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---------- Forwarded message ---------- From: <r-help-bounces@r-project.org> Date: Mon, May 11, 2009 at 10:24 PM Subject: The results of your email commands To: das.moumita.online@gmail.com The results of your email command are provided below. Attached is your original message. - Results: Ignoring non-text/plain MIME parts - Unprocessed: What is the function for partial

hi, am trying to understand speex's algo. have a few questions. 1) autocorrelation: in the function, _spx_autocorr (for floating point version), there is a line ac[0] += 10; correct me if i am wrong, i suppose the addition of 10 is used to condition the autocorrelation matrix. wonder how the value of 10 is arrived at? 2) levinson durbin (LD) algo in the function _spx_lpc, i referred

Why do we get Partial correlation values greater than 1? I have used the default function pcor.mat :-- I have manipulated the default pcor.mat function a bit so ignore tha variables corr_type,element1_in_no,element2_in_no,P.Please ignore the ?pairwise? section and have a look at athe ?listwise ? part i.e else part. *pcor.mat <-

Hello, I am updating my benchmark (http://www.sciviews.org/other/benchmark.htm) to recent versions of data analysis software (including R 1.6.0 and Splus 6.1), and I now run it on a Pentium IV instead of the old Celeron 500 Mhz that candidates for retirement. I test R under Windows Xp pro with and without optimized BLAS. I use the optimized Rblas.dll for P4 found on CRAN. Here are the results.

Hi, I am turning to you with a (hopefully simple?) stats question. I would like to test equality of two correlation coefficients in a setting with three variables X,Y,Z, i.e. equality of r(X,Y) and r(Z,Y). I have found a formula to transform the "2 dependent correlations difference" to t-distribution with N-3 df: t = (rxy - rzy)* SQRT[{(n - 3)(1 + rxz)}/ {2(1 - rxy^2 - rxz^2 - rzy^2 +

I get this error while computing partial correlation. *Error in solve.default(Szz) : system is computationally singular: reciprocal condition number = 4.90109e-18* Why is it?Can anyone give me some idea ,how do i get rid it it? This is the function i use for calculating partial correlation. pcor.mat <- function(x,y,z,method="p",na.rm=T){ x <- c(x) y <- c(y)

Hi All, This is my R-version information:--- > version _ platform i486-pc-linux-gnu arch i486 os linux-gnu system i486, linux-gnu status major 2 minor 7.1 year 2008 month 06 day 23 svn rev 45970 language R version.string R version 2.7.1 (2008-06-23) While calculating partial

Can someone point me to literature and/or R software to solve the following problem: Assume n true scores t measured as x with uncorrelated errors e , i.e. x = t + e and assume each true score to a have a certain amount of correlation with some of the other true scores. The correlation matrix cx of x will have its off-diagonal entries reduced by measurement error compared to the true

Hello everybody, I am making a modified version of "Stephan Steinhaus' benchmark test for number crunching, v. 2, (see http://www.scinetificweb.com/ncrunch/ncrunch.pdf for the original version), comparing several functions of some math/stat software. R is not performing bad at all... except for the sorting of a 1,100,000 random vector (test #3) which is the worst of all (see cell F3 in

Hello everybody, I am making a modified version of "Stephan Steinhaus' benchmark test for number crunching, v. 2, (see http://www.scinetificweb.com/ncrunch/ncrunch.pdf for the original version), comparing several functions of some math/stat software. R is not performing bad at all... except for the sorting of a 1,100,000 random vector (test #3) which is the worst of all (see cell F3 in

Hi list! My Problem: all calls to international numbers will be dropped after exactly 15 minutes... I have a VoIP-account by Deutsche Telekom. This is what I see when I call someone (my parents) and the connection will be dropped: == Using SIP RTP CoS mark 5 -- Executing [+39015222222 at default:1] Set("SIP/00493511111111-00000125", "newNumber=0039015222222") in new

I can't find a way to retrieve z values and p-values from the output from lmer in the lme4 package. How is this done? Rick B.

Jens I'm not sure what you intend by "predefined assumptions". 1. If you merely want to conduct an exploratory rather than confirmatory analysis for the relevant paths, there are ways within SEM to do this. (In this case you could use John Fox's SEM package). 2. If you do not wish to assume multivariate normality, then you may use a variety of alternative (to maximum likelihood)

Hi, I have been having a tedious issue with lmer models with lots of factors and lots of levels. In order to get the basic information at the beginning of the print out I also have to generate these enormous tables as well. Is there a method command to leave off all of the effects and correlations? Or, do I have to go to string commands?

Hi useRs, I am trying to calculate the Sharpe ratio with "sharpe" of the library "tseries". The documentation requires the univariate time series to be a portfolio's cumulated returns. In this case, the example given data(EuStockMarkets) dax <- log(EuStockMarkets[,"FTSE"]) is however not the cumulated returns but rather the daily returns of the FTSE

Given an nxm matrix A I want to compute the nxm matrix B whose ij-th element is the sum of the elements of A lying on the diagonal that ends with element ij, i.e., b_ij = a_ij + a_(i-1)(j-1) + a_(i-2)(j-2) + ... In APL (which I no longer use), I would use the 'rotate' operator to derive an array whose columns are diagonals of the given array and then cumulate down columns. Is

Device manufacturer: Fideltronik INIGO Device name: Viper 1200 Device type: UPS Bus type: USB WWW: http://fideltronikinigo.com/viper/viper-1200/ " nut-scanner -U" output: [nutdev1] driver = "blazer_usb" port = "auto" vendorid = "0001" productid = "0000" product = "MEC0003" vendor =

I'm trying to write a formula method for canonical correlation analysis, that could be called similarly to lm() for a multivariate response: cancor(cbind(y1,y2,y3) ~ x1+x2+x3+x4, data=, ...) or perhaps more naturally, cancor(cbind(y1,y2,y3) ~ cbind(x1,x2,x3,x4), data=, ...) I've adapted the code from lm() to my case, but in this situation, it doesn't make sense to include an

Hello All, I would like to retrieve some of the results from the lmer(...) function in library lme4. If I run a model, say fm.1 <- lmer(y ~ 1 + (1 | x), data = dog) and try names(fm.1), I get NULL. Is there anyway to retrieve the information? Thanks

Hello, metaflac provides exporting CUEpoints, but not SEEKpoints. As i understand, cuepoints represent gaps beetween tracks (inserting pause), whereas seekpoints merely describe a list of seekable points. Can cuepoint be used just as seekpoints (in the end, the only thing which matters is that some classic media players will recognize them). In the script i have just posted before (joining