similar to: Re sampling with index

Hall all, Where can I find the two sample Cramer-von Mises test in R package? Thank you. Legendy -- View this message in context: http://www.nabble.com/Two-sample-Cramer-von-Mises-test-tp20174229p20174229.html Sent from the R help mailing list archive at Nabble.com.

Hi all, I skimmed through the archives and couldnt really find an answer to my question. One thing i dont understand of the description of the function boot() is the second variable for statistics. I have a sample of say 19 subjects out of these, using boot(), i would like to generate say 1000 samples. For these 1000 samples ill calculate an nlme() and ill use these 1000 estimators of a variable

I was attempting to use the residual resampling approach to generate 999 bootstrap samples of alpha and beta and find their confidence intervals. However, I keep getting the error message:Error in nls(resample.mp ~ cases/(alpha + (beta * cases)), start = init.values, : singular gradientafter R has only produced a few bootstraps.Could anyone suggest where I am going wrong? Would greatly

Hi, I need to resample from a long string, which is written in many lines with carriage-return marks at the end of each line. Perhaps because the data looks like a matrix, using the code: sample(data, 25, replace=T) gives me 25 columns of characters from the data because it is resampling whole columns. What I would like it to do is to treat the data as a vector that has just been spread across

Hi, I need to resample from a long string, which is written in many lines with carriage-return marks at the end of each line. Perhaps because the data looks like a matrix, using the code: sample(data, 25, replace=T) gives me 25 columns of characters from the data because it is resampling whole columns. What I would like it to do is to treat the data as a vector that has just been spread across

I'm implementing a custom bootstrap resampling procedure in R. This procedure resamples clusters of data points obtained by different subjects in an experiment. Since the bootstrap samples need to have the same size as the original dataset, `target.set.size`, I select speakers compute their data point contributions to make sure I have a set of the right size. set.seed(1)

I din't have the patience to go through your missive in detail, but do note that it is not reproducible, as you have not provided a "data" object. You **are** asked to provide a small reproducible example by the posting guide. Of course, others with more patience and/or more smarts may not need the reprex to figure out what's going on. But if not ... Cheers, Bert Bert Gunter

Hi, another question on the same topic Speex resampler at 44.1kHz seems to be very CPU intensive on Android (even more than the Opus encoder) While Speex at 48kHz is just fine. I wonder any alternate solutions or ideas ? Improve it, look for alternate solution ... I am guessing the NEON optimization are still used for both, etc. On Thu, Apr 2, 2015 at 4:46 PM, Jean-Marc Valin <jmvalin at

Dear R-listers, I do clustering on tens of individuals by thousands of traits. I have known the assignment of each individual. I want to classify the individuals by randomly resampling different subsets of the traits, for example, randomly resampling 100 traits for 100 times, then 200 traits for 100 times, then 300 traits for 100 times, ,,,,,,. By each subset of traits, I do clustering of the

Hi all, I need to estimate S.E. of a certain indicator. The function to compute the value of indicator contains two arguments. Can anybody tell me how to do it? Example: We have data: a <- c(1:10) b <- c(11:20) data <- data.frame(a, b) Function to compute value of the indicator: indicator <- function(X, Y) sum(X)/(sum(Y)*2) Next I need to do the

Hi, is there any way to tell the decoder the output sampling Fz we want ? opus_decoder_create = Sampling rate of input signal (Hz) Considering this example (VoIP-out from WebRTC/RTP) MICROPHONE(44.1/48kHz) >> [encoder created at 48kHz but with internalSampleRate set to 8kHz]>> INTERNET >> [decoder(created with 48kHz)] >> 48kHz(?) >> G.711(8kHz) This leaves us with

I'm using caret to assess classifier performance (and it's great!). However, I've found that my results differ between R2.* and R3.* - reported accuracies are reduced dramatically. I suspect that a code change to kernlab ksvm may be responsible (see version 5.16-24 here: http://cran.r-project.org/web/packages/caret/news.html). I get very different results between caret_5.15-61 +

Hello I'm using logistic regression from the Design library (lrm), then fastbw to undertake a backward selection and create a reduced model, before trying to make predictions against an independent set of data using predict.lrm with the reduced model. I wouldn't normally use this method, but I'm contrasting the results with an AIC/MMI approach. The script contains: # Determine full

Hi all, I have a matrix of 474 rows (samples) with 565 columns (variables). each of the 474 samples belong to one of 120 groups, with the groupings as a column in the above matrix. For example, the group column would be: 1 1 1 2 2 2 . . . 120 120 I want to randomly select one from each group. Not all the groups have the same number of samples, some have 4, some 3 etc. Is there a function to

Hi Julien, Quote from : http://dspguru.com/dsp/faqs/multirate/resampling "The problem is that for resampling factors close to 1.0, the interpolation factor can be quite large. For example, in the case described above of changing from the sampling rate from 48 kHz to 44.1 kHz, the ratio is only 0.91875, yet the interpolation factor is 147!" My guess is that Opus would perform similar to

Hi I have the following array: test <- array(c(1:16), dim = c(3,4,3)) test ## I call some enries using an index array test.ind <- array(rbind(c(1,2,1), c(3,3,2)), dim = c(2,3)) test[test.ind] ## suppose I want all values in the 2nd row and 4th col over ## all three 3rd dimensions test[2,4,] how to specify a test.ind array with the last index left with ',' i.e test.ind should be

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________________________________ Hi David, Thank you very much for your reply. Since I need to resample the audio in the program itself, I decided to try out the resampling API in speex. But now, I have another problem. The resampled sound is very much distorted and clicks appear quite often. (I have attached the source code I used for testing it below). The test data I had was a file sampled

Hi ALL: Suppose you have a population of N <- 5 observations, x <- c(43, 28, 7, 61, 39). From that you can draw a maximum of 10 samples without replacement of size n <- 3. (Command choose(N,n) yields 10). For instance the samples I seek are 43, 61, 7 39, 7, 28 ...etc How can I get R to do that for me, to get an exhaustive list of samples of size n drawn without replacement

Dear All, For logistic regression models: is it possible to use validate (rms package) to compute bias-corrected AUC, but have variable selection with AIC use step (or stepAIC, from MASS), instead of fastbw? More details: I've been using the validate function (in the rms package, by Frank Harrell) to obtain, among other things, bootstrap bias-corrected estimates of the AUC, when variable