1. Please follow the posting guide and provide a small reproducible
example. See ?dput to provide data.
2. Please do not double post.
-- Bert
On Mon, Jun 4, 2012 at 4:47 PM, eliza botto <eliza_bo...@hotmail.com> wrote:
>
> 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?? more precisely, i want to
> interpolate 366 discharge readings, in each 8 columns of a matrix, over 365
> days.
> 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.
>>
>> [[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.
--
Bert Gunter
Genentech Nonclinical Biostatistics
Internal Contact Info:
Phone: 467-7374
Website:
http://pharmadevelopment.roche.com/index/pdb/pdb-functional-groups/pdb-biostatistics/pdb-ncb-home.htm
______________________________________________
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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.
