similar to: Merge sort

I indeed used is.na() to check length, as I was not sure weather lenght() was a simple query or would go through the whole vector to count the elements. So to sum up, function calls are expensive, therefore recursion should be avoided, and growing the size of a vector (which is probably reassigning and copying?) is also expensive. Thank you for your help! On 04/19/2016 11:51 PM, Duncan

On 19/04/2016 3:39 PM, Gaston wrote: > Hello everyone, > > I am learning R since recently, and as a small exercise I wanted to > write a recursive mergesort. I was extremely surprised to discover that > my sorting, although operational, is deeply inefficient in time. Here is > my code : > >> merge <- function(x,y){ >> if (is.na(x[1])) return(y) >>

Hi, I'd like to normalize a dataset by dividing each row by the first row. Very simple, right? I tried this: > expt.fluor X1 X2 X3 1 124 120 134 2 165 163 174 3 52 51 43 4 179 171 166 5 239 238 235 >first.row <- expt.fluor[1,] > normed <- apply(expt.fluor, 1, function(r) {r / first.row}) >normed [[1]] X1 X2 X3 1 1 1 1 [[2]] X1 X2 X3 1

Hello, some time ago I reported a bug, where we saw indeterministic behaviour of rsync (all versions since 2.5), when having the same file appearing in multiple sources. Sometimes the file in the first source was copied, other times the file was copied from one of the other sources. The attached mstest.tgz contains a test to reproduce the behaviour under darwin and solaris. The bug did

Hi, I would like to know how to capture the console output from running an algorithm for further analysis. I can capture this using capture.output() but that yields a character vector. I would like to extract the actual numeric values. Here is an example of what I am trying to do. fr <- function(x) { ## Rosenbrock Banana function on.exit(print(f)) x1 <- x[1] x2 <- x[2]

Hi, Does anyone know what the distribution for the product of two correlated normal? Say I have X~N(a, \sigma1^2) and Y~N(b, \sigma2^2), and the \rou(X,Y) is not equal to 0, I want to know the pdf or cdf of XY. Thanks a lot in advance. yu [[alternative HTML version deleted]]

R 2.2 on windows XP I have a dataset with multiple columns. Some of the columns represent independent variables, some represent dependent variables. I would like to run the same analyses on a fixed set of independent variables, changing only the dependent variable, e.g. y1-y2=x1+x2+x3 y3-y4=x1+x2+x3 y5-y6=x1+x2+x3, etc. I know I can write a function to perform the analyses, however in order to

I found a form of the if statement that works but it is very long. I'm attempting to check the value of of two different variables to see if they evaluate to either of two different values, which will result in a division by 0 in the final equation. This first if statement works for me _______ if ((x0.trial01 == 0.0)||(x0.trial01 == npt01)||(x1.trial01 == 0.0)||(x1.trial01 == npt01))

Hi, I have a simple problem that I would appreciate getting some tips. I am using the "truehist" function within an "apply" call to plot multiple histograms. I can't figure out how to get truehist to use the column names of the matrix as the labels for the x-axis of the histograms. Here is a simple example: X <- matrix(runif(4000),ncol=4) colnames(X)

Hi r users, I have two data sets (X1, X2). For example, time1<-c( 0, 8, 15, 22, 43, 64, 85, 106, 127, 148, 169, 190 ,211 ) outpue1<-c(171 ,164 ,150 ,141 ,109 , 73 , 47 ,26 ,15 ,12 ,6 ,2 ,1 ) X1<-cbind(time1,outpue1) time2<-c( 0 ,8 ,15 , 22 ,43 , 64 ,85 ,106 ,148) output2<-c( 5 ,5 ,4 ,5 ,5 ,4 ,1 ,2 , 1 ) X2<-cbind(time2,output2) I want to

Dear All, Hans Borchers and I have been trying to compute "exact" derivatives in R using the idea of complex-step derivatives that Hans has proposed. This is a really, really cool idea. It gives "exact" derivatives with only a minimal effort (same as that involved in computing first-order forward-difference derivative). Unfortunately, we cannot implement this in R as the

Dear all, I'm trying to merge 2 dataframes, but I'm not being entirely successful and I can't understand why. Dataframe x1 State_prov Shape_name bob2009 bob 2010 bob2011 Nova Scotia Annapolis 0 0 1 Nova Scotia Antigonish 0 0 0 Nova Scotia Gly NA NA

Hi: Suppose that I have a data frame as below x1 x2 x3 ... x10 wk1 wk2 ... Wk208 (these are the column names) For each record, x1, x2, x3 ... x10 are attributes. and wk1, wk2, ..., wk208 are the sales recoreded for this attribute combination. Suppose that now, that I want to do the following 1. Merge the data frame so that I have a new data frame grouped by values of x2 and x3 (for example).

Hi, Suppose I have an arbitrary function: arbfun<-function(x) {...} Is there a robust implementation of a numerical derivative routine in R which I can use to take it's derivative ? Something a bit more than simple division by delta of the difference of evaluating the function at x and x+delta... Perhaps there is a way to do this using D or deriv but I could not figure it out.

Given a square matrix of variables X, is there any way to compute a multivariable correlation among all the variables in the array? It is possible to calculate the correlation of all pairs of variables in the array, but I want to know the correlation of all the variables taken together, i.e. for the matrix X=x1 x2 x3 x4 x5 x6 x7 x8 x9 I don't want the pair-wise correlations

Hello, I have a general question about combining imputations as well as a question specific to the rms and Hmisc packages. The situation is multiple regression on a data set where multiple imputation has been used to give M imputed data sets. I know how to get the combined estimate of the covariance matrix of the estimated coefficients (average the M covariance matrices from the individual

Hi, I have a character vector that contains the names of several objects that I would like to pass to a function (specifically, the ridge function in the survival package, but cbind is a similar example). I've been struggling with how to do this so that the object values get interpreted by the function, rather than the object names. For example, x1 <- 1:4 x2 <- 2:5 x3 <-

Dear all, If I have a data frame x<-data.frame(x1=c(1,7),x2=c(4,6),x3=c(8,2)): x1 x2 x3 1 4 8 7 6 2 I want to sort the whole data and get this: x1 1 x3 2 x2 4 x2 6 x1 7 x3 8 If I do sort(X), R reports: Error in order(list(x1 = c(1, 7), x2 = c(4, 6), x3 = c(8, 2)), decreasing = FALSE) : unimplemented type 'list' in 'orderVector1' The only way

i'm trying to use the BB package to minimize the sum of the squared deviations for 2 vectors. The only thing am having trouble with is defining the project constraint. I got the upper and lower bounds to work but i am not sure how to create a constraint that the sum of x must be 1. Any help would be greatly appreciated. -- View this message in context:

I?ve been using Frank Harrell?s rms package to do bootstrap model validation. Is it the case that the optimum penalization may still give a model which is substantially overfitted? I calculated corrected R^2, optimism in R^2, and corrected slope for various penalties for a simple example: x1 <- rnorm(45) x2 <- rnorm(45) x3 <- rnorm(45) y <- x1 + 2*x2 + rnorm(45,0,3) ols0 <- ols(y