search for: 0.03125

#Here is a vector of IDs > cwaves [1] 86 90 185 196 197 209 210 215 216 217 218 #Here is a matrix. The rows and columns correspond to the IDs in cwaves, and the matrix is populated with a coefficient > mat 86 90 185 196 209 210 215 216 217 218 86 0 0 0 0 0 0.00000 0 0.000000 0.000000 0.000000 90 0 0 0 0 0 0.00000 0

Dear R people, I notice that the confidence intervals of a very small sample (e.g. n=6) derived from the one-sample wilcox.test are just the maximum and minimum values of the sample. This only occurs when the required confidence level is higher than 0.93. Example: > sample <- c(1.22, 0.89, 1.14, 0.98, 1.37, 1.06) > summary(sample) Min. 1st Qu. Median Mean 3rd Qu. Max.

No sé si he entendido bien la pregunta, pero creo que lo que quieres obtener es esto: (as.complex(-0.5)^(1/5)) Saludos,Salva > To: r-help-es en r-project.org > From: canadasreche en gmail.com > Date: Thu, 15 Oct 2015 10:45:10 +0200 > Subject: Re: [R-es] potencia fracional de un número negativo > > Hola. > No sé si va por aquí, pero prueba a quitar el paréntesis a (-0.5) >

Hi I have the feeling, that the argument stringsAsFactors has no impact in the function expand.grid: a <- c("PR", "NC", "A2", "BS") b <- c(1, 0.5, 0.25, 0.125, 0.0625, 0.03125) class(expand.grid(css, fscs, stringsAsFactors=FALSE)[[1]]) [1] "factor" class(expand.grid(css, fscs, stringsAsFactors=TRUE)[[1]]) [1] "factor" Also, when

Hola a tod en s. Realizando el calculo de encontrar la raíz quinta de -0.5, la cual dígito de la siguiente manera (-0.5)^(1/5) El resultado que me arroja R es NaN. Averiguando un poco entre las ayuda de las funciones aritméticas encuentro el siguiente comentario Users are sometimes surprised by the value returned, for example why (-8)^(1/3) is NaN. For double inputs, R makes use of IEC 60559

Mirando los comentarios, realmente lo que deseo es encontrar la raíz real de (-0.5)^(1/5) la cual debería ser -0.87055056329. José me hace caer en cuenta que además de no encontrar la raiz real, tampoco da todas las raiz complejas. Habría alguna manera de que tuviera en cuenta? > ------------------------------ > > Message: 6 > Date: Thu, 15 Oct 2015 11:25:39 +0200 > From: José

Hi, Jean-Marc Valin wrote: > Well, you could change the order in the encoder as long as you reverse > it in the decoder as well. Ok, I see that in the split_cb_shape_sign_unquant function, that each coefficient is tied to it's position in the nb_subvect exc coefficients. Honestly, I have problems understanding what exactly the codebook search works like. If you have the time to to

El problema del módulo es que pierde el signo. En tu caso sale igual porque has invertido el signo del coeficiente en el polinomio (en realidad se me pasó a a mí advertir que el término independiente debe ir con signo negativo): .> polyroot(z=c(0.5,0,0,0,0,1)) [1] 0.7042902+0.5116968i -0.2690149+0.8279428i -0.2690149-0.8279428i [4] 0.7042902-0.5116968i -0.8705506+0.0000000i .> .>

Optim's Nelder-Mead works correctly for this example. > optim(par=10, fn=fn, method="Nelder-Mead") x=10, ret=100.02 (memory) x=11, ret=121 (calculate) x=9, ret=81 (calculate) x=8, ret=64 (calculate) x=6, ret=36 (calculate) x=4, ret=16 (calculate) x=0, ret=0 (calculate) x=-4, ret=16 (calculate) x=-4, ret=16 (memory) x=2, ret=4 (calculate) x=-2, ret=4 (calculate) x=1, ret=1

Hello, Is it possible to adjust the level of the denoiser ? In an old beta, before you change the aggressiveness of the denoiser, it works very well with the noise of a car, a road etc... but not now. The AEC too works very well in a old beta, but now, I think there is a problem... I have tested it with the same sound card (WB 16000). In any case, your project is the best VOIP library in this

That's consistent/not surprising if the problem lies in the numerical gradient calculation step ... On 2019-05-06 10:06 a.m., Ravi Varadhan wrote: > Optim's Nelder-Mead works correctly for this example. > > >> optim(par=10, fn=fn, method="Nelder-Mead") > x=10, ret=100.02 (memory) > x=11, ret=121 (calculate) > x=9, ret=81 (calculate) > x=8, ret=64

Hi, Jean-Marc Valin wrote: >> 1. What is the point in multiplying a codebook index with some number >> ant adding a loop variable to it as done in the exc unquant function. >> for (j=0;j<subvect_size;j++) >> exc[subvect_size*i+j]+=s*0.03125*shape_cb[ind[i]*subvect_size+j]; > > That's just how you represent a 2D array in C: the codebook has

It seems that it's an old bug that was found in some other packages, but at that time not optim: https://bugs.r-project.org/bugzilla/show_bug.cgi?id=15958 and that Duncan Murdoch posted a patch already last Friday :) Thomas Am 06.05.2019 um 16:40 schrieb Ben Bolker: > That's consistent/not surprising if the problem lies in the numerical > gradient calculation step ... >

Hello, The denoiser was good with a car noise or a raod noise before the r11739. But for some situation, the actual version is perfect. That's why I think that if we can adjust the agressivity of the denoiser, we can respond to all of the situations. Maybe two parameters should be enough : high or low. For the AEC, I have to test with older versions because it's another person that

> 1. What is the point in multiplying a codebook index with some number > ant adding a loop variable to it as done in the exc unquant function. > for (j=0;j<subvect_size;j++) > exc[subvect_size*i+j]+=s*0.03125*shape_cb[ind[i]*subvect_size+j]; That's just how you represent a 2D array in C: the codebook has shape_cb_size entries and subvect_size samples per

How about this: the codebook search gives you the N best (in order) combinations of entries for the current sub-frame. You can simply compute a one-bit checksum on all the codebook entries and choose which of the N-best to use based on that and the "message" you have. Of course, there will be cases where all of the N-best match to the same checksum, but that's what error-correcting

Dear List members, I would like to ask for advise on quantile regression in R. I am trying to perform an analysis of a relationship between species abundance and its habitat requirements - the habitat requirements are, however, codes - 0,1,2,3... where 0<1<2<3 and the scale is linear - so I would be happy to treat them as continuos The analysis of the data somehow does not work, I am

"in non linear modelling finding appropriate starting values is something like an art"... (maybe from somewhere in Crawley , 2007) Here a colleague and I just want to compare different response models to a null model. This has worked OK for almost all the other data sets except that one (dumped below). Whatever our trials and algorithms, even subsetting data (to check if some singular

Ouss a ?crit : > Hello, > > Is it possible to adjust the level of the denoiser ? Not for now. > In an old beta, before you change the aggressiveness of the denoiser, it > works very well with the noise of a car, a road etc... but not now. When did that change? > The AEC too works very well in a old beta, but now, I think there is a > problem... When did that change?

Dear R users I have a really simple question (hoping for a really simple answer :-): Having estimated the spectral density of a time series "x" (heart rate data) with: x.pgram <- spectrum(x,method="pgram") I would like to compute the power in a specific energy band. Assuming that frequency(x)=4 (Hz), and that I am interested in the band between f1 and f2, is the