[R] Variate
Duncan Mackay
mackay at northnet.com.au
Mon Jun 4 03:54:11 CEST 2012
Hi Eliza
You will not want 1 panel with 96 lines - too confusing after about 20
Instead 1 per panel or with groups using useOuterStrips and
combineLimits from latticeExtra package
Try this -- a minimal example with an 12 row 8 col grid done on the fly
setseed(12)
Sites <- 1:92
dat <-
data.frame(y = rep(rnorm(5),92), x = rep(1:5,92), site = rep(Sites,each = 5))
xyplot(y ~ x|site,dat,
as.table=T,
strip = F,
layout = c(8,12),
scales = list(x = list(alternating = 2),y=list(alternating=1)),
type = "b",
panel = function(x,y,...){
pnl=panel.number()
panel.xyplot(x,y,...)
panel.text(4,-1.5,Sites[pnl], cex = 0.6)
}
)
or with groupings for Site something like (untested)
xyplot(y ~ x|groupings,dat,
as.table=T,
strip = F,
strip.left = T,
groups = site,
scales = list(x = list(alternating = 2),y=list(alternating=1)),
type = "b",
panel = function(x,y,...){
pnl=panel.number()
panel.xyplot(x,y,...)
panel.text(4,-1.5,Sites[pnl], cex = 0.6)
}
)
You will need an extra column for groupings
This can also be done with the base plot function but lattice gives
more flexibility, see ?xyplot and particularly par.settings into
get things right size
Regards
Duncan
Duncan Mackay
Department of Agronomy and Soil Science
University of New England
Armidale NSW 2351
Email: home: mackay at northnet.com.au
At 11:01 4/06/2012, you wrote:
>Content-Type: text/plain
>Content-Disposition: inline
>Content-length: 2431
>
>
>
>
>Dear
>R users,
>
>We
>are working on a project called,"Environmental Impact Assessment".
>We are stationed
>at alpine regions of Ireland to see the impact of rainfall on
>localities. We have
>divided our study area into 92 stations. We have also collected 1 year data
>from each station. Afterwards we placed data into a matrix in such a way that
>we got 366*92 matrix. 366 stands for number of days.
>
>What
>we want is a lognormal probability plot, of each station(which is individual
>column of matrix) with normal reduced variant on x-axis. In this
>way, we should
>be getting, at the end, 92 curves, one for each station, on same coordinate
>axis.
>
>Kindly
>help us on that. We are all very new to R.
>
>
>
>Eliza
>botto
>
>Waters
>Inn
>
>
>
> > CC: r-help at r-project.org
> > From: dwinsemius at comcast.net
> > To: eliza_botto at hotmail.com
> > Subject: Re: [R] Log-normal probability plot
> > Date: Sun, 3 Jun 2012 13:11:35 -0400
> >
> >
> > On Jun 2, 2012, at 9:38 PM, eliza botto wrote:
> >
> > You might consider the strategy of reading the Posting Guide, followed
> > by posting an intelligible message.
> >
> > >
> > > Dear R users,
> > >
> > > You can literally safe my
> > > life my telling me the solution of my problem. I have created matrix
> > > of a data
> > > frame with 3 columns, with each column representing data of
> > > different year.
> > >
> > > 2
> > ...snipped useless srting of numbers mangled by mailer processing of
> > HTML.
> >
> > > 4
> > >
> > >
> >
> > > I now want to plot "Lognormal
> > > probability plot" of each column data against its respective "normal
> > > reduced
> > > variante(z)".
> >
> > "Normal reduced variate"? What is that? Is it a set of numbers that
> > have been centered and scaled, also known as a z-transform? If so, I
> > do not think it should affect the results of a probability plot since
> > it is just a linear transformation and the theoretical quantiles will
> > be unaffected.
> >
> > You might look at qqplot()
> >
> > >
> > > How to do that?
> >
> > >
> > > If you don't know the
> > > answer, consider me dead.
> >
> > What greater lifesaving project are you trying to accomplish, ....
> > other than getting homework done?
> > >
> > > [[alternative HTML version deleted]]
> >
> >
> > --
> > David Winsemius, MD
> > West Hartford, CT
> >
>
> [[alternative HTML version deleted]]
>
>
>______________________________________________
>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.
More information about the R-help
mailing list