similar to: Complex Matrix Exponentials.

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

Is the matrix exponential available in some package? The cannonical reference is "Nineteen dubious ways to take the exponential of a matrix". (Love that title) Terry T.

On two laptops running 32-bit kubuntu, I have found that svd(), invoked within R 2.9.1 as supplied with the current ubuntu package, returns very incorrect results when presented with complex-valued input. One of the laptops is a Dell D620, the other a MacBook Pro. I've also verified the problem on a 32-bit desktop. On these same systems, R compiled from source provides apparently

> -----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 have code and documentation that don't match, but R CMD check didn't flag it. in mspath.R mspath <- function(formula, # formula with observed Markov states ~ observation times (required) qmatrix, # matrix of 1s and 0s with indices of allowed transitions (diagonal is ignored) (required) misc = FALSE, ematrix = NULL, # matrix

While working on the printing code, my colleague Zbyn?k ?lajchrt noticed that complex matrixes are sometimes misaligned: > { matrix(1i,2,13) } [,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10] [,11] [,12] [,13] [1,] 0+1i 0+1i 0+1i 0+1i 0+1i 0+1i 0+1i 0+1i 0+1i 0+1i 0+1i 0+1i 0+1i [2,] 0+1i 0+1i 0+1i 0+1i 0+1i 0+1i 0+1i 0+1i 0+1i 0+1i 0+1i 0+1i 0+1i (the values in the last four columns

Hi When using Sweave, most of my functions get called with complex arguments. They get typeset in with additions that I don't want; "1+1i" appears as "1 + (0 + 1i)" and I would rather have plain old "1+1i". Example follows: \documentclass[a4paper]{article} \title{A Test File} \author{Robin Hankin} \usepackage{a4wide} \begin{document} \maketitle A

Dear all, in R 3.1.0, this is happening: > cummin(c(1+1i,2-3i,4+5i)) Error in cummin(c(1 + (0+1i), 2 - (0+3i), 4 + (0+5i))) : 'cummax' not defined for complex numbers > cummax(c(1+1i,2-3i,4+5i)) Error in cummax(c(1 + (0+1i), 2 - (0+3i), 4 + (0+5i))) : 'cummin' not defined for complex numbers It may be fixed in R-devel, but I thought I'd mention it to make sure

This is another follow-up to the thread from September "Recent changes to as.complex(NA_real_)". A test in data.table was broken by the changes for NA coercion to complex; the breakage essentially comes from c(NA, 0+1i) # vs c(as.complex(NA), 0+1i) The former is the output we tested against; the latter is essentially (via coerceVector() in C) what's generated by our

>>>>> Michael Chirico >>>>> on Sun, 5 Nov 2023 09:41:42 -0800 writes: > This is another follow-up to the thread from September > "Recent changes to as.complex(NA_real_)". > A test in data.table was broken by the changes for NA > coercion to complex; the breakage essentially comes from > c(NA, 0+1i) > # vs

Hmm, it is not actually at odds with help(c), it is just that the autocoercion works different that it used to, so that as.complex(NA) == as.complex(NA_real) == NA_real_+0i) which now differs from NA_complex although both print as NA. I haven't been quite alert when this change was discussed, but it does look a bit unfortunate that usage patterns like c(NA, 0+1i) does not give complex NA

So, to summarize, the open questions are: (1) Should as.complex(NA_character_) give complex(r=NA_real_, i=0) instead of NA_complex_? (2) Should the first argument in c(NA, x) and c(NA_integer_, x), where typeof(x) == "complex", be promoted to complex(r=NA_real_, i=0) instead of NA_complex_? My opinions: (1) No. The imaginary part of the

>>>>> Mikael Jagan >>>>> on Wed, 8 Nov 2023 11:13:18 -0500 writes: > So, to summarize, the open questions are: > (1) Should as.complex(NA_character_) give complex(r=NA_real_, i=0) > instead of NA_complex_? > (2) Should the first argument in c(NA, x) and c(NA_integer_, x), > where typeof(x) == "complex", be promoted

Thanks Martin. My hang-up was not on what the outcome of as.complex(NA) should be, but rather, how I should read code like c(x, y) generally. Till now, I have thought of it like 'c(x, y)' is c(as(x, typeof(y)), y)` when "type(y) > type(x)". Basically in my mind, "coercion" in R <-> as.<newtype>(.) (or coerceVector() in C). So I tracked down the source

Hi all, I am going to sample two variables from two exponential distributions, but I want to specify a covariance structure between these two variables. Is there any way to do it in R? Or is there a "Multivariate Exponential" thing corresponding to the multivariate normal? Thanks in advance. Sincerely, Yanwei Zhang Department of Actuarial Research and Modeling Munich Re America Tel:

Hi there, I am trying to fit the following model with a sum of exponentials - y ~ Ae^(-md) + B e^(-nd) + c the model has 5 parameters A, b, m, n, c I am using nls to fit the data and I am using DEoptim package to pick the most optimal start values - fm4 <- function(x) x[1] + x[2]*exp(x[3] * -dist) + x[4]*exp(x[5] * -dist) fm5 <- function(x) sum((wcorr-fm4(x))^2) fm6 <- DEoptim(fm5,

I'm having trouble grokking complex NaN's. This first set examples using complex(re=NaN,im=NaN) give what I expect > Re(complex(re=NaN, im=NaN)) [1] NaN > Im(complex(re=NaN, im=NaN)) [1] NaN > Arg(complex(re=NaN, im=NaN)) [1] NaN > Mod(complex(re=NaN, im=NaN)) [1] NaN > abs(complex(re=NaN, im=NaN)) [1] NaN and so do the following > Re(complex(re=1,

The following caught me off-guard: R> z <- 1i + 1:10 R> z <- Re(z) R> z [1] 1 2 3 4 5 6 7 8 9 10 as expected. But look: R> z <- 1i + 1:10 R> make.real <- abs(z) < 1000 R> z[make.real] <- Re(z[make.real]) R> z [1] 1+0i 2+0i 3+0i 4+0i 5+0i 6+0i 7+0i 8+0i 9+0i 10+0i R> didn't make z a real vector, which is what I wanted.

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

R-3.0.1 rev 62743, binary downloaded from CRAN just now; macosx 10.8.3 Hello, eigen(symmetric=TRUE) behaves strangely when given complex matrices. The following two lines define 'A', a 100x100 (real) symmetric matrix which theoretical considerations [Bochner's theorem] show to be positive definite: jj <- matrix(0,100,100) A <- exp(-0.1*(row(jj)-col(jj))^2) A's being