
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: ruipbarradas@sapo.pt
> To: eliza_botto@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: mackay@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: mackay@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: dwinsemius@comcast.net
> >>>> To: eliza_botto@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.
 		 	   		  
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