similar to: next step in randomly sampling

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

I have R randomly sampling my array made up of 2 columns of data. Here is my code randomly sampling 5 different rows from my dataset to create a new dataset of 8 rows of data: testdat<-growth[sample(5,8,replace=T),] Now I want to tell R to repeat this function 50 times and give me the output. I have been searching the internet and have been unable to figure this out. Any advice

I am trying to get R to randomly select values from my dataset (i.e. bootstrapping) with replacement. However, my attempts at this have been unsuccessful. Here is a basic example of what I am doing: I have a data vector of 8 values (i.e. data= 2,5,9,4,5,6,7,8). I used the sample function and it worked. However, it only repeated my values in the exact same order as the dataset. It did not

I apologize if this comes across as confusing. I will try to explain my situation as best I can. I have R bootstrapping my growth data for fish. It's resampling my database of age and length data and then produces several new datasets for me. In this case, it's resampling my data to create three new datasets of age and length data. Here is my code with my original data called

I am trying to get R to pick random integers from my dataset (i.e. bootstrapping) with replacement. However, my attempts at this have been unsuccessful. Here is a basic example of what I am doing: I have a data vector of 8 integers (data= 2,5,9,4,5,6,7,8). I used the sample function and it worked but it only repeated my values in the exact same order. It did not randomly sample them. Here

I calculated a large vector. Unfortunately, I have some measurement error in my data and some of the values in the vector are erroneous. I ended up wih some Infs and NaNs in the vector. I would like to filter out the Inf and NaN values and only keep the values in my vector that range from 1 to 20. Is there a way to filter out Infs and NaNs in R and end up with a clean vector? Mike

I forgot to add that I first gave a starting value for K. Nonlinear least squares won't work because my errors are not normally distributed. Any advide on my maximum likelihood function would be greatly appreciated. ---------------------------- Original Message ---------------------------- Subject: RE: [R] maximum likelihood problem From: "Ravi Varadhan" <rvaradhan at

I am trying to figure out how to run maximum likelihood in R. Here is my situation: I have the following equation: equation<-(1/LR-(exp(-k*T)*LM)*(1-exp(-k))) LR, T, and LM are vectors of data. I want to R to change the value of k to maximize the value of equation. My attempts at optim and optimize have been unsuccessful. Are these the recommended functions that I should use to maximize

Thanks to the help of people from this forum I was able to bootstrap my data and then apply a model to it. Thanks for all your help. Everything worked out well, but I am having a difficult time getting the new parameter values. I bootstrapped the data 300 times and I want to get the 300 sets of parameter estimates and plot them in Excel. Here is my code:

I''m trying to specify that a particular view must render two different partials. My spec looks like: describe AClass do it do template.should_receive(:render).with(:partial => ''foo'', :locals => { ... }) ... end describe ''some conditional case'' do it do template.should_receive(:render).with(:partial =>

Hello - I am attempting to test rsync on a series of 8 MacOS X servers. On my initial test, I configured one machine as the "sender" and one machine to "receive." On the "sending" machine, I created an rsyncd.conf file. On the "receiving" machine, I issued the command rsync --daemon To which I got no error messages. On the "sending"

Hi, I am doing a research project on application frameworks (specifically the evaluation and selection of) and Rails is one of the key frameworks I am evaluating. Does anyone know of any case studies on RoR out on the Internet? Is anyone prepared to write up a case study for me on a project that succeeded thanks to the structure and dynamism of Rails? Only needs to be 1 page. Anyone who

SSweibull() :  problems with step factor and singular gradient Hello I am working with growth data of ~4000 tree seedlings and trying to fit non-linear Weibull growth curves through the data of each plant. Since they differ a lot in their shape, initial parameters cannot be set for all plants. That’s why I use the self-starting function SSweibull(). However, I often got two error messages:

It turns out I didn't have to filter out the 1-20 values. The code of x[is.finite(x)] did the trick. Thanks!!! Mike ---------------------------- Original Message ---------------------------- Subject: Re: [R] cleaning up a vector From: "Henrique Dallazuanna" <wwwhsd at gmail.com> Date: Fri, October 1, 2010 1:55 pm To: mlarkin at rsmas.miami.edu Cc: r-help

Hi there I''m considering Rails for a new web-application planned to be built from scratch. The application has an extensive web front, and in fact most of the application is interfaced through that front and engaged through clients'' HTTP requests (i.e. the conventional way web-applications and "dynamic web-sites" work). However, some essential parts are supposed to

Hi, I am trying to understand the alternative methods that are available for selecting variables in a regression without simply imposing my own bias (having "good judgement"). The methods implimented in leaps and step and stepAIC seem to fall into the general class of stepwise procedures. But these are commonly condemmed for inducing overfitting. In Hastie, Tibshirani and Friedman

Hi everyone, I'm having trouble adding error bars to a grouped barchart in lattice. I know that this topic has been addressed quite a bit, as I've been searching the internet for a while to try to troubleshoot the issue, but I've not been able to find any solution that I could get working on my data. I was wondering if someone could look at my code and tell me what I'm doing

I'm a programmer in a biology lab who is starting to use R to automate some of our statistical analysis of growth rate determination. But I'm running into some problems as I re-code. 1) Hypotheses concerning Slope similarity/difference: I'm using R's anova(lm()) methods to analyse a model which looks like this: growth.metric ~ time * test.tube I understand that

Dear all, I am a total beginner in R, so sorry if this is the wrong place. I am using R 2.10.1 on a Mac (Mac OS 10.6.2). I have this small dataset : growth sugar 75 C 72 C 73 C 61 F 67 F 64 F 62 S 63 S I have no problem reading the table, or getting the summary, but if I try boxplot(growth~sugar, ylab="growth", xlab="sugar", data=Dataset), I have the following error :

I am analyzing a dataset on the effects of six pesticides on population growth rate of a predatory mite. The response variable is the population growth rate of the mite (ranges from negative to positive) and the exploratory variable is a categorical variable (treatment). The experiment was blocked in time (3 blocks / replicates per block) and it is unbalanced - at least 1 replicate per block. I am