similar to: function odiag(): assigning values to off-diagonal

Hi there I'm trying to find the mle fo a multinomial model ->*L(N,h,S?x)*. There is only *N* I want to estimate, which is used in the number of successes for the last cell probability. These successes are given by: p^(N-x1-x2-...xi) All the other parameters (i.e. h and S) I know from somewhere else. Here is what I've tried to do so far for a imaginary data set:

Sorry if this is a stupid question but I've been stuck on how to code so that I can order rows of a matrix without paying attention to the diagonal elements. Say, for example, I have a matrix d: > d [,1] [,2] [,3] [,4] [1,] 0.000000 2.384158 2.0065682 2.2998856 [2,] 2.384158 0.000000 1.4599928 2.4333213 [3,] 2.006568 1.459993 0.0000000 0.9733285 [4,] 2.299886

Hi, I have worked long and hard and looked in the manuals and am having a hard time constructing a diagonal matrix. I can get the diagonals out of a matrix but can't construct the matrix with just the diagonals. I have been on the web site and manuals and I think that it says to use: dsj <- diag (three = 1, nrow, ncol = 7) three is the name of my matrix and

Hi, how do i fill the secondary diagonals of a matrix? Is there an funktion like the "diag" funktion in matlab, where i can specify the diagonal i?d like to fill? -- View this message in context: http://www.nabble.com/Filling-matrix-secondary-diagonal-tp25121745p25121745.html Sent from the R help mailing list archive at Nabble.com.

Dear list, is anyone aware of the following behavious of diag when used to replace diagonals (plural!) of a matrix? Small example: The following is documented and clearly to be expected: A <- matrix(0, nrow = 5, ncol = 5) diag(A) <- 1; A BUT, what about the following? When executing the code of `diag<-` line by line, it throws errors. So why does it work? diag(A[-1, ]) <- 2; A

Hi Suppose I have a matrix (cohort are rows and years are columns) [2000] [2001] [2002] [2003] [C1] 0.01 0.03 0.02 0.09 [C2] 0.06 0.05 0.07 0.11 [C3] 0.1 0.5 0.4 0.98 [C4] 0.7 0.6 0.2 0.77 I want to extracts the diagonals to get a matrix which looks like this (C1 becomes C2 in 2002, C2 becomes C3 in 2003

Yes you are right ... an example is mandatory. So ... I have a matrix of 0 with just a single 1 per row and per column I need to extract all maximal 'diagonal' submatrices Let's say I have the following matrix A B C D E a 0 1 0 0 0 b 1 0 0 0 0 c 0 0 1 0 0 d 0 0 0 1 0 e 0 0 0 0 1 well I would like to get, for this example, the two following submatrices A B C D E

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

Hi I would like to fit a non-linear regression to the follwoing data: quantiles<-c(seq(.05,.95,0.05)) slopes<-c( 0.000000e+00, 1.622074e-04 , 3.103918e-03 , 2.169135e-03 , 9.585523e-04 ,1.412327e-03 , 4.288103e-05, -1.351171e-04 , 2.885810e-04 ,-4.574773e-04 , -2.368968e-03, -3.104634e-03, -5.833970e-03, -6.011945e-03, -7.737697e-03 , -8.203058e-03, -7.809603e-03, -6.623985e-03,

Hello, I am using Mac OS X on a power book and R 2.5.0 I try to extract a diagonal from a dissimilarity matrix made with dsvdis, with this code: diag(DiTestRR) But I get this error message: Fehler in array(0, c(n, p)) : 'dim' spezifiziert ein zu großes Array english: Error in array(0, c(n, p)) : 'dim' specifies a too big array. Is there a limit to extract diagonals? I

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

The following 1460 x 1460 matrix can be throught of as 16 distinct 365 x 365 matrices. I'm trying to set off-diaganol terms in the 16 sub-matrices with indices more than +/- 5 (days) from each other to zero using some for loops. This works well for some, but not all, of the for loops. The R code I"m using follows. For some reason the third loop below zero's-out everything in the

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

Given an nxm matrix A I want to compute the nxm matrix B whose ij-th element is the sum of the elements of A lying on the diagonal that ends with element ij, i.e., b_ij = a_ij + a_(i-1)(j-1) + a_(i-2)(j-2) + ... In APL (which I no longer use), I would use the 'rotate' operator to derive an array whose columns are diagonals of the given array and then cumulate down columns. Is

Hello and sorry that I still haven?t found a solution for my problem. I need to extract the lower and upper triangle from a square matrix including the diagonal. This diagonal is not zero in that special case. I tried with as.dist w<-as.dist(w, diag = TRUE) > w 1 2 3 4 5 1 0 2 2 0 3 3 8 0 4 4 9 14 0 5 5 10 15 20 0 but found no way to keep the diagonal that is in the

Hi R-Help! I am trying to find a nicer way of extracting all the "complete" diagonals of a matrix. I am working with very large matrices that have many more rows than columns. I want to be able to extract each of the diagonals that are as long as the number of columns in the matrix. I have written a rather ugly function that presently does the job. It illustrates what I am trying to

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 ) #

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

Hello, I need to build certain interpolation logic using R. Unfortunately, I just started using R, and I'm not familiar with lots of advanced or just convenient features of the language to make this simpler. So I struggled for few days and pretty much reduced the whole exercise to the following problem, which I cannot resolve: Assume we have a vector of some values with NA: a <- c(1,