 2500 microns there
> is 0.2g remining on the 2000micron sieve etc. as per the data supplied.
>
> size, mass
> 2500, 0
> 2000, 0.2
> 1700, 1.8
> 1400, 5
> 1000, 13
> 800, 40
> 600, 20
> 300, 15
> 180, 3
> <180, 2
>
> The data here I have made up for simplicity. In general sands tend to be
> distributed as lognormal curves and mixtures of sands are combined as the
> mixture of 2 or more lognormal distributions.
>
> I would like to fit 2, 3 or preferably 4 parameter log normal distributions
> and plot these cumulative distributions on the charts.
>
> The problems are: I can't seem to find how to do the bar charts in R and
> I have not found in the past how to fit 3 or 4 parameter log normal
> cumulative distributions in R
>
> Please help.
> Thanks
> Scriptham
>
> --
> View this message in context:
> http://r.789695.n4.nabble.com/Bar-charts-frequencies-known-intervals-of-varying-width-tp4100114p4100114.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<http://www.r-project.org/posting-guide.html>
> and provide commented, minimal, self-contained, reproducible code.
>

	[[alternative HTML version deleted]]

