similar to: Need help on ploting Histograms

Hi, I want to generate 10000 samples from normal distribution with replacement case and every sample size is 50. What should I do ? -- View this message in context: http://r.789695.n4.nabble.com/IMPORTANT-PLEASE-HELP-ME-tp4650676.html Sent from the R help mailing list archive at Nabble.com.

Dear R users, Can anyone please tell me how to generate a large number of samples in R, given certain distribution and size. For example, if I want to generate 1000 samples of size n=100, with a N(0,1) distribution, how should I proceed? (Since I dont want to do "rnorm(100,0,1)" in R for 1000 times) Thanks for help Debbie

"classwt" in the current version of the randomForest package doesn't work too well. (It's what was in version 3.x of the original Fortran code by Breiman and Cutler, not the one in the new Fortran code.) I'd advise against using it. "sampsize" and "strata" can be use in conjunction. If "strata" is not specified, the class labels will be used.

Hi Andy, I know this topic has been discussed before on the R-help, but I was wondering if you could offer some advice specific to my application. I'm using the R random forest package to compare two classes of data, the number of cases in each class relatively low, 28 in class 1 and 9 in class 2. I'd really like to use R environment to analyze this data, however I'm finding it

Hi, The following function use to work, but now it doesn't giving the error "> CallSnow(, 100) Using snow package, asking for 2 nodes 2 slaves are spawned successfully. 0 failed. Error in checkForRemoteErrors(val) : 2 nodes produced errors; first error: no applicable method for 'lapply' applied to an object of class "list" ". Where this is the

Hi all, I have a dataset where each point is assigned to a class A, B, C, or D. Each point is also assigned to a study site. Each study site is coded with a number ranging between 1-100. This information is stored in the vector studySites. I want to run randomForests using stratified sampling, so I chose the option strata = factor(studySites) But I am not sure how to control the number of

Dear all, I am doing a regression in ramdomForest, using the option "sampsize" reduce the number of records used to produce the randomForest object. The manual says "For classification, if sampsize is a vector of the length the number of strata, then sampling is stratified by strata, and the elements of sampsize indicate the numbers to be drawn from the strata". I need my

Sorry for the repost, but I've really been looking, and can't find any syntax direction on this issue... Just browsing the documentation, and searching the list came up short... I have some unbalanced data and was wondering if, in a "0" v "1" classification forest, some combo of these options might yield better predictions when the proportion of one class is low (less

The documentation for caret::train shows a list of parameters that one can tune for each method classification/regression method. For example, for the method randomForest one can tune mtry in the call to train. But the function call to train random forests in the original package has many other parameters, e.g. sampsize, maxnodes, etc. Is there **any** way to access these parameters using train

All, I'm trying again with a slightly more generic version of my first question. I can extract the plotted values from hist(), boxplot(), and even plot.randomForest(). Observe: # get some data dat <- rnorm(100) # grab histogram data hdat <- hist(dat) hdat #provides details of the hist output #grab boxplot data bdat <- boxplot(dat) bdat #provides details of the boxplot

Hi, I am trying to estimate the sample size needed for the comparison of two groups on a certain measurement, given some previous data at hand. I find that the data collected does not follow a normal distribution, so I would like to use a non-parametric option for sample size calculation. I found the pwr package but I don't think it has this option and on the internet found that

Hi All, I am looking for a reference that explains how the randomForest function in the randomForest package uses the classwt parameter. Here: http://tolstoy.newcastle.edu.au/R/e4/help/08/05/12088.html Andy Liaw suggests not using classwt. And according to: http://r.789695.n4.nabble.com/R-help-with-RandomForest-classwt-option-td817149.html it has "not been implemented" as of 2007.

Hi all, Had struggled in getting "Strata" in randomForest to work on this. Can I get randomForest for each of its TREE, to get ALL sample from some strata to build tree, while leaving some strata TOTALLY untouched as oob? e.g. in below, how I can tell RF to, - for tree 1 in the forest, to use only Site A and B to build the tree, while using the WHOLE Site C data for the oob error

I'm trying to compute sample size requirements for a binomial exact test. we want to show that the proportion is at least 90% assuming that it is 95%, with 80% power so any asymptotic approximations are out of the questions. I was planning on using binom.test to perform the simple test against a prespecified value, but cannot find any functions for computing sample size. do any exist?

Thank you very much for the example. I think interactively I could get something. But my obstacle is to write an R script that processes my set of data automatically. My difficulty is to extract the information that appears on the screen, when R is operated interactively, from a scripts. Let me go over some steps to make sure I am doing things right. Assume my data have been read into the matrix

Dear List, I'm just creating a little application for my openmoko freerunner, unfortunately in python, so that I have to use pyogg and pyvorbis(http://ekyo.nerim.net/software/pyogg/index.html) as wrappers around the C-functions and objects. I've got it all installed, after applying some patches and trying to run an example of encoding a wave-file I just get an empty ogg-file, the

The following code tr <- rpart(Y ~ ., dat, method="class") dev <- residuals(tr, "deviance") produces the following error Error in log(x) : Non-numeric argument to mathematical function > .Traceback [[1]] [1] "log(yhat)" # line 588 of rpart [[2]] [1] "switch(type, usual = as.integer(y != yhat), pearson = (1 - yhat)/yhat, " [2] "

http://r.789695.n4.nabble.com/file/n2260087/%E6%8D%95%E8%8E%B7.png I am going to plot my data set like this, with means and 25% & 75% quentiles. I've tried "boxplot", but the output is not what I want. Should I use other functions? Thanks -- View this message in context: http://r.789695.n4.nabble.com/ploting-dots-with-quentiles-tp2260087p2260087.html Sent from the R help

I'm trying to do something very simple... I wan to plot a histogram where the y axis represent the percentage of the total sample that each bin represents. I know how to plot a histogram with the counts and density... but can't find anything that gives me perenct of sample on the y axis. Any help is appriciated Below is the script I'm working with par(mfrow=c(1,2))

hi: Yesterday I post a message about hoy to plot a time series, but someone told me to post more information about the file so here it is: the file was read using read.table and the name is list. When I use str(list) it tells the following variables: YEAR int: 2003,2003,2003....2004 MONTH int:1,1,1,1,.... DAY:int 1,1,1,... STATE: factor with 51 levels. SALES: int (sales per day) The reason why