similar to: Pre-allocation of matrices is LESS efficient?

Hi. This is my first post to this list, I seem to be graduating to from the r-help list. :-) I'm trying to wrap my R package in a GUI such that when the user launches the app, they see my GUI window and never interact with the R console at all. I don't have any fancy requirements for the GUI itself-- all it needs to do is collect input from the user and pass the input as arguments to

Let's say I've run Anova(lm(y~a*b)) and found the a:b interaction to be significant. Now I'm interested in which specific level combinations of a and b significantly differ from the control group. Can I use the t-tests from summary(lm(y~a*b)) to answer that question? I saw no mention of multiple comparison in the documentation for summary.lm, so am I right in assuming I need to

I have a data frame with 1 factor, one date, and 37 numeric values: str(waterchem) 'data.frame': 3525 obs. of 39 variables: site : Factor w/ 64 levels "D-1","D-2","D-3",..: 1 1 1 1 1 ... $ sampdate : Date, format: "2007-12-12" "2008-03-15" ... $ CO3 : num 1 1 6.7 1 1 1 1 1 1 1 ... $ HCO3 : num 231 228 118 246

Hello, and apologies for the upcoming naive questions. I am a biologist who is trying to teach himself the appropriate areas of math and stats. I welcome pointers to suggested background reading just as much as I do direct answers to my question. Let's say I have a function F() that takes variables (a,b,c,a1,b1,c1) and returns x, and I want to find the values of these variables that result in

I was wondering if someone can tell me the best way to search through a matrix and choose certain rows (based on certain conditions) to put into a separate matrix. What I have tried so far is very slow for a large dataset I'm working with. e.g., I have this piece of code to create a new matrix (newmat) based on my filtering conditions. Do I need to do this kind of thing where I keep

Hello, I have been wondering of an efficient way to do this: I have an n x m x p array Z and a p x n matrix Y. I want to multiply each of the n matrices with the corresponding column vector of Y. In other words, I am wanting to matrix multiply: Z[i, ,] %*% Y[, i] which will give me a (two-dimensional) array or matrix of dimension n x p with the i'th row storing the above. Any pointers

I'm having trouble setting up the function call to handle two lists of matrices. Each list has 6 matrices - Each matrix is 20x10. I need to do some basic math on corresponding matrices in each list. Here are some outputs of these lists, etc... # first list > length(qc.pm) [1] 6 > dim(qc.pm[[1]]) [1] 20 10 > qc.pm[[1]][1:4,1:4] 441-JP071707.CEL 442-JP071707.CEL

Hello, I want to add some new functionalities in the package 'quantmod '. So I download source code and am managed to build it. I found that modifying code and check if it works by repeating the following steps: 1) r CMD check quantmod 2) r CMD build quantmod 3) r CMD INSTALL quantmod_0.3-17.tar.gz 4) launch R gui 5) library('quantmod') 6) run my script Let me know if there

Hello. To save the hassle of quitting and restarting R every time I rebuild the package I'm working on (for the purposes of this question called "roots") I would like to write a script cleanly remove the package from my R session and then load it again. Of course detach("package:roots") works for the native R objects in the package. However, the compiled C library remains

Hello. To save the hassle of quitting and restarting R every time I rebuild the package I'm working on (for the purposes of this question called "roots") I would like to write a script cleanly remove the package from my R session and then load it again. Of course detach("package:roots") works for the native R objects in the package. However, the compiled C library remains

Dear R-users I have four simple linear models, which are all in the form of a*X+b The estimated parameter vectors are a <- c(1,2,3,4) b <- c(4,3,2,1) My goal is to draw a plot where x-axis is X (range from -100 to 100) and y-axis is the sum of all four linear models X <- seq(-100,100, length=10000) plot(X, sum of the four linear functions) I started with a function for summing

Hola a todos, mi consulta va relacionada con los paquete nlme o lmer. Mi idea va relacionada a correr un modelo lineal mixto en el cual una de las matrices de incidencia (Z), sea previamente formada por la suma de dos matrices o por su puperposición (Z1+Z2=Z) dentro de esas funciones. Con un ejemplo creo que me explicaré mejor outputF<-lmer(formula=ALT~ (1|MADRE)+(1|PADRE)+(1|FAMILIA),

Hello, I have a few questions now: 1. How can I move data the following way: I have 2 variables: one two 1 5 ^ 3 4 | 1 3 | 4 4 | Now I want to move the two one arround (sorry I don't know how to say that in english). That means: I want to move the first item at the end of my column and move the second at the first place, the third at the second, and so on. You can see it at

Hi expeRts, I would like to calculate weighted mean by two factors. My code is as follows: R> tmp <- by(re$meta.sales.lkm[, c("pc", "sales")], re$meta.sales.lkm[, c("size", "yr")], function(x) weighted.mean(x[,1], x[,2])) The result is as follows: R> tmp size: micro yr: 1994 [1] 1.090

I've been able to figure out on my own how to do what I need in the largely undocumented tcltk package, but I've finally hit a wall. I can't even think of any sufficiently specific search terms to use for this. I'm trying to make the widgets in my tk window resize when the window is resized by clicking and dragging on its corners or edges. Instead they stay exactly where they

Hi! I use simtest fonction of multcomp package to compile a Dunnett's test. I have 10 treatments and one control group, so i create a matrix with: m<-matrix(0,10,11) m[1,1]<--1 m[1,2]<-1 m[2,1]<--1 m[2,3]<-1 m[3,1]<--1 m[3,4]<-1 m[4,1]<--1 m[4,5]<-1 m[5,1]<--1 m[5,6]<-1 m[6,1]<--1 m[6,7]<-1 m[7,1]<--1 m[7,8]<-1 m[8,1]<--1 m[8,9]<-1

Hello. I wrote a package (that contains C source) that I've been compiling and running on both Linux and Windows for about a year. However, that same source package fails to compile on MacOS (10.4.11, PowerPC G4, Xcode installed, gcc version 4.0.1, make version 3.80, ld version cctools-590.23.2.obj~17). There is nothing platform-specific in the code-- just numerical functions that I

Hi dear users, I try to split a matrix into a few matrices, for example, suppose that I have 1000X4 matrix from mvrnorm(1000,m,c) with m<-matrix(c(0,0,0,2),4,1) and c<-matrix(c(1.0,0.2,-0.5,0.3,0.2,1,0.2,-0.5,-0.5,0.2,1,0.2,0.3,-0.5,0.2,1),4,4,byrow=T) How to split the matrix into a. 2 matrices which the first one consists of the first 500 rows, and the second one consist of the

Hello, i try to understand, how it works (IDLE). Try to get it successfully work with my new Palm Pre ;-) which looks like to have a lot issues wir imap... so i'll blame not dovecot for the issues. Sent a mail, from googlemail. processed by dovecot ad 12:11. what me now confusing, is, that there in the out-log is nothing visible, I expected, to see there was sent an notification, there was

Take vector x and a subset y: x=1:10 y=c(4,5,7,9) For each value in 'x', I want to know how many elements in 'y' are less than 'x'. An example would be: sapply(x,FUN=function(i) {length(which(y<i))}) [1] 0 0 0 0 1 2 2 3 3 4 But this solution is far too slow when x and y have lengths in the millions. I'm certain an elegant (and computationally efficient)