similar to: exponential of a matrix

Dear all, I have a population with three age-classes, at time t=0 the population is: n.zero <- c(1,0,0) I have a transition matrix A which denotes "fertility" and "survival": A <- matrix(c(0,1,5, 0.3,0,0, 0,0.5,0), ncol=3, byrow=TRUE) To obtain the population at t=1, I calculate: A %*% n.zero To obtain the population t=2, I calculate: A %*% (A %*% n.zero) ... and so

Hi, Is there a function for raising a matrix to a power? For example if you like to compute A%*%A%*%A, is there an abbreviation similar to A^3? Atte Tenkanen > A=rbind(c(1,1),c(-1,-2)) > A [,1] [,2] [1,] 1 1 [2,] -1 -2 > A^3 [,1] [,2] [1,] 1 1 [2,] -1 -8 But: > A%*%A%*%A [,1] [,2] [1,] 1 2 [2,] -2 -5

Hi, Suppose I have a matrix, A. Is there an easy way to find A^{n}? I mean, I can do something like: A %*% A %*% A %*% A for A^4, but if I want A^{10} it would be kind of annoying... Cheers, Kevin ------------------------------------------------------------------------------ Ko-Kang Kevin Wang Postgraduate PGDipSci Student Department of Statistics University of Auckland New Zealand

Hello, I was curious if there was a complex valued matrix exponential function available for R? I have some Laplace transforms of occupation times for a hidden Markov model. The matrix exponential function in the msm package does not seem to handle complex values. For example > MatrixExp(diag(1i,2)) [,1] [,2] [1,] 1 0 [2,] 0 1 Warning message: imaginary parts

Suppose I have a square matrix P P <- matrix(c(.3,.7, .7, .3), ncol=2) I know that > P * P Returns the element by element product, whereas > P%*%P Returns the matrix product. Now, P^2 also returns the element by element product. But, is there a slick way to write P %*% P %*% P Obviously, P^3 does not return the result I expect. Thanks, Harold [[alternative HTML version

I have a problem with some functions handling dates, in packages 'date' and 'survival' (they seem to be identical). For instance, from the documentation, -------------------- mdy.date {survival} R Documentation Convert to Julian Dates Description Given a month, day, and year, returns the number of days since January 1, 1960. Usage mdy.date(month, day, year, nineteen = TRUE,

Hi, Any help on this would be appreciated: I need to integrate where K is a 4x4 matrix, and SIGMA is a 4x4 matrix from say a to b, i.e. 0 to 5: integral MatrixExp(-K * s) %*% SIGMA %*% t(SIGMA) %*% MatrixExp(t(-K) s) ds t is tranpose , %*% : matrix mult , MatrixExp : matrix exponential I've use integrate before on univariate functions like f(x) = x^2 which is fine but when doing this on

> -----Original Message----- > From: Federico Calboli > Sent: Tuesday, January 20, 2004 5:40 PM > To: r-help > Subject: [R] matrix exponential: M^0 > > I would like to ask why the zeroeth power of a matrix gives me a matrix > of ones rather than the identity matrix: > > > D<-rbind(c(0,0,0),c(0,0,0),c(0,0,0)) > > D<-as.matrix(D) > > D >

I am concerned about the code under the comment /* Find canonic host name. */ in ssh.c. This replaces the hostname entered by the user with the cannonical name determined by getaddrinfo, causing the new name to be used henceforth. This includes connecting to the host, and finding its public key in a known_hosts file. getaddrinfo seems (on Debian GNU/Linux 2.2, GNU libc 2.1.3) to look up

Hi Guys, Im trying to find the exponential of a matrix. Can someone please help me do this? Thanks a lot _________________________________________________________________ View photos of singles in your area Click Here =1&lage=18&uage=55&cl=14&sl=0&dist=50&po=1&do=2&trackingid=1046138&r2s=1&_t=773166090&_r=WLM_EndText

Hello! I've a problem with the combn function and a set of vector. I would like to make a simple combination where, instead of scalars, i would like to combine vector, in order to form matrixes. In other words, i have nineteen 6-items vectors (for example coef1-coef19), that i would like to combine in n!/k!(n-k)! 6x6 matrixes. I tried with a code like this mma <-

Martyn, No, that didn't work. One other thing in the mix (which I don't think is the issue) is that I call one of the C-entry points of expm. So the DESCRIPTION file imports expm, the NAMESPACE file imports expm, and the init.c file is #include "R.h" #include "R_ext/Rdynload.h" /* Interface to expm package. */ typedef enum {Ward_2, Ward_1, Ward_buggy_octave}

I try to fit reaction kinetic data to a given hypothetical model consisting of 3 ODEs. After some reading in Bates/Watts and the literature cited there (e.g. Jennrich/Bright) I looked in R for functions that support the use of the matrix exponential method. Until now I used for a similar (but simpler) problem the nls package and fitted against the the parameterized solution function. But this

I use the very nice expm functions available from the expm and Matrix packages. My understanding is that for large sparse matrices the currently best methods available are Krylov subspace methods, but they are as far as I can tell not implemented in either of the packages mentioned, nor in any other R package I have found. Does anybody know if Krylov subspace methods are available from any R

This message is about a curious difference in timing between two ways of computing the same function. One uses expm, so is expected to be a bit slower, but "a bit" turned out to be a factor of >1000. The code is below. We would be grateful if anyone can point out any egregious bad practice in our code, or enlighten us on why one approach is so much slower than the other. The problem

Martin, I am aware of --vanilla; I use it myself for some testing. In this case R_LIBS_USER was set externally (part of my login) and does not involve any of the R scripts. That means it is inherited by any subprocess. For example: tmt1495% R --vanilla --no-environ R version 3.3.1 (2016-06-21) -- "Bug in Your Hair" Copyright (C) 2016 The R Foundation for Statistical Computing

Hi, My name is Laura. I'm a PhD student at Queen's University Belfast and have just started learning R. I was wondering if somebody could help me to see where I am going wrong in my code for estimating the parameters [mu1, mu2, lambda1] of a 2-phase Coxian Distribution. cox2.lik<-function(theta, y){ mu1<-theta[1] mu2<-theta[2] lambda1<-theta[3]

We want to join out Linux-Server: SLES 10 SP1 x86 with Samba (samba-client-3.0.24-2.23) to our W2000 Domain. so i use the command: net join -S TQ-NET.DE -UAdministrator and i get the following Errormessage: Failed to join domain! ADS join did not work, falling back to RPC... [2008/03/12 12:07:29, 0] utils/net_rpc_join.c:net_rpc_join_newstyle(350) Error in domain join verification

I have a local library which depends on the expm library. The expm library is loaded into my personal space and I have the environment variable R_LIBS_USER set appropriately. The command "library(expm)" works just fine from the command line, and in fact the package works if I do the source() and dyn.load() commands by hand. The following sequence works: tmt% R CMD build

Recently, I have been working with some data that look like two overlapping gaussian distributions. I would like to either 1) determine the mean and SD for each of the two distributions OR 2) get some (bayesian ?) statistic that estimates how likely an observation is to belong to the left-hand or right-hand distribution In case I'm using the wrong language, my data looks something like