similar to: Stereo mode settings

Hello, The question looks like simple. It's probably even stupid. But I spent several hours searching Internet, downloaded tons of papers, where deviance is mentioned and... And haven't found an answer. Well, it is clear for me the using of entropy when I split some node of a classification tree. The sense is clear, because entropy is an old good measure of how uniform is distribution.

Hi, I've read the Vorbis stereo documentation on square polar mapping and currently reading the source code to understand it. But there are some things which I don't quite understand and hope I can get some guidance on. I understand the decoding/decoupling part as it is the same as the one described in the stereo docs: From mapping0.c: /* channel coupling */

Dear all, I have to handle a large matrix (1000 x 10001) where in the last column i have a value that all the preceding values in the same row has to be compared to. I have made the following code : # generate a (1000 x 10001) matrix, testm # generate statistics matrix 1000 x 4: qnt <- c(0.01, 0.05) cmp_fun <- function(x) { LAST <- length(x) smpls <- x[1:(LAST-1)] real

Hi Sam, Thanks for your answer! Sorry I didn't really know how to process, but this issue block me to make some legacy C code works without having some glue with a bit static lib ;( (The change have really low risk) The changes I used locally to make dlopen/dlclose et dlsym mechanism works :) : Index: wasm/Writer.cpp =================================================================== ---

R Experts: I am conducting a meta-analysis where the effect measures to be pooled are simple proportions. For example, consider this data from Fleiss/Levin/Paik's Statistical methods for rates and proportions (2003, p189) on smokers: Study N Event P(Event) 1 86 83 0.965 2 93 90 0.968 3 136 129 0.949 4 82 70 0.854 Total

I'm trying to install packages on windows XP and I have trouble with command Rcmd build (R version 1.8.1) : In the Windows console for package maanova for example, answer is : C:\Documents and Settings\dillies\Mes documents\ghis\packages>Rcmd build maanova * checking for file 'maanova/DESCRIPTION' ... OK * preparing 'maanova': * cleaning src *

Hello, The table generated by lld (Wasm target) have a max size. So this make impossible to add some others functions in the table . As for the moment only one Table is available in WAsm this is the only way to add function in a dynamic way. Having a none static size of the table is useful for a kind dynamic loader/inker at run-time: by adding some exported functions coming from another

Using libvorbis (1.3.5) I wish to extract the raw vorbis packets.  I've built some simple code on the excellent libvorbis API overview on the xiph.org site, but the example relies on the ogg_packet struct for final output and input to decoder, and shows now examples on how to do without it. Taking a look at the vorbis_bitstream_flush() function, which in the overview is the last step before

Hi, I have a vector with 4 elements, e.g., tau_i=c(100,200,300,400), but potentially tau_i[0]=0. In a "for" loop, tau_i=c(100,200,300,400) m=4 tau_i[0]=0 # <------- ? P_i=1 for(i in 2:m) { P_i = P_i*(tau_i[i-1]-tau_i[i-2]) } Error in P_i = P_i * (tau_i[k - 1] - tau_i[k - 2]): replacement has length zero Unfortunately, I can add this potential element into

Buenas tardes, Estoy interesado en generar observaciones de una distribucion binomial bivariada en la que hay _cierto_ grado de correlacion (denotemoslo rho). Podria por favor alguien indicarme como hacerlo en R? Este es el contexto. Supongamos que se tienen dos experimentos en los que la variable respuesta _sigue_ una distribucion binomial, i.e., X_i ~Binomial(n_i, p_i), i=1,2 y que, por ahora,

Hello everyone, I want to define a function that receives the name of two variables (may include Greek letters and subscripts) and uses them into the title of a plot. My best attempt is the following: myplot <- function(var1, var2) { v=paste(var1,"==1 & ",var2,"==2"); plot(1:10, main=parse(,,v)) } But when I call it with something like myplot("Q[i]",

Hello. I have searched the archives but have not found anything. I need to solve a constrained optimisation problem for a nonlinear function (“maximum entropy formalism”). Specifically, Optimise: -1*SUM(p_ilog(p_i)) for a vector p_i of probabilities, conditional on a series of constraints of the form: SUM(T_i*p_i)=k_i for given values of T_i and k_i (these are constraints on

Suppose I have data organized in the following way: (P_i, M_j, S_k) where i, j and k and indexes for sets. I would like to analyze the data to get for example the following information: what is the average over k for (P_i, M_j) or what is the average over j and k for P_i. My question is what would be the way of doing this in R. Specifically how should I write the data in a csv file and how do I

Dear R community, I have a fairly large file with variables in rows. Every variable (thousands) needs to be regressed on a reference variable. The file is too big to load into R (or R gets too slow having done it) and I do now read in line by line with "scan" (see below) and write the results to out. Although improved, this is still very slow... Can someone please help me and suggest

Hi there I am trying to learn how to compute mle in R for a multinomial negative log likelihood function. I am using for this the book by B. Bolker "Ecological models and data in R", chapter 6: "Likelihood an all that". But he has no example for multinomial functions. What I did is the following: I first defined a function for the negative log likelihood:

Hi, I would like to know whether there exist algorithms to compute the coefficients or, at least, the degree of the minimal polynomial of a square matrix A (over the field of complex numbers)? I don't know whether this would require symbolic computation. If not, has any of the algorithms been implemented in R? Thanks very much, Ravi. P.S. Just for the sake of completeness, a

Hi All, I am trying to code an R script which gives me the time varying parameters of the NIG and GH distributions. Further, becasue I think these these time varying parameters should be more responsive to more recent observations, I would like to include a weighted likelihood estimation proceedure where the observations have an exponentially decaying weighting rather than the equal weighting

Dear all, I have define a discrete distribution P(y_i=x_i)=p_i, which I want to plot a CDF plot. However, I can not find a function in R to draw it for me after searching R and R-archive. I only find the one for the sample CDF instead my theoretical one. I find stepfun can do it for me, however, I want to plot some different CDF with same support x in one plot. I can not manage how to do it with

Dear UseRs: I have simulated data from a zero-inflated Poisson model, and would like to use a package like zicounts to test my code of fitting the model. My question is: can I use zicounts directly with the following simulated data? Create a sample of n=1000 observations from a ZIP model with no intercept and a single covariate x_{i} which is N(0,1). The logit part is logit(p_{i})=x_{i}*beta

Is someone working on the infamous high frequency boost effect ? S.Gesemann published an interesting paper three months ago: http://www.xiph.org/archives/vorbis-dev/200403/att-0005/01-sq.pdf <p> -- Giuliano. --- >8 ---- List archives: http://www.xiph.org/archives/ Ogg project homepage: http://www.xiph.org/ogg/ To unsubscribe from this list, send a message to