similar to: Resampling Stats software

I want to use caret to build a model with an algorithm that actually has no parameters to find. How do I stop it from repeatedly building the same model 25 times? library(caret) data(mdrr) LOGISTIC_model <- train(mdrrDescr,mdrrClass ,method='glm' ,family=binomial(link="logit") ) LOGISTIC_model 528

Dear all, Here is a little coding problem. It falls in the category of "how can I do this efficiently?" rather than "how can I do this?" (I know how to do it inefficiently). So, if you want to take the challenge, keep reading, otherwise just skip to the next post - I won't be offended by that ;-) I am coding a particle filter and I want to use systematic resampling to

Dear All, I was writing a small wrapper to bootstrap a classification algorithm, but if we generate the indices in the "usual way" as: bootindex <- sample(index, N, replace = TRUE) there is a non-zero probability that all the samples belong to only one class, thus leading to problems in the fitting (or that some classes will end up with only one sample, which will be a problem

Dear UseRs I would like to show my students how to use "resampling" to solve the following simple problem: If a family has two children of which one is a boy, what is the probability that the other child is also a boy. The answer is (obviously) 1/3, and can be show easily using the usual methods. But I would like to get the students to think of resampling, by doing the following:

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

I need to encode a WAV to OGG but must resample to 22050 samples per second, but can't do that with oggdropXPd.exe. The application always crashes. What I do is: Start oggdropXPd.exe. Right-click on fish, choosing 'Encoding Options'. Under Advanced Options, I set Re-sample to 22050 samples per second. Click 'Accept'. Drag WAV on fish. In the directory where the WAV originates,

I am trying to get R to resample my dataset of two columns of age and length data for fish. I got it to work, but it is not resampling every replicate. Instead, it resamples my data once and then repeated it 5 times. Here is my dataset of 9 fish samples with an age and length for each one: Age Length 2 200 5 450 6 600 7 702 8 798 5 453 4 399 1 120 2 202 Here is my code which resamples my

Dear all, I have a grid (data frame) dataset at 0.5 x 0.5 degrees spatial resolution (720 columns x 360 rows; regular spacing) and wish to coarsen this to a resolution of 2.5 x 2.5 degrees. A simple calculation which takes the mean of a block of points to form the regridded values would do the trick. Values which should be excluded from the calculation are -9999 (unless all points within a block

Can anyone recommend a good library for performing audio downsampling? I intend to start playing around with "libresample" (http://ccrma-www.stanford.edu/~jos/resample/README-libresample-0.1.3.txt), as well as taking a look at "Secret Rabbit Code" (http://www.mega-nerd.com/SRC/), but I'd love some opinions before I get too involved with either. Free would be best, but

I'm trying to: Resample with replacement pairs of distinct rows from a 120 x 65,000 matrix H of 0's and 1's. For each resampled pair sum the resulting 2 x 65,000 matrix by column: 0 1 0 1 ... + 0 0 1 1 ... _______ = 0 1 1 2 ... For each column accumulate the number of 0's, 1's and 2's over the resamples to obtain a 3 x 65,000 matrix G. For those

Hi everyone, I recently ran a simulation on a computer using R that was hooked up to a UPS. There was one time when the power was out for length and the computer shut down. I was worried that I had lost the simulation, but upon booting the machine up, I heard the processor kick in. It sounded like the simulation had resumed. Does anyone have any experience with this? Because I live in

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

Dear R gurus, I have the following code, but I still not know how to estimate and extract confidence intervals (95%CI) from resampling. Thanks! ~Adriana #data penta<-c(770,729,640,486,450,410,400,340,306,283,278,260,253,242,240,229,201,198,190,186,180,170,168,151,150,148,147,125,117,110,107,104,85,83,80,74,70,66,54,46,45,43,40,38,10) x<-log(penta+1) plot(ecdf(x),

Hi, I'm doing some modelling (lm) for my 3rd year dissertation and I want to do some resampling, especially as I'm working with microbes, getting them to evolve resistance to antimicrobial compounds, and after each exposure I'm measuring the minimum concentration required to kill them (which I'm expecting to rise over time, or exposures), I have 5 lineages per cleaner, and

Dear all R users, I am going to use R to process some of my physiological data about eye. The problem is the recording machine does not sample in a reliably constant rate: the time intervals between data sampled can vary from 9msec to ~120msec, while most around in the 15-30msec range. The below is a fraction of a single data file of a trial: Time CursorX CursorY Pupilsize 1811543 -1 -1 -1

I have a host-parasite association matrix in which parasite species are rows and host species columns and cells contain the frequency of interactions. Some parasites are associated with many hosts, and some hosts harbor several parasites, and I want to repeatedly select only one single representative host per "generalized" (multi-host) parasite to create a new matrix in which no hosts

Hello all R-er, I'm trying to run a resampling method on some data. The current method I have takes 2+ days or a lot of memory . I was wondering if anyone has a better suggestion. Currently I take a matrix and get the correlation matrix from it. This will be called rho.A. Each element in this will be tested against the distribution from the resampled correlation B matrix. Some example

Hello there, I have a problem concerning bootstrapping in R - especially focusing on the resampling part of it. I try to sum it up in a simplified way so that I would not confuse anybody. I have a small database consisting of 20 observations (basically numbers from 1 to 20, I mean: 1, 2, 3, 4, 5, ... 18, 19, 20). I would like to resample this database many times for the bootstrap process with

Hello there, I have a problem concerning bootstrapping in R - especially focusing on the resampling part of it. I try to sum it up in a simplified way so that I would not confuse anybody. I have a small database consisting of 20 observations (basically numbers from 1 to 20, I mean: 1, 2, 3, 4, 5, ... 18, 19, 20). I would like to resample this database many times for the bootstrap process with