similar to: Find the first values in vector

I think it's easy problem but I can't find solution. I have a vector: vec <- c (23.4, 3.0, 14.7, 7.7) and I would like to add all values which are inside my vector to each other. as a result a want to get one value like sum all values from my vector- sth=(23.4 + 3.0 + 14.7 + 7.7) PS. I usually don't know how long is my vector in my function -- View this message in

Hi, My english isn't brilliant and my problem is very difficult to describe but I try ;) My first question is: May I write loop "for" like this or similar - for (i in sth : sth[length(sth)], k in sth_else : length(sth_else) ) - I'd like to have two independent conditions in the same loop "for". My secound question depend on program below. I'd like to write every

Do you know any good editor R? -- View this message in context: http://www.nabble.com/Editor-R-tp23822342p23822342.html Sent from the R help mailing list archive at Nabble.com.

Hi, For example: I built a half matrix "w" using a daisy(x, metric = c("euclidean")) http://www.nabble.com/file/p25211016/1.jpg And next I transformed this matrix "w" using isoMDS function, for example isoMDS(w, k=2) and as result I got: http://www.nabble.com/file/p25211016/2.jpg And now I have two questions: 1. If number in matrix w[2, 1] (= 0.41538462) match

Hi! I have list, for example: ... [[22]] [1] 27 51 69 107 119 [[23]] [1] NA [[24]] [1] 54 57 62 And I would like to avoid NA value. Similar way like I may do it in vector using na.value() function. Do you have any idea? -- View this message in context: http://www.nabble.com/avoid-NA-in-list-tp25321020p25321020.html Sent from the R help mailing list archive at Nabble.com.

Hi, I have got a data frame: df=data.frame(x=c(3,6,7),y=c(2,7,4)) and I would like to write my values from data frame to list using loop, for example: lista=list() for (i in 1: length(?)){ lista[[?]][?] = df [?] } But I havn't got any idea what I should put in places where I put a question mark? As a rusult I would like to get a list like this: list: [[1]] 3,6,7 [[2]] 2,7,4 I

All, I would like to find a simper method that I now have to find the product of all elements in a vector: #get product of vector elements: (1,2,3,4,5) vec.product <- exp(sum(log(c(1,2,3,4,5)))) I have not found a vector product function, if one has been written. Thanks, Gerard [[alternative HTML version deleted]]

Hi So my particular problem is this: I have a row vector of length 5200 elements - specifically created by x<-rbinom(5200,1,0.5) y<-matrix(x,nrow=1,ncol=5200) y now, each element is either a 0 or a 1 - e.g. it could be (0,1,1,1,1,0,0,0,1,1,1) e.t.c. when the element is a 1, i need to multiply a number (say 1000) by 1.005, and if it is 1 again, multiply it _again_ by 1.005. so

Hi! I want to use one method "combinations" from "gtools" package but in my code I must use also "dprep" method where is method "combinations" too. Mayby I show you result my help function: Help on topic 'combinations' was found in the following packages: Package Library dprep /usr/lib64/R/library gtools

I spent a lot of time searching and came up empty handed on the following query. Is there an equivalent to rowSums that does product or cumulative product and avoids use of apply or looping? I found a rowProd in a package but it was a convenience function for apply. As part of a likelihood calculation called from optim, I?m computing products and cumulative products of rows of matrices with

Dear R-help, I have been trying really hard to generate the following vector given the data (x) and parameter (alpha) efficiently. Let y be the output list, the aim is to produce the the following vector(y) with at least half the time used by the loop example below. y[1] = alpha * x[1] y[2] = alpha^2 * x[1] + alpha * x[2] y[3] = alpha^3 * x[1] + alpha^2 * x[2] + alpha * x[3] ..... below are

Full_Name: J. Sisk Version: 1.6.1 OS: Linux (RedHat 8) Submission from: (NULL) (67.119.41.66) Suppose you make a data-frame like so: xxx <- data.frame(a=10,b=20,c=30,d=40) Then cumprod(xxx[1,]) returns > cumprod(xxx[1,]) a b c d 1 10 20 30 40 The documentation for cumprod says that it should work on "numerical objects", and this is a data-frame, but it

I have a dataframe of numeric values with 30 ?rows? and 7 ?columns?. For each column, beginning at ?row? 12 and down to ?row? 30, I wish to calculate the ?rolling 12 row product?. I.e., within each column, I wish to multiply all the values in row 1:12, 2:13, 19:30. I wish to save the results as a new dataframe, which will have 19 rows and 7 columns.

Is there anything like cumsum and cumprod but which allows you to apply an arbitrary function instead of sum and product? In other words, I want a function cumfunc(x, f) that returns a vector, so that for all n up to the length of x cumapply(x,f)[n] = f(x[1:n]) This would give cumsum and cumprod as special cases when f=sum or f=prod. I could write such a function, but I can't see

Just when I think I'm starting to learn .... Statement z1 works, statement z doesn't. Why doesn't z work and what do I do to fix it ? Clearly the problem is with the first NA, but I would think it's handled through the loop vectorization. y1 <- rnorm(20, 0, .013) y1 [1] -0.0068630836 -0.0101106230 -0.0169663344 -0.0066314769 0.0075063818 [6] -0.0033548024 0.0015647863

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"

I thought the "apply" functions are faster than for loops, but my most recent test shows that apply actually takes a significantly longer than a for loop. Am I missing something? It doesn't matter much if I do column wise calculations rather than row wise ## Example of how apply is SLOWER than for loop: #rm(list=ls()) ## DEFINE VARIABLES mu=0.05 ; sigma=0.20 ; dt=.25 ; T=50 ;

What is the R way of computing cumulative growth rates given a series of discrete values indexed . For instance, given a matrix of 20 observations for each of 5 series (zz), what is the most straight forward technique in R for computing cumulative growth (zzcum) ? It seems for the solution I'm after might be imbedding the following cum growth rate calc as a function into a function call

This is my code i don't understand the error message: library(rgenoud) rm(list=ls()) set.seed(666) ######################################################### # As a first step, it is assumed that all input parameters are independent of ageing : ######################################################### InputDim <-20 # Max number of ageings in the inputs CPIRate <- rep(0.02 , InputDim ) #

I have a vector like this: h <- c(4, 6, NA, 12) and I create the secound logical vector like this: g <- c(TRUE, TRUE, FALSE, TRUE) And my problem is that I would like to get a new "m" vector as a rasult "h" and "g"( as dot-matrix printer) but with missed "NA" value, for example: m = (4,6,12) Do you have any idea? -- View this message in