search for: conj

...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", "weil"), 403, TRUE)) LENGTH_DIFF <- sample(-32:25, 403, TRUE) I fit two models: model.01.lrm <- lrm(ORDER ~ CONJ*LENGTH_DIFF) model.01.glm <- glm(ORDER ~ CONJ*LENGTH_DIFF, family=binomial) Then I wan...

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 mistake. Matlab and Octave sort of recognize this, as "A...

...aculty/shimotsu/ ) The Matlab code is ======================================================================================= function[r] = whittle(d,x,m) % WHITTLE.M computes the local Whittle likelihood, which uses % the periodogram of data x accoding to the definition % % Ixx(k) = w(x)*conj(w(x)), % % where % N % w(k) = (2*pi*n)^(-1/2) sum x(t)*exp(i*2*pi*(k-1)*t/N), 1 <= k <= N. % t=1 % % Katsumi Shimotsu, April 1999 % % INPUT x: data (n*1 vector)...

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...

...> > (no 'library', noR extension yet) contains definitions for 'fft', 'nextn' > > and 'convolve' where the latter was (note the ":=" for what now > > would be assignment to the base package) > > > > convolve := function (a, b, conj=F) > > { > > na <- length(a) > > nb <- length(b) > > n <- max(na, nb) > > if (nb < n) > > b <- c(b, rep(0, n - nb)) > > else if (na < n) > > a <- c(b, rep(0, n - na)) > > da <- fft(a) > > db <- fft(b)...

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...

...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 <- La.svd(X) Y$u %*% diag(Y$d) %*% t(Y$v) # this doesn't give back X Y$u %*% diag(Y$d) %*% Y$v # this works fine. Z <- La.eigen(X) # the eigen values should be real, but are not. Z$vec %*% diag(Z$val) %*% t(Z$vec) # this doesn't give back X The help for...

...) results are correct with the ubuntu packaged R as well as with R compiled on the machine. The error seems not to arise, at least sometimes, with simple 2x2 complex matrices. To check for the error, run the following: a <- matrix(rnorm(16) + rnorm(16)*1i, 4) b <- svd(a) with(b, u %*% t(Conj(u))) The result should be an identity matrix, by the definition of the singular value decomposition. Below are example runs, first on the 64-bit system where results are correct, then on one of the 32-bit systems. > version _ platform x86_64-p...

...e, play_file, out_file, tail_length) F=fopen(rec_file,'rb'); rec=fread(F,Inf,'short'); fclose (F); F=fopen(play_file,'rb'); play=fread(F,Inf,'short'); fclose (F); rec = [rec; zeros(1024,1)]; play = [play; zeros(1024,1)]; N = length(rec); corr = real(ifft(fft(rec).*conj(fft(play)))); acorr = real(ifft(fft(play).*conj(fft(play)))); [a,b] = max(corr); if b > N/2 b = b-N; end printf ("Far end to near end delay is %d samples\n", b); if (b > .3*tail_length) printf ('This is too much delay, try delaying the far-end signal a bit\n'...

...noise. The convolve function is not very big (see below). When type is not specified, it defaults to "circular". So my guess is that something mysterious might be happening inside the first else clause below, at least on some architectures. -Art Owen > convolve function (x, y, conj = TRUE, type = c("circular", "open", "filter")) { type <- match.arg(type) n <- length(x) ny <- length(y) Real <- is.numeric(x) && is.numeric(y) if (type == "circular") { if (ny != n) stop("lengt...

...unctions are applicable to objects of class "quaternion". So, for example, I have a generic function Im.octonion(): R> Im.octonion function (x) { Re(x) <- 0 return(x) } The definition of Im.quaternion() is exactly the same. Sometimes the return value is an octonion: Conj.octonion function (x) { x <- as.matrix(x) x[-1, ] <- -x[-1, ] return(as.octonion(x)) } So the last line of Conj.quaternion() would be "return(as.quaternion (x))" but would be otherwise identical. A similar story holds for each of maybe twenty generic functions. Near...

Hi, all, Does anybody got the most general expression of a unitary matrix? I found one in the book, four entries of the matrix are: (cos\theta) exp(j\alpha); -(sin\theta)exp(j(\alpha-\Omega)); (sin\theta)exp(j(\beta+\Omega)); (cos\theta) exp(j\beta); where "j" is for complex. However, since for any two unitary matrices, their product should also be a unitary matrix. When I

Is there a function in R that returns the complex conjugate of a matrix (a la 'CONJ' in IDL or 'Conjugate' in Mathmatica)?

...code is do_fft in Internals.h - but how do I use do_fft? Or should I call another C routine (and how)? How do I solve the problem in the most appropriate way? convolve2=function2(x,y) { x<- c(rep.int(0,exp.length-1),x) n <- length(y<-c(y, rep.int(0, irf.length -1))) x <- fft(fft(x) * Conj(fft(y)), inverse=TRUE) return(Re(x)/n) } -- Best wishes/bedste hilsner Gunnar Hellmund cand. scient., PhD http://staff.pubhealth.ku.dk/~guhe/ --- ?If everyone is thinking alike, then somebody isn't thinking.?

Full_Name: Bill Simpson Version: 65.1 , 0.90.1 OS: Linux Submission from: (NULL) (193.62.250.209) I reported this on r-help, but here is official bug report. The present convolve() does not do convolution by default. Its default behaviour is correlation. This is a bug. The default argument conj should be set to FALSE. The zero-padding should be on the right for linear convolution (don't ask me why you call this type="open"; I suggest type="linear"). Here is what I expect linear convolution to do: myconvolve<-function (x,h) { nx <- length(x) nh <...

...amp;" "*" "+" [8] "-" "/" "<" "<=" "==" ">" ">=" [15] "Arg" "Conj" "Im" "Mod" "Re" "^" "abs" [22] "acos" "acosh" "all" "any" "as.character" "as.complex" &quot...

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 12.46 64.98 3.32 88.54 3.70 24.33 0....

...make octonion matrices multiply as they should, in the same way that (eg) complex matrices do. Perhaps we could define "*" and "/" appropriately for vectors of class "octonion" (if such a thing makes sense): or is there a better way? Also, Mod(), Re(), and perhaps Conj() would have to be generalized to work with octonions. comments please! -- Robin Hankin Uncertainty Analyst National Oceanography Centre, Southampton European Way, Southampton SO14 3ZH, UK tel 023-8059-7743

I'm doing convolutions in the frequency domain and need to know the layout of the Fourier modes returned by fft. (This is leading up to a more involved question about moment generating functions, but I need to know if I've got this part correct first.) I think in 1D the pattern is: 0 1 2 3 -2 1 (even) 0 1 2 3 -3 2 1 (odd) In 2D is it simply (for a square matrix): 0 1 2 -1 (horizontal)

...quot;o") [1] 4 6 10 11 14 7 4 I think "open" is the right type. I want to get length(x)+length(h)-1 terms in the convolution output, which is what "open" gives. I definitely don't want "circular" BTW, the help for convolve says: If `r <- convolve(x,y, conj=TRUE, type)' and `n <- length(x)', then r[k] = sum(i=1,..,n; x[i] * y[k-i]) for k = 1,...,n. There seems to be a typo: shouldn't it be r <- convolve(x,y, conj=TRUE, type="open") or "filter" or whatever 2. x<-seq(1,100) y...