search for: renormalize

...gmail.com /Sergey Here is the function: #Computes the s.p.a. to the doubly noncentral t at value x. #degrees of freedom n, noncentrality parameters mu and theta. #==========================================================# nctspa <- function(a,n,mu=0,theta=0,renorm=0,rec=0){ #Pass renorm=1 to renormalize the SPA to the pdf. #There is a last argument called rec. DO NOT PASS it! alpha <- mu/sqrt((1+theta/n)) normconst <- 1 if(renorm==1 & rec==0){ term1 <- integrate(nctspa, -Inf, alpha, n=n, mu=mu, theta=theta)$value term2 <- integrate(nctspa, alpha, Inf, n=n, mu=mu, the...

...your help! /Sergey Here is the function: #Computes the s.p.a. to the doubly noncentral t at value x. #degrees of freedom n, noncentrality parameters mu and theta. #==========================================================# nctspa <- function(a,n,mu=0,theta=0,renorm=0,rec=0){ #Pass renorm=1 to renormalize the SPA to the pdf. #There is a last argument called rec. DO NOT PASS it! alpha <- mu/sqrt((1+theta/n)) normconst <- 1 if(renorm==1 & rec==0){ term1 <- integrate(nctspa, -Inf, alpha, n=n, mu=mu, theta=theta)$value term2 <- integrate(nctspa, alpha, Inf, n=n, mu=mu, theta=theta)$...

...i+1]; work[i]=sqrt(acc); acc-=prev*prev; prev=this; } work[n-1]=sqrt(acc); } If this is intended to be a simple smoothing operation, I would expect that work[0] and work[n-1] must be divided by sqrt(2) and all other entries in work must be divided by sqrt(3) in order to renormalize work[]. Is there something I overlooked? Cheers, Martin --- >8 ---- List archives: http://www.xiph.org/archives/ Ogg project homepage: http://www.xiph.org/ogg/

...in > > your AEC module? > > Sure, use the right ordering (and be careful with scaling!) and it'll work. In the FIX_POINT version of the spx_fft function, where is the actual code that do the forward FFT normaliaztion by 1/N? I saw the code first maxmize the input before the FFT and renormalize it back afterwards. Isn't this making the signal bigger and easy to overflow? If I am not mistaking, the input to the kiss_fft is the 2's complement value. I use the Xilinx Logicore FFT IP which also supports the 16bit fixed point FFT and it has some internal scaling for each stage. Do I n...

...to perform a box-cox transformation to a data set and also plot > > lambda versus L(lambda) using R. Does anybody knows how can I do such a > > thing? gnlr3 in my gnlm library does both linear and nonlinear models with Box-Cox transformation. However, it is somewhat nonstandard as it renormalizes to obtain a true density whereas the standard transformation creates a function that is not a density because of the constraint that only positive values can be transformed but the normal distribution is on the whole real line. Jim -.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-....

On Oct 21, 2007, at 6:23 PM, BGB wrote: > ok, just in my case, I guess I am a little fussy/weird, wanting > efficient dot and cross products (if at all possible, though these > operations at present don't exist natively within SSE...), among > many other operations (length, lerp, renormalization, ..). > > then again, probably a fairly smart compiler could still get

...d a super high compression way of FLAC. I have tested a 1 hour WAV file of 440HTZ with a 5,25,50,75,100 normalize volume preset. This dramatically changes the compression size of the end FLAC file even though the WAV file size is identical for all 5 WAV files. Only the volume is different. When you renormalize the WAV to its original volume the file is still 100% original. My tests are the following. source file WAV. 1 hour 440HTZ tone. 600MB. volume at 100. FLAC file size is 184MB. volume at 75. FLAC file size is 166MB. volume at 50. FLAC file size is 143MB. volume at 25. FLAC file size is 10...

well, sadly, I am not sure how people are on this list... in any case, LLVM is an interesting project, and may well continue being interesting. but, in my case, I have done my own compilation framework... ok, I didn't really hear about the really interesting bits of LLVM until after I had (more or less) wrote mine... ok, my point is to maybe to have something interesting to talk about, not

--- Wayde Milas <wmilas@rarcoa.com> wrote: > On Tue, 2004-01-20 at 23:44, Josh Coalson wrote: > > Miroslav did some experiments with searching for optimum blocksize. > > from what I remember it made at best a couple percent difference. > > there was a thread about it here a while back. > > > Did his changes make it in? I can think of a coupla ways to approach

Hello!!! Thank you all for your suggestion on my last question about locfit. Now I have another question: I would like to change the evalution structure ev in locfit() to a vector/matrix. I created a vector and a matrix: > vec <- mat.or.vec(101, 1) > vec <- c(0:100) > mat <- matrix(data = vec, nrow = 101, ncol = 1) and I tried to change the ev parameter: > fit <-

...t; > nonsense (and, if possible, tell me where I'm wrong). > > If this is intended to be a simple smoothing operation, I would expect > that > > work[0] and work[n-1] must be divided by sqrt(2) and all other entries > in work > > must be divided by sqrt(3) in order to renormalize work[]. > > it computes 'sqrt(work[i-1]^2+work[i]^2+work[i+1]^2)' as intended. > [Roman Razilov] but not for first and last sample... for first sqrt(work[0]^2 + work[1]^2) and for last sqrt( work[n-2]^2 + work[n-1]^2 ), I don't know if the...

Hi list, i've got a question about the chisq.test function. in the use of the "given probabilities" method (p= ...), normally there should be typed in probabilities in the range of 0 to 1 with the absolute sum of 1.0 (r-help) But it is possible to use probabilities > than 1. or the sum <1.! without any warning message Ok, now the question, what does r calcutate in these

Dear R users, Version 0.30-1 of the np package has been released and uploaded to CRAN. The np package provides nonparametric kernel smoothing methods for mixed data types. We encourage anyone using the package to upgrade to the latest version. Description: This package provides a variety of nonparametric (and semiparametric) kernel methods that seamlessly handle a mix of continuous, unordered,

Dear R users, Version 0.30-1 of the np package has been released and uploaded to CRAN. The np package provides nonparametric kernel smoothing methods for mixed data types. We encourage anyone using the package to upgrade to the latest version. Description: This package provides a variety of nonparametric (and semiparametric) kernel methods that seamlessly handle a mix of continuous, unordered,

Yes, you're right. In fact, it's just an adaptation of a matlab command and the author advises using N^4 replications that's why it's the default in the function. The bistochastic matrix is not my subject of interest, but I need it to perform some random tranformation of a vector of incomes. Florent Bresson ----- Message d'origine ---- De : Richard M. Heiberger <rmh at

On Oct 21, 2007, at 5:27 PM, BGB wrote: > well, sadly, I am not sure how people are on this list... I'd suggest browsing through the llvmdev mailing list archive. > now, what I do with it is this: > I use C as a scripting language... > Sounds like a fun project. Note that the clang C front-end also supports use in a JIT environment: this will allow you to JIT the full

Hi Jean-Marc and list, Is the spx_fft function in fftwrap.c a standard fft function? void spx_fft(void *table, spx_word16_t *in, spx_word16_t *out) When I say standard, I mean the input "in" is 128 point short data for example and the output "out" is 128 short complex value which is stored in 256 short array with real and image part. Looks like the function did some

On Tue, 2004-01-20 at 23:44, Josh Coalson wrote: > Miroslav did some experiments with searching for optimum blocksize. > from what I remember it made at best a couple percent difference. > there was a thread about it here a while back. > Did his changes make it in? I can think of a coupla ways to approach this and I'd like to hear about what he tried. A couple of % doesnt seem

Thanks, I tried someting like this, but computation takes times for large matrices btransf <- function(y,X=length(y)^4) { N <- length(y) bm <- matrix(rep(1/N,N^2),N,N) for(j in 1:X){ coord <- sample(1:N,4,replace=T) d <- runif(1,0,min(bm[coord[1],coord[2]],bm[coord[3],coord[4]]))

These were used because the entropy coder originally came from outside libcelt, and thus did not have a common type system. It's now undergone enough modification that it's not ever likely to be used as-is in another codec without some porting effort, so there's no real reason to maintain the typedefs separately. Hopefully we'll replace these all again somedate with a common set