similar to: Efficient way to Calculate the squared distances for a set of vectors to a fixed vector

This is some interesting: > -8^(1/3) [1] -2 > x=(-8:8) > y=x^(1/3) > y [1] NaN NaN NaN NaN NaN NaN NaN NaN 0.000000 1.000000 [11] 1.259921 1.442250 1.587401 1.709976 1.817121 1.912931 2.000000 So, can anybody explain this?! (Why is x[1]^(1/3)=y[1]=NaN, but -8^(1/3)=-2?) Thx!!! [[alternative HTML version deleted]]

deaRs, I want to build a covariance matrix out of the data from a binary file, that I can read in chunk by chunk, with each chunk containing a single observation vector X. I wonder how to do that most efficiently, avoiding the calculation of the full symmetric matrices XX'. The trivial non-optimal approach boils down to something like: Q <- matrix(rnorm(100000),ncol=200) M <-

Hi, I am trying to plot several columns in different graphs in columns and rows. The first column of my data file is the time, and the third is the 'elevation angle' with 19 different numbers. I would like to plot the rest of the columns with the x axis as time and the individual angles in different colours. Here is the code I am using right now. It plots the different columns with time,

Dear all, I have a large matrix with about 2500 variables, and 100 rows. I would like to calculate the means of the every 10 variables starting from 1:2500 and saving the results as a vector or matrix. How can I do that? Alternatively, How can I create 250 subset matrices in the order of variables 1:2500 in groups of 10 from the single matrix which had initially 2500 variables ? I guess I have

Hello! I'm trying to build a lower triangular matrix (with zeros in the diagonal) from a particular dataframe. The matrix I have to construct has 203 rows and 203 columns and that makes 20503 values to be included within (that's why I can't do it manually). To illustrate the dataframe I have, I'll give you an example of a dataframe and matrix with dimensions 6x6 (to make it

Dear all, I admit this is not anything to do R and even with Statistics perhaps. Strictly speaking this is a math related question. However I have some reasonable feeling that experts here would come up with some elegant suggestion to my question. Here my question is: What is sum of all Integers? I somewhere heard that it is Zero as positive and negative integers will just cancel each other out.

I've been wondering what L means in the R computing context, and was wondering if someone could point me to a reference where I could read about it, or tell me what it's called so that I can search for it myself. (L by itself is a little too general for a search term). I encounter it in strange places, most recently in the "save" documentation. save(..., list = character(0L),

Hello to all again :) Again, I have an issue with my homework. I was troubling myself for two days, and I still can't get it :( So, if someone can help me, I would be so grateful... HOMEWORK 1. I need to draw function, random walk take the length of walk, and its in 2D. As a result, I have to take matrix in which are i-lines of matrix, written coordinates on i-steps radnom.walk <-

Hi, I'm trying to set the minimum and maximum in a parallel plot, but trying xlim=c(-1,1) gives strange results. Am I missing something? The call I give is: parallel(~X[,c(6,9,12,15,18)]|X$ff,X,panel=panel.parallel.new,groups=X$protein,layout=c(3,1),xlim=c(-1,1)) Besides, I would like to add a reference line to the plot, but can't find how to do that. I hope someone can give me a

Hello R-helpers, I am trying to search for string that includes the caret symbol, using the following code: grepl("latitude^2",temp) And R doesn't like that. It gives me: > temp<-c("latitude^2","latitude and latitude^2","longitude^2","longitude and longitude^2") > temp [1] "latitude^2" "latitude and

Dear R-users, I would like to apply a function (more precisely sd()) over the third dimension of a three-dimension array. The function apply would be interesting but the chosen function can only be applied on the rows and columns of the array according to the help file. I can use a loop to cut the array in matrices and then use apply for each replication, but it's not very nice. A small

Hello, I am a newcomer to R and therefore apologize for posting such a basic question. I am trying to multiply 2 matrices t(X1)%*%X1, where t(X1) is: 1 2 3 4 5 8 12 13 20 24 26 27 31 33 34 36 37 40 41 42 45 46 47 48 49 ones 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 Shadow 0 1 1 1 1 1 1 1 0 1 1 1 1 0 1 0

Dear R experts, How to find out the index of minimum or maxmum number in a vetor or data.frame? For example, a= n price 1 50 -2 100 0 200 -1 300 ...... I want to find out the row which the n is the smallest or largestest and extract the price. Thanks Ted -- View this message in context:

I'm trying to create a graph where different cells of a grid (a shapefile) will be painted with a color share scale, where the most easy way is to use gray(). Can I somehow get a vector (gradient) of colors, a vector of colors with other methods but gray()? I'm doing this until now quad_N_sp <-

Dear list, I have a vector of numbers, let's say: myvec <- c(2, 8, 24, 26, 51, 57, 58, 78, 219) My task is to reduce this vector to non-reducible numbers; small numbers can cross-out some of the larger ones, based on a function let's say called reduce() If I apply the function to the first element 2, my vector gets shorted to: > (myvec <- reduce(myvec[1])) [1] 2 24 51

Dear R community Have just recently got back into R after a long break and have been amazed at how much it has grown, and how active the list is! Thank you so much to all those who contribute to this amazing project. My question: I am trying to calculate Mahalanobis distances for a matrix called "fgmatrix" >dim(fgmatrix) [1] 76 15 >fg.cov <- cov.wt(fgmatrix)

Hi all, I’ve narrowed down a problem in my code to the following test case: - - - - typedef struct {float v[2];} vec2; typedef struct {float v[3];} vec3; vec2 getVec2(); vec3 getVec3() { vec2 myVec = getVec2(); vec3 res; res.v[0] = myVec.v[0]; res.v[1] = myVec.v[1]; res.v[2] = 1; return res; } - - - - Compiling this with any level of optimization for arm64 gives incorrect code,

Dear R-users, I have two outliers related questions. I. I have a vector consisting of 69 values. mean = 0.00086 SD = 0.02152 The shape of EDA graphics (boxplots, density plots) is heavily distorted due to outliers. How to define the interval for outliers exception? Is <2SD - mean + 2SD> interval a correct approach? Or should I define 95% (or 99%) limit of agreement for data interval,

Dear experts, I try not to trouble the list again after this question. I want to print this vector into a file > myvec [1] --Control --Control --Control --Control --Control HBA2 HBA1 [8] HBA1 --Control HBB --Control HBB HBA1 MBP [15] --Control HBA1 HBA2 HBB PTGDS GAPDH UBC [22] --Control GAPDH TPT1 HUWE1 PRM1 CKM

Dear list, This should be a simple one, I just cannot see it. I need to generate a sequence of the form: 4 5 6 13 14 15 22 23 24 That is: starting with 4, make a 3 numbers sequence, jump 6, then another 3 and so on. I can create a whole vector with: myvec <- rep(rep(c(F, T, F), rep(3, 3)), 3) Then see which are TRUE: which(myvec) [1] 4 5 6 13 14 15 22 23 24 I'd like to avoid