similar to: transition matrix and discretized data

In my code below tempa and tempb are numeric vectors that I combined into a dataframe along with the deciles of tempa. I have an lapply statement that goes through the dataframe and does ten plots according to the appropriate decile. The code is below and it works fine. There are no bugs so I figure there was no need to include structure statements on the data. Also, I don't want to use coplot

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!

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

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

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?

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

> Buenas, tengo la siguiente inquietud. > Tengo un data frame con los microdatos de la ECH de mi pais. He realizado > un cuadro sin problemas en excel pero me gustaria una rutina de R para > poder generar la tabla. El data.frame se llama ECH2009. Cuenta con las > siguientes variables para este caso: > > idhogar region estrato integranteshogar expansor ingpercapsvl Computador

Dear All, I am economist and working on poverty / income inequality. I need descriptive statitics like the ratio of education expentitures between different income quintiles where each household has a different weight. After a bit of google search I found 'Hmisc' and 'quantreg' libraries for weighted quantiles. The problem is that these packages give me only weighted quintiles;

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

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, 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/

Hi everyone, I'm a new R user (if this is a really basic question, please do excuse me...) and I'm having some questions regarding a deciles problem. I have a variable which I need to categorize according to its deciles (X). However, this categorization should be made into another variable (call it NewVar). Ex. for the quartiles case (just for the sake of exposition, since I need

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

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)

Thanks for your help, Rui! That works and will save me a lot of trouble. --Kelly -----Original Message----- From: Rui Barradas [mailto:ruipbarradas at sapo.pt] Sent: Tuesday, July 10, 2012 2:24 AM To: Vining, Kelly Cc: r-help at r-project.org Subject: Re: [R] boxplot with "cut" Hello, Maybe this iss what you're looking for. GD is your data.frame. multi.boxplot <-

Hi, I am using the package "demography" from Rob Hyndman for the Lee-Carter-Model. It is an amazing powerful tool but I am struggling with one issue: *I want to compute different quintiles for the cumulative survival probability derived from the Lee-Carter-Forecast (e.g. the 50%-quintile, 75%-quintile and 99%-quintile) for the next 10 years. * I am sure the package possess this

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

Hi, I am looking to build even quintiles for a set of data. I managed to get it done, but I would like to know if there is a more direct way to write the data from my loop output x in the bottom of the code into the "empty" matrix p1, which I filled with NA''s. The way I am doing it at the moment is, more or less adding the matrix x after p1 and then deleting in a second step

Hi, Ia m working in discretized data. Here my data: x <- c(2,1,3, 5), and I want to make (0,1) data based on the length of each component in x. So the new data should like: y = (0, 1, 1, 0, 0, 1, 0, 0, 0, 0, 1). I spent too much time with "seq", "rep". Still didn't get it. Any help? Thanks Ilham [[alternative HTML version deleted]]