Dear Rui Barradas, Mackay and all R Users,
Thankyou
very much for your reply. You helped me a lot. I got what I wanted. I just want
one more favor from you, if you could.
Suppose
I have certain number of lists of data frame, say 50. Each list has yearly data
in it. Of-course, some lists have 365 readings and some have 366(due to leap
year). Now I want to split lists into two different matrices, one containing
leap years and other with normal years.
I
hope you will be kind enough to help me as you did before.
Eliza
Botto
Waters
Inn
> Date: Mon, 4 Jun 2012 10:51:49 +0100
> From: ruipbarra...@sapo.pt
> To: eliza_bo...@hotmail.com
> CC: r-help@r-project.org
> Subject: Re: [R] Variate
>
> Hello,
>
> Sorry for not understanding your problem, but it really seemed like
> homework.
>
> Now, when I answered scale(x) I meant it, it transforms a matrix in (x -
> mean)/sd, column by column.
> If you're new to R, to use the on-line help the instruction is
>
> help("scale")
> ?scale # shortcut
>
>
> As for your graph, I agree with Duncan, 92 lines on the same graph
> doesn't seem to be a good idea. Anyway, using base R, it could be done
> along the lines of
>
> set.seed(1)
> nc <- 92 # number of columns
> nr <- 366 # number of rows
> x <- matrix(rexp(nr*nc), ncol=nc)
>
> x1 <- scale(x) # "z", standard normal (in fact, studentized)
> y1 <- apply(x, 2, plnorm) # log-normal
>
> colrs <- rainbow(nc)
> plot(1, type="n", xlim=c(min(x1), max(x1)), ylim=c(min(y1), max(y1)),
> xlab="", ylab="")
>
> # if you want lines
> sapply(seq_len(nc), function(j){
> i <- order(x1[, j])
> lines(x1[i, j], y1[i, j], col=colrs[j])})
>
> # if you want points
> sapply(seq_len(nc), function(j) points(x1[, j], y1[, j], col=colrs[j],
> pch="."))
>
>
> Hope this helps,
>
> Rui Barradas
>
> Em 04-06-2012 07:38, eliza botto escreveu:
> > Dear Mc kay,
> > thankyou very much for your reply. we are extremly greatful to you. we
> > actually wanted all on one scale. we want to compare them all on one axis.
> > kindle see if you could help us on that. one more thing, does this practice
> > give us normal reduced variant on x-axis because we stricktly want normal
> > reduced variant on x-axis.
> > i hope you will cooperate.
> >
> > eliza botto
> > waters inn
> >
> >> Date: Mon, 4 Jun 2012 11:54:11 +1000
> >> To: r-help@r-project.org
> >> From: mac...@northnet.com.au
> >> Subject: Re: [R] Variate
> >>
> >> 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: mac...@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@r-project.org
> >>>> From: dwinsem...@comcast.net
> >>>> To: eliza_bo...@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@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.
> >> ______________________________________________
> >> 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.
> >
> > [[alternative HTML version deleted]]
> >
> > ______________________________________________
> > 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.
[[alternative HTML version deleted]]
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