Dear R users,
we generally apply approx() command to a list data. how can we apply this
command to a matrix, so that we can approximate 366 readings from certain
number of each column over 365 intervals??
hope i am clear in my statement.
eliza botto
> From: eliza_bo...@hotmail.com
> To: ruipbarra...@sapo.pt
> Date: Mon, 4 Jun 2012 22:13:10 +0000
> CC: r-help@r-project.org
> Subject: Re: [R] Spliting Lists into matrices
>
>
>
>
>
>
> 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]]
>
> ______________________________________________
> 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.
