similar to: Loading only particular columns from csv file...

Hi all R helpers, I'm trying to comeup with nice and elegant way of "detecting" consecutive increases/decreases in the sequence of numbers. I'm trying with combination of which() and diff() functions but unsuccesifuly. For example: sq <- c(1, 2, 3, 4, 4, 4, 5, 6, 5, 4, 3, 2, 1, 1, 1, 1, 1); I'd like to find way to calculate a) maximum consecutive increase = 3 (from 1

Dear R users, I'm new but already fascinated R user so please forgive for my ignorance. I have the problem, I read most of help pages but couldn't find the solution. The problem follows.... I have large data set 10,000 rows and more than 100 columns... Say something like var1,var2,var2,var4.......var120 ------------------------------------------- 12,12,345,657,67,8.....

Dear R helpers, I'm trying to build logistic regression model large dataset 360 factors and 850 observations. All 360 factors are known to be good predictors of outcome variable but I have to find best model with maximum 10 factors. I tried to fit full model and use stepAIC function to get best model but unfortenatly, the process takes too long to complete (more than 4 hours)... Is it

Hi R helpers, I'm preparing dataset to fir logistic regression model with lrm(). I have various cointinous and discrete variables and I would like to: 1. Optimaly discretize continous variables (Optimaly means, maximizing information value - IV for example) 2. Regroup discrete variables to achieve perhaps smaller number of level and better information value... Please suggest if there is

Hi R helpers, I'd like to see source code for some of built-in R functions... for example, I would like too see how "na.omit" was implemented? Thanks?

Hi, What I'm trying to achieve is very fast algorithm for fitting logistic regression model. I have to estimate regression coeficients using about 10k observations. Once I have coefficients estimated, new 100 rows of data becomes available.... Now I need to reestimate coeficients using 100 newly arrived observations and removing 100 oldest observations. So, my question is would it be

For reasons that are best known to myself [ ;-) ] I have a value of .Random.seed saved (via dput()) in a file ``.Random.seed.save''. In my .Rprofile I have the lines: .Random.seed <- dget(".Random.seed.save") Junk <- dget(".Random.seed.save") print(all.equal(.Random.seed,dget(".Random.seed.save")))

Hi all, Why subscripting a one column matrix drops one dimension? > x<- matrix(rnorm(100), ncol=1) > str(x) num [1:100, 1] -0.413 -0.845 -1.625 -1.393 0.507 ... > str(x[20:30,]) num [1:11] -0.315 -0.693 -0.771 0.448 0.204 ... > str(x[20:30]) num [1:11] -0.315 -0.693 -0.771 0.448 0.204 ... This breaks: > cov(x) [,1] [1,] 0.9600812 >

dear all, in the package pwr , there is the fonction power.anova.test which permit to obtain the power for a one-way ANOVA...but I'm looking for a way to compute the power of a multiway ANOVA.( find the 1-beta). Is it possible? do you have some ideas ? regards [[alternative HTML version deleted]]

Hi all, So far I only know one way to get the confidence limit for the Poisson distribution is to use the look-up table given by the 2 parameter (the number of observation x and the confidence level, e.g. 95%) and the table is limit by the maximum number of observations (x <= 50). I know the formula to compute the CI, however, mathematically it is not easy to do it. So, anyone know an R

Dear list, I have a data frame of survey respondents, a little like this: set.seed(20081215) n <- 100 dat <- data.frame(id=1:100, addr1=sample(LETTERS, n, replace=TRUE), addr2=sample(LETTERS, n, replace=TRUE), addr3=sample(LETTERS, n, replace=TRUE)) head(dat) id addr1 addr2 addr3 1 1 R H Q 2 2 H C K 3 3

I would like to calculate the mean of tree leader increment growth over 5 years (I1 through I5) where each tree is a row and each row has 5 columns. So far I have achieved this using rowMeans when all columns are numeric type and used in the calculation: Data1 <- data.frame(cbind(I1 = 3, I2 = c(0,3:1, 2:5,NA), I3 =c(1:4,NA,5:2),I4=2,I5=3)) Data1 Data1$mean_5 <- rowMeans(Data1, na.rm =T)

Hello, I am trying to figure out if there exists some R command that allows one to be particularly selective when reading a file. I'm dealing with large fixed-width data sets that look like 539001.. 639001.. 639001.. ... 539002.. 639002.. ... Presently, I am using read.fwf to read an entire file, but I am interested only in reading those records beginning with 5. I have been unable to

I have a dataframe with columns "ID",'date","estimate","actual" (but not necessarily in that order - I do a merge somewhere and that somehow messes up the order of the columns). How can I output it to a csv file with the columns in the order that I want? Thanks.

Does anyone know of a literature reference, or a piece of code that can help me calculate the amount of variation explained (R2 value), in a regression constrained to have a slope of 1 and an intercept of 0? Thanks! Sebastian J. Sebastián Tello Department of Biological Sciences 285 Life Sciences Building Louisiana State University Baton Rouge, LA, 70803 (225) 578-4284 (office and lab.)

Hi R-experts, suppose I have a list with containing data frame elements: [[1]] (Intercept) y1 y2 y3 y4 -6.64 0.761 0.383 0.775 0.163 [[2]] (Intercept) y2 y3 -3.858 0.854 0.834 Now I want to put them into ONE dataframe like this: (Intercept) y1

Am I correct in believing that one cannot match on multiple columns? One can indeed subset on multiple criteria from different variables (or columns) but not from unique combinations thereof. I need to exclude about 10000 rows from 108000 rows of data based on several unique combinations of identifiers in two columns. Only merge() seems to be able to do that. Merge would allow me to positively

Hi all, I was wondering whether it is possible to use the lapply() function to alter the value of the input, something in the spirit of : a1<-runif(100) a2<-function(i){ a1[i]<-a1[i-1]*a1[i];a1[i] } a3<-lapply(2:100,a2) Something akin to a for() loop, but using the lapply() infrastructure. I haven't been able to get rapply() to do this. The reason is that the "real"

Hi there, I have a binary matrix (dim 100x100) filled with values 0 and 1. I need select a record "n" positions of that matrix when values are 1. How can I do that? Thanks for all, Miltinho Brazil --------------------------------- [[alternative HTML version deleted]]

Dear All, Thanks to an answer which I received from a previous post, I'm now able to create a series of environments using the following: nmes <- c("en1", "en2", "en3") for(i in nmes) assign(i, new.env(parent = .GlobalEnv)) My next question is how, using "load", can I automatically place data into each of these newly created environments. The