similar to: getting a title in a plot during an lapply

Hi : I think I need to use sapply but I can't figure this out. Suppose I have two vectors : tempa ( 4, 6,10 ) and tempb ( 11,23 ,39 ) I want a function that returns 4:11,6:23 and 10:39 as vectors. I tried : sapply(1:length(tempa) function (z) seq(tempa[z],tempb[z]) but i got 3 really strange vectors back in the sense that the numbers in them did not make no sense to me. obviously, i

in my previous post in which i asked about creating sequences from two vectors of numbers, all suggestions worked. tradevectors<-mapply(seq,from=tempa,to=tempb) or tradevectors<-sapply(1:length(tempa),function(x) seq(tempa[x],tempb[x]) >both return a list with 3 components. the problem is that i want to take these 3 sequences and use them as the indices of two other vectors, X and

can someone show me how to convert a table to a data.frame or a matrix ? I tried below and as.data.frame rearranges the columns similarly to a melt from reshape and as.matrix didn't change it. I actually would prefer to change it to a dataframe but if someone can show me how to convert it to a matrix, then as.data.frame will work on that. I was thinking about just changing the class to

Greetings all, I am calculating two t-test values for each of many files then save it to file calculate another set and append, repeat. But I can't figure out how to write it to file and then append subsequent t-tests. (maybe too tired ;} ) I have tried to use "dump" and "file.append" to no avial. ttest_results = tempfile() two_sample_ttest <- t.test (tempA, tempB,

Marc and many other people ( whose names escape me ) have been very helpful in explaining the use of lapply to me. In his last response, Marc explained that if tradevectors is a list of vectors of different lengths ( excuse my terminology ) then lapply(tradevectors,function(x) G[x]*B[x] ) will go through each component of the list as if it was a vector and apply the element by element

I have a data frame, lets call it dat, with 3 columns ( mc, yr, ret) which represent market cap, year, and return. mc is a factor, mc, and ret are real numbers. I want to add a column to the data calculated as follows. For each year, I want to split the data by mc decile, then calculate the mean ret within that mc decile, and finally subtract that year's decile mean from the raw return. Then

Hi R users, I have a matrix of data similar to: > y=matrix(rnorm(55),ncol=5) I would like to know to which decile each number belongs compared to the numbers in its column. Say y[1,1] is the third decile among y[1:11,1] and y[2,1] is in the second decile I would like get a matrix that would return their ranks in decile, i.e., y[1,1] -> 3 y[2,1] -> 2 Your help is much appreciated!

bonjour, i'm a mathematic teacher and i have a question for R-developers : is it possible to have (in the future) a boxplot with whiskers from the first decile to the ninth decile, as usual in secondary french schools... by example : boxplot(serie,range=-1) for french boxplot ? cordialement, jean-pierre lyc?e jean zay orl?ans, france http://mathazay.free.fr/spip/

Hello, I have a set of data with two columns: "Target" and "Actual". A http://n4.nabble.com/file/n1584647/Sample_table.txt Sample_table.txt is attached but the data looks like this: Actual Target -0.125 0.016124906 0.135 0.120799865 ... ... ... ... I want to be able to break the data into tables based on quantiles in the "Target" column. I can see (using

I guess this is really basic. But I do not find an answer yet. I have a big data.frame. I would like to divede them into 10 deciles accounding to one of its member. Then I need a number for each decile with some computaion within each group. How to devide it?

Hi Experts, I am new to R, using decision tree model for getting segmentation rules. A) Using behavioural data (attributes defining customer behaviour, ( example balances, number of accounts etc.) 1. Clustering: Cluster behavioural data to suitable number of clusters 2. Decision Tree: Using rpart classification tree for generating rules for segmentation using cluster number(cluster id) as target

How to use ggplot to do the binned quantile plots(one type of scatter plot)? Hi all, I have done scatter plot: plot(x, y). Now I wanted to do binned quantile plots... can ggplot2 help me? For example, we bin x data into 10 bins. For each bin, we draw the 10 deciles of the corresponding y data in that bin as points/dots. And then accross all bins, we would like to connect the corresponding

I am constructing plots ( regular not lattice ) and my initial command is par(mar=c(3,4,2,2), mfcol=c(5,2)) and then I create 10 plots on the page. It looks great but the plots on the page go in the order 1 6 2 7 3 8 4 9 5 10 Where the numbers denote decile breakdowns. Is there an easy way to make them go from left to right so 1 2 3 4 5 6 7 8 9 10 I could try

Hello all, I have searched and have not yet identified a solution so now I am sending this message. In short, I need to split my data into training, validation, and testing subsets that keep all observations from the same sites together ? preferably as part of a cross validation procedure. Now for the longer version. And I must confess that although my R skills are improving, they are not so

I am trying to calculate the weighted mean for a of 10 deciles and I get an error: > decile <- tapply(X=mat$trt1m, INDEX=mat$Rank, FUN=weighted.mean, w=mat$mcap) Error in FUN(X[[1]], ...) : 'x' and 'w' must have the same length All three of my inputs have the same length, as shown below, and the weighted.mean calculation works by itself, just not in tapply() >

bonjour, je voudrais savoir s'il serait possible de sugg?rer aux d?veloppeurs de R de proposer une option suppl?mentaire pour les moustaches, ? savoir les placer sur d1 et d9 comme c'est pr?conis? dans les programmes du secondaire en France, option du style boxplot (serie,range=91) par exemple... i would like to know if it is possible to have (with the agrement of developpers)

Hi all, I am doing a array marginalization over one dimension in the following manner: =========================================================== for(l in 1:L) { flst=list(Pzu, Pzi, array(Puzu[,as.character(r[[l,"u"]])], dim=dim(Puzu)[1], dimnames=dimnames(Puzu)[1]), array(Pizi[,as.character(r[[l, "i"]])], dim=dim(Pizi)[1], dimnames=dimnames(Pizi)[1]) ); tempa = 1;

Dear UseRs, I'm making box plots from a data set that looks like this: Chr Start End GeneDensity ReadCount_Explant ReadCount_Callus ReadCount_Regen 1 1 1 10000 107.82 1.243 1.047 1.496 2 1 10001 20000 202.50 0.835 0.869 0.456 3 1 20001 30000 158.80 1.813 1.529 1.131

I have a general question about coefficients estimation of the mixed model. I simulated a very basic model: Y|b=X*\beta+Z*b +\sigma^2* diag(ni); b follows N(0,\psi) #i.e. bivariate normal where b is the latent variable, Z and X are ni*2 design matrices, sigma is the error variance, Y are longitudinal data, i.e. there are ni

Hi, Not sure if I am making a simple problem complex but still here we go: I have a data frame with four columns say, X1 X2 X3 and X4. I want to break X4 into deciles and for each deciles obtained, I want to see corresponding elements of X1. Ideally, the output should be in a tabular fashion as shown below: Deciles 1 Deciles 2 .... Deciles 10 X1-1 X1-2 X1-99 X1-5 X1-3 X1-10