similar to: Complex conjugate?

Hi, All: Is there a simple way to detect complex conjugates in the roots returned by 'polyroot'? The obvious comparison of each root with the complex conjugate of the next sometimes produces roundoff error, and I don't know how to bound its magnitude: (tst <- polyroot(c(1, -.6, .4))) tst[-1]-Conj(tst[-2]) [1] 3.108624e-15+2.22045e-16i

Hello everybody When one is working with complex matrices, "transpose" very nearly always means *Hermitian* transpose, that is, A[i,j] <- Conj(A[j,i]). One often writes A^* for the Hermitian transpose. I have only once seen a "real-life" case where transposition does not occur simultaneously with complex conjugation. And I'm not 100% sure that that wasn't a

Hi, Man page for 'convolve' says: conj: logical; if 'TRUE', take the complex _conjugate_ before back-transforming (default, and used for usual convolution). The complex conjugate of 'x', of 'y', of both? In fact it seems that it takes the complex conjugate of 'y' only which is OK but might be worth mentioning because (1) conj=TRUE is the

Hi all I have run into a case where I don't understand why predict.lrm and predict.glm don't yield the same results. My data look like this: set.seed(1) library(Design); ilogit <- function(x) { 1/(1+exp(-x)) } ORDER <- factor(sample(c("mc-sc", "sc-mc"), 403, TRUE)) CONJ <- factor(sample(c("als", "bevor", "nachdem",

To add to the wish-list for "convolve": For modeling processes that decay exponentially in time, e.g., fluorescence, it is desirable to have a function that convolves an arbitrary vector with an exponential using an iterative method. In the TIMP package (which won't be on CRAN till R 2.5.0 is official, but is for now at www.nat.vu.nl/~kate/TIMP) we implemented this special-purpose

Dear R-users, I am trying to translate a matlab code for calculating the Local Whittle estimator in time series with long memory originally written by Shimotsu and available free in his webpage ( http://www.econ.queensu.ca/pub/faculty/shimotsu/ ) The Matlab code is ======================================================================================= function[r] = whittle(d,x,m) % WHITTLE.M

> On Jul 3, 2019, at 4:43 PM, Krzysztof Parzyszek via llvm-dev <llvm-dev at lists.llvm.org> wrote: > > -----Original Message----- > From: David Greene <dag at cray.com> > Sent: Wednesday, July 3, 2019 2:44 PM > To: Krzysztof Parzyszek via llvm-dev <llvm-dev at lists.llvm.org> > Cc: Krzysztof Parzyszek <kparzysz at quicinc.com> > Subject: [EXT] Re:

Hello, I propose two small changes to spec.pgram to get modest speedup when dealing with input (x) having multiple columns. With plot = FALSE, I commonly see ~10-20% speedup, for a two column input matrix and the speedup increases for more columns with a maximum close to 45%. In the function as it currently exists, only the upper right triangle of pgram is necessary and pgram is not returned by

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

Dear R-ophiles, I've found something very odd when I apply convolve to ever larger vectors. Here is an example below with vectors ranging from 2^11 to 2^17. There is a funny bump up at 2^12. Then it gets very slow at 2^16. > for( i in 11:20 )print( system.time(convolve(1:2^i,1:2^i,type="o"))) user system elapsed 0.002 0.000 0.002 user system elapsed 0.373

Hi there, I'm new to R and despite searching today, I can't find a function which will compute the adjoint of a matrix A. Does this adjoint function exist in R? Thanks in advance!

Hi: I create a hermitian matrix and then perform its singular value decomposition. But when I put it back, I don't get the original hermitian matrix. I am having the same problem with spectral value decomposition as well. I am using R 1.7.0 on Windows. Here is my code: X <- matrix(rnorm(16)+1i*rnorm(16),4) X <- X + t(X) X[upper.tri(X)] <- Conj(X[upper.tri(X)]) Y <-

Greetings I have been experimenting with sampling from posterior distributions using R. Assume that I have the following observations from a normal distribution, with an unscaled joint likelihood function: normsamples = rnorm(1000,8,3) joint_likelihood = function(observations, mean, sigma){ return((sigma ^ (-1 * length(observations))) * exp(-0.5 * sum( ((observations - mean ) ^ 2)) / (sigma

Hi I have written a whole bunch of methods for objects of class "octonion". [ an octonion is a single column of an eight-row matrix. Octonions have their own multiplication rules and are a generalization of quaternions, which are columns of a four-row matrix. ] So far I've done about a dozen generic functions such as seq.octonion(), rep.octonion(), [<-.octonion(), and so on

Krzysztof Parzyszek via llvm-dev <llvm-dev at lists.llvm.org> writes: > Vectorization must know the data layout: whether we have vectors (r1, > i1, r2, i2...) or (r1, r2, ...), (i1, i2, ...). These two approaches > are not compatible. If you have vector registers that can hold 8 > floats, with the first approach you can load 4 complex numbers in a > single instruction, then

Good afternoon/morning readers. This is the first time I am trying to run some Bayesian computation in R, and am experiencing a few problems. I am working on a Poisson model for cancer rates which has a conjugate Gamma prior. 1) The first question is precisely how I work out the parameters. #Suppose I assign values to theta with *seq()* *theta<-seq(0,1,len=500)* #Then I try out the

Hi, I've been doing a lot of CA modeling lately and am now wanting to make some checkerboard plots in R. Let's say I have a matrix: > is.matrix(junk) [1] TRUE > junk [,1] [,2] [,3] [,4] [,5] [1,] 0 0 1 0 0 [2,] 0 1 1 1 0 [3,] 0 1 0 0 1 [4,] 0 1 1 1 1 [5,] 0 1 0 0 0 > and I want to make a

Hi I have made a R function 'convolve2' for convolution of two real valued vectors based on Rs 'convolve' with option type="open" - see below. (exp.length and irf.length are variables set in another part of the program) I wish to implement the function convolve2 in C and use it in a function used from R with .Call - e.g. I need to call fft in C. All I can find in the

Hi, I'm currently in the process of writing an R-installation SOP for my company. As part of that process I'm using the recommendations from the 'R Installation and Administration' document, section 3.2, "Testing an installation". This is done on an XP machine, using the latest binary of 2.11.0. The binary is downloaded and then installed from the installer. I then

Hi all, I have the following dataset, call it test.data (30 columns, and one row named "0"): ADVP ADVP AP AP CONJ CONJ CP CP DU DU INF INF MWU MWU NP NP PP PP PPRT PPRT REL REL SMN SMN SSB SSB SV1 SV1 TI TI 0 96.85 2.05 89.07 2.54 70.91 2.37 94.92 3.46 82.31 11.33 40.96 2.25 98.06 3.43 90.77 17.63 86.60 10.78 60.27 1.32 93.27 0.97 77.60