dear rui,
lots of hugs for you.
thnkyou very much 4 your support.
eliza
> Date: Mon, 4 Jun 2012 22:58:12 +0100
> From: ruipbarra...@sapo.pt
> To: eliza_bo...@hotmail.com
> CC: r-help@r-project.org
> Subject: Re: Spliting Lists into matrices
>
> Hello,
>
> Try
>
> # 'x' is your list
> xlen <- sapply(x, length)
> i1 <- which(xlen == 365)
> i2 <- which(xlen == 366)
>
> mat365 <- matrix(unlist(x[i1]), nrow=365)
> mat366 <- matrix(unlist(x[i2]), nrow=366)
>
>
> Hope this helps,
>
> Rui Barradas
>
> Em 04-06-2012 22:46, eliza botto escreveu:
> > i realy appreciate your concern..
> > here is a small piece of my data. if you see the first and last part data,
> > they contain 366 entries but the middle one has 365 entries. i want to put
> > first and last entries is one matrix.
> >
> > list(c(0.86, 0.86, 0.86, 0.86, 0.86, 1.08, 1.08, 1.08, 1.08,
> > 1.08, 1.08, 1.4, 1.4, 23, 11.18, 38.83, 23, 3.45, 3.45, 3.45,
> > 3.45, 3.45, 3.45, 3.45, 3.45, 3.02, 2.58, 2.58, 2.15, 2.15, 2.15,
> > 2.15, 2.15, 2.15, 2.15, 2.15, 3.02, 1.72, 1.72, 1.72, 1.72, 1.72,
> > 1.72, 1.72, 1.72, 1.6, 1.6, 1.6, 1.6, 1.6, 1.6, 1.6, 1.6, 1.6,
> > 1.6, 1.6, 1.6, 1.6, 1.6, 1.6, 1.6, 1.6, 1.6, 1.6, 1.6, 1.6, 1.6,
> > 1.6, 1.6, 1.6, 2.4, 2.4, 2.4, 2.4, 2.4, 2.4, 2.4, 2.8, 2.8, 2.8,
> > 4.1, 4.1, 13.55, 9.34, 8.32, 7.31, 4.5, 4.1, 14.63, 24.88, 39.99,
> > 23.69, 14.63, 7.31, 4.5, 7.31, 16.82, 21.35, 24.88, 20.2, 24.88,
> > 26.07, 30.98, 49.58, 51.01, 26.07, 24.88, 30.98, 34.77, 58.26,
> > 30.98, 23.69, 26.07, 19.06, 16.82, 20.2, 16.82, 23.69, 14.63,
> > 16.82, 11.42, 11.42, 11.42, 11.42, 10.38, 10.38, 8.32, 7.31,
> > 6.31, 16.82, 6.31, 6.31, 6.31, 4.9, 4.9, 4.5, 4.5, 4.5, 4.5,
> > 4.5, 4.1, 4.1, 2.8, 2.4, 2.4, 26.07, 45.4, 16.82, 7.31, 4.5,
> > 3.2, 3.2, 2.8, 2.8, 2.4, 2.4, 2.8, 3.2, 3.2, 4.9, 4.9, 36.05,
> > 65.8, 76.86, 53.87, 26.07, 20.2, 21.36, 14.63, 10.38, 10.38,
> > 7.31, 7.31, 51.01, 16.82, 14.63, 12.48, 14.63, 10.38, 11.42,
> > 52.44, 64.27, 36.05, 26.07, 21.36, 21.36, 23.69, 47.79, 52.44,
> > 167.9, 97.12, 76.86, 144.71, 90.18, 34.77, 30.98, 28.5, 26.07,
> > 26.07, 14.63, 14.63, 6.31, 6.31, 6.31, 4.5, 4.1, 3.2, 6.31, 6.31,
> > 16.82, 4.5, 3.2, 3.2, 3.2, 3.2, 4.5, 8.32, 10.38, 10.38, 8.32,
> > 11.42, 10.38, 7.31, 6.31, 6.31, 6.31, 6.31, 6.31, 6.31, 6.31,
> > 8.32, 6.31, 6.31, 20.2, 14.63, 7.31, 4.9, 34.77, 26.07, 14.63,
> > 10.38, 6.31, 4.9, 7.31, 4.9, 4.5, 4.5, 4.5, 21.36, 12.48, 7.31,
> > 4.5, 4.5, 6.31, 4.9, 4.9, 6.31, 8.32, 7.31, 6.31, 6.31, 14.63,
> > 11.42, 6.31, 6.31, 4.9, 6.31, 14.63, 7.31, 12.48, 6.31, 6.31,
> > 24.88, 15.72, 33.49, 111.57, 44.03, 39.99, 44.03, 24.88, 12.48,
> > 39.99, 11.42, 7.31, 4.9, 4.5, 4.1, 4.5, 4.1, 4.1, 3.2, 3.2, 3.2,
> > 3.2, 3.2, 2.8, 2.8, 3.2, 3.2, 3.2, 3.2, 3.2, 3.2, 3.2, 2.8, 2.8,
> > 3.2, 2.8, 2.8, 2.8, 2.8, 2.8, 2.8, 2.8, 2.8, 2.8, 2.8, 2.8, 2.8,
> > 4.1, 4.1, 2.4, 3.2, 10.38, 8.32, 4.5, 3.2, 3.2, 2.8, 3.2, 3.2,
> > 3.2, 2.4, 2.4, 2.4, 15.72, 23.69, 12.48, 14.63, 4.5, 4.1, 4.5,
> > 4.1, 4.1, 4.1, 3.2, 2.8, 2.8, 3.2, 2.8, 2.4, 4.5, 4.5, 12.48,
> > 68.9, 30.98, 39.99, 29.73, 95.37, 44.03, 26.07, 41.33, 49.58,
> > 23.69, 28.5), c(16.82, 14.63, 6.31, 6.31, 4.5, 4.5, 4.1, 4.1,
> > 4.1, 3.2, 3.2, 4.1, 3.2, 3.2, 4.1, 4.5, 4.1, 4.1, 167.9, 75.24,
> > 44.03, 23.69, 19.06, 15.72, 11.42, 8.32, 6.31, 4.9, 6.31, 4.9,
> > 4.9, 4.1, 4.1, 3.2, 4.1, 4.1, 4.1, 90.18, 102.45, 39.99, 29.73,
> > 8.32, 21.36, 21.36, 21.36, 12.48, 11.42, 12.48, 11.42, 12.48,
> > 14.63, 14.63, 15.72, 23.69, 28.5, 29.73, 33.49, 29.73, 23.69,
> > 21.36, 6.31, 16.82, 15.72, 15.72, 15.72, 15.72, 16.82, 20.2,
> > 20.2, 21.36, 21.36, 26.07, 28.5, 29.73, 33.49, 29.73, 33.49,
> > 34.77, 26.07, 26.07, 23.69, 23.69, 26.07, 21.36, 23.69, 23.69,
> > 23.69, 24.88, 21.36, 20.2, 16.82, 19.06, 20.2, 21.36, 20.2, 20.2,
> > 24.88, 23.69, 26.07, 29.73, 23.69, 24.88, 29.73, 36.05, 33.49,
> > 34.77, 28.5, 28.5, 26.07, 153, 70.47, 58.26, 81.77, 36.05, 39.99,
> > 30.98, 33.49, 28.5, 28.5, 33.49, 29.73, 28.5, 24.88, 30.98, 38.67,
> > 30.98, 50.01, 65.8, 51.01, 38.67, 34.77, 29.73, 29.73, 33.49,
> > 30.98, 30.98, 30.98, 33.49, 34.77, 33.49, 30.98, 88.48, 14.63,
> > 8.32, 19.06, 14.63, 104.25, 44.03, 33.49, 21.36, 20.2, 15.72,
> > 15.72, 11.42, 7.31, 6.31, 4.9, 4.5, 4.5, 4.5, 3.2, 8.32, 8.32,
> > 14.63, 97.12, 310.8, 88.48, 36.05, 24.88, 19.06, 14.63, 12.48,
> > 8.32, 23.69, 11.42, 19.06, 90.18, 90.18, 33.49, 16.82, 70.47,
> > 38.67, 29.73, 34.77, 33.49, 68.9, 102.45, 176.7, 78.48, 45.4,
> > 106.06, 83.43, 45.4, 68.9, 39.99, 28.5, 23.69, 20.2, 36.05, 38.67,
> > 30.98, 26.07, 20.2, 47.79, 52.44, 28.5, 23.69, 20.2, 14.63, 14.63,
> > 14.63, 12.48, 21.36, 24.88, 47.79, 38.67, 34.77, 21.36, 16.82,
> > 8.32, 153, 47.79, 53.87, 29.73, 23.69, 15.72, 19.06, 97.12, 33.49,
> > 15.72, 10.38, 6.31, 4.5, 11.42, 6.31, 6.31, 6.31, 4.5, 19.06,
> > 14.63, 4.9, 4.9, 28.5, 70.47, 15.72, 4.9, 4.1, 41.33, 241, 85.1,
> > 38.67, 28.5, 20.2, 15.72, 12.48, 12.48, 20.2, 14.63, 12.48, 10.38,
> > 7.31, 7.31, 15.72, 33.49, 20.2, 15.72, 12.48, 8.32, 7.31, 6.31,
> > 4.9, 4.5, 4.1, 4.9, 4.5, 4.9, 20.2, 11.42, 6.31, 4.9, 4.9, 4.9,
> > 4.5, 4.5, 4.5, 4.1, 4.1, 4.1, 4.1, 4.1, 4.1, 4.1, 4.1, 4.1, 6.31,
> > 6.31, 4.5, 4.9, 4.9, 4.5, 4.5, 4.5, 4.9, 4.5, 15.72, 24.88, 4.1,
> > 58.26, 23.69, 26.07, 28.5, 174.5, 58.26, 49.58, 23.69, 23.69,
> > 23.69, 28.5, 26.07, 15.72, 20.2, 26.07, 23.69, 19.06, 21.36,
> > 15.72, 4.1, 4.1, 6.31, 15.72, 24.88, 39.99, 45.4, 23.69, 33.49,
> > 33.49, 33.49, 23.69, 23.69, 20.2, 24.88, 19.06, 23.69, 20.2,
> > 8.32, 6.31, 6.31, 4.1, 4.1, 14.63, 106.06, 51.01, 26.07, 23.69,
> > 20.2, 15.72, 15.72, 12.48, 19.06, 16.82, 14.63, 12.48, 12.48,
> > 11.42, 11.42, 12.2), c(8.32, 8.32, 8.32, 8.32, 8.32, 8.32, 8.32, 8.32,
> > 8.32, 8.32, 8.32, 8.32, 8.32, 7.31, 8.32, 8.32, 8.32, 8.32, 6.31,
> > 6.31, 6.31, 6.31, 6.31, 6.31, 6.31, 6.31, 6.31, 6.31, 6.31, 6.31,
> > 6.31, 6.31, 6.31, 4.5, 4.5, 4.5, 4.5, 4.5, 6.31, 6.31, 4.1, 4.1,
> > 4.1, 4.5, 6.31, 6.31, 6.31, 6.31, 4.9, 10.38, 12.48, 15.72, 8.32,
> > 11.42, 78.48, 65.8, 85.1, 29.73, 26.07, 29.73, 21.36, 26.07,
> > 23.69, 28.5, 15.72, 12.48, 12.48, 14.63, 12.48, 12.48, 8.32,
> > 8.32, 11.42, 6.31, 6.31, 6.31, 4.9, 4.9, 6.31, 10.38, 15.72,
> > 16.82, 19.06, 34.77, 20.2, 20.2, 15.72, 14.63, 33.49, 28.5, 28.5,
> > 28.5, 64.27, 29.73, 20.2, 15.72, 11.42, 11.42, 11.42, 7.31, 4.9,
> > 6.31, 12.48, 10.38, 8.32, 7.31, 14.63, 15.72, 16.82, 20.2, 19.06,
> > 19.06, 28.5, 19.06, 15.72, 28.5, 29.73, 38.67, 20.2, 30.98, 21.36,
> > 14.63, 12.48, 10.38, 47.79, 23.69, 14.63, 10.38, 8.32, 11.42,
> > 11.42, 15.72, 12.48, 11.42, 14.63, 26.07, 23.69, 36.05, 167.9,
> > 44.03, 21.36, 15.72, 12.48, 8.32, 8.32, 8.32, 21.36, 20.2, 15.72,
> > 30.98, 21.36, 15.72, 53.87, 29.73, 21.36, 12.48, 11.42, 10.38,
> > 10.38, 6.31, 39.99, 19.06, 4.1, 2.8, 44.03, 24.88, 11.42, 8.32,
> > 6.31, 78.48, 38.67, 34.77, 19.06, 12.48, 15.72, 15.72, 59.74,
> > 34.77, 21.36, 14.63, 12.48, 11.42, 11.42, 11.42, 10.38, 8.32,
> > 6.31, 6.31, 4.9, 4.9, 4.9, 4.9, 4.1, 4.5, 6.31, 4.1, 4.5, 4.5,
> > 8.32, 6.31, 6.31, 6.31, 6.31, 6.31, 6.31, 6.31, 6.31, 4.9, 4.5,
> > 4.5, 4.5, 4.5, 4.5, 4.5, 4.5, 4.5, 4.5, 4.5, 4.1, 2.8, 2.8, 2.8,
> > 2.8, 2.8, 2.8, 2.4, 2.8, 2.8, 2.8, 2.8, 2.4, 2.8, 2.4, 1.3, 1.3,
> > 1.3, 1.3, 29.73, 21.36, 4.1, 3.2, 2.8, 6.31, 3.2, 3.2, 3.2, 3.2,
> > 3.2, 3.2, 3.2, 3.2, 3.2, 3.2, 3.2, 3.2, 3.2, 3.2, 3.2, 7.31,
> > 8.32, 8.32, 4.1, 3.2, 4.9, 4.1, 23.69, 23.69, 19.06, 11.42, 14.63,
> > 7.31, 4.9, 14.63, 36.05, 28.5, 15.72, 10.38, 12.48, 14.63, 20.2,
> > 14.63, 15.72, 23.69, 10.38, 4.9, 4.1, 3.2, 3.2, 3.2, 3.2, 3.2,
> > 3.2, 3.2, 3.2, 3.2, 3.2, 4.9, 2.8, 2.8, 1.6, 14.63, 7.31, 11.42,
> > 7.31, 3.2, 3.2, 3.2, 3.2, 3.2, 23.69, 4.5, 3.2, 3.2, 3.2, 4.5,
> > 3.2, 3.2, 3.2, 3.2, 3.2, 1.3, 2.8, 4.5, 4.5, 3.2, 3.2, 4.5, 4.5,
> > 11.42, 4.5, 4.5, 4.5, 1.3, 1.3, 1.3, 3.2, 1.6, 2.8, 2.8, 1.3,
> > 2.8, 2.8, 2.8, 2.8, 4.1, 4.1, 4.1, 4.1, 4.1, 7.31, 4.1, 2.8,
> > 2.8, 3.2, 4.1, 4.9, 26.07, 24.88, 15.72, 20.2, 21.36, 30.98,
> > 21.36, 20.2, 19.06, 14.3)
> >
> > thankyou very much..
> > bye
> >
> >> Date: Mon, 4 Jun 2012 22:27:55 +0100
> >> From: ruipbarra...@sapo.pt
> >> To: eliza_bo...@hotmail.com
> >> CC: r-help@r-project.org
> >> Subject: Re: Spliting Lists into matrices
> >>
> >> Hello,
> >>
> >> I'm glad it helped.
> >> To answer to this new question, we need to see what your data looks like.
> >> When you say 'list' are you refering to the type of R data structure
> >> 'list'? Or to data.frames?
> >> For us to see the best way is to use function dput. Example:
> >>
> >>
> >> df1<- data.frame(A=rnorm(10), B=runif(10))
> >> df2<- data.frame(A=rnorm(11), B=runif(11))
> >>
> >> lst1<- list(df1, df2) # a list of data.frames
> >>
> >> dput(lst1) #<----- paste the output of this in a post
> >>
> >>
> >> (If your data.frames are not in a list do NOT create a list just to
> >> post, dput them _as_they_are_.)
> >> Can be dput(df1); dput(df2)
> >> If they are in a list, don't dput the entire list, 50x365 or 366 is
> >> endless, just enough for us to see.
> >>
> >> If you have several (50) data.frames, do they share something such as a
> >> name prefix?
> >> Any information you find relevant, post it.
> >>
> >> Rui Barradas
> >>
> >> Em 04-06-2012 21:41, eliza botto escreveu:
> >>> 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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PLEASE do read the posting guide http://www.R-project.org/posting-guide.html
and provide commented, minimal, self-contained, reproducible code.
