similar to: Graphics with moderately large amounts of data

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

Hello, I am getting an unexpected result from quantile(). Specifically, the return value falls outside the range of the data, which I wouldn't have thought possible for a weighted average of 2 order statistics. Is this an unintended accuracy issue or am I being too casual in my comparison (is there some analogue of 'all.equal' for "<=")? Small example: > foo <-

R-help readers, I''m having a problem with an R script (see below), which regularly generates the error message, Error in start:(start + (sample.length - 1)) : NA/NaN argument , for which I am unsure of the cause. In essence, the script (below) generates the start and end points for random subsamples from along a vector (in reality a transect (of a given length,

As an updatee to my last post, things are still not working! The drivers did get added but I'm still not sure whether I achieved this via the Add Printer Wizard or despite error messages the rpcclient adddriver did work. I did wonder if the lsa_io_sec_qos: length c does not match size 8 error is because the printer name is too long, especially as when I tried a shorter name such as HP2300 -

Further to my last post I decided to BUY a copy Suse 9.1 including Samba 3. Not only was Suse very easy to setup I managed to get Samba up and running without too many problems and can now print from Windows clients via Samba. My only remaining challenge is setting up point and print. Thanks for the responses. Regards, Chris Christopher Moss Murray McIntosh O'Brien Wellesley House 204

Hello R-users, I am trying to obtain Type III SS for an ANOVA with subsampling. My design is slightly unbalanced with either 3 or 4 subsamples per replicate. The basic aov model would be: fit <- aov(y~x+Error(subsample)) But this gives Type I SS and not Type III. But, using the drop() option: drop1(fit, test="F") I get an error message: "Error in

Can anyone comment or point me to a discussion of the pros and cons of robust regressions, vs. a more "manual" approach to trimming outliers and/or "normalizing" data used in regression analysis?

Dear all, I would like to randomly split a sample in two equally large subsamples. The sample data is stored as a matrix with each row representing an individual and each column representing some variable (e.g., name, age, sex, etc.); the first row contains the names of the variables; the first column contains the individual number (1:n, for n individuals); the number of individuals is even (so,

Hi I?m having difficulty configuring Samba running on FreeBSD. Samba version is 2.2.8a. The scenario is that we have an NT4 domain and I am looking to migrate the printers onto Samba. All of the printers are connected via print servers, mainly HP JetDirect. As far as security is concerned I am happy for guest/anonymous logon as the server will only be used for printing but I have set security to

hi, I would like to subsample the array c(1:200) at random into ten subsamples v1,v2,...,v10. I tried with to go progressively like this: > x<-c(1:200) > v1<-sample(x,20) > y<-x[-v1] > v2<-sample(y,20) and then I want to do: >x<-y[-v2] Error: subscript out of bounds.

Hello, I'm most grateful for your time to read this. I have a uber size 30GB file of 6 million records and 3000 (mostly categorical data) columns in csv format. I want to bootstrap subsamples for multinomial regression, but it's proving difficult even with my 64GB RAM in my machine and twice that swap file , the process becomes super slow and halts. I'm thinking about generating

Dear R users, This is more a statistical question rather than an R question. I'd appreciate it if you can give me some suggestions. I have a sample of a time series (sample size 500, fat tail in density). I am trying to calculate the Standard error of standard deviation of a sub-block-sample (sample size 250). I take 100 this kind of sub-block-sample, randomly. For these 100 subsamples, I

Hey there! I got a pseudo code and don't know how to apply it to R, maybe someone can help me: Input: A dataset X, kmax: maximum number of clusters, num_subsamples: number of subsamples. Output: S(i; k) - a distribution of similarities between partitions into k clusters of a reference clustering and clustering of subsamples; i = 1 to num_subsamples Requires: T = cluster(X): A hierarchical

I'm using the fwdmsa package to identify deviant cases in a Mokken scale analysis. I've run into a problem., separate from the one I posted previously. The problem comes with items that are "easy" by IRT standards. A good scale should include a range of difficulties; yet when I include "easy" items in a forward search I continuously run into the problem that these items

Hello, I can not get the function plot.logistic.fit.fnc() working....it returns "Error: could not find function "plot.logistic.fit.fnc"". Do I need to upload as specific package first? I am trying to check the fit of a mixed logistic model. Also, any advice for checking the assumption of independence in a mixed logistic model? Many thanks in advance, Sarah Foster

Dear list I am sorry to have to ask this question, but I have not been able to find a solution to what seems a simple problem. I have created a lattice plot of a number of regression points and lines using a function containing panel.xyplot and panel.lmline. The result is what is expected , but I cannot figure out how to obtain the coefficients of each of the regression lines. Any help

Hello I apologise for the length of this entry but please bear with me. In short: I need a way of subsampling communities from all possible communities of n taxa taken 1:n at a time without having to calculate all possible combinations (because this gives me a memory error - using combn() or expand.grid() at least). Does anyone know of a function? Or can you help me edit the combn or

Hello all, I've got a large set of data consisting of 2 continuous numerical variables, and 2 factors. I'm trying to write a function that will draw scatter plots of the 2 numerical variables for various combinations of the factors. The problem is that my function doesn't seem to understand what I want it to do even though the command works fine outside the function. Here is

Does anyone else miss email-friendly character graphics such as the following example, produced using Minitab? Histogram of C6 N = 478 N* = 21 Each * represents 2 observation(s) Midpoint Count -12 16 ******** -11 53 *************************** -10 63 ******************************** -9 83

I would like to join repeated measures for patients across two visits using a line. The program below uses symbols to represent each patient. Basically, I would like to join each pair of symbols. library(lattice) patient <- c(1,2,3,4,5,6,7,8,9,1,2,3,4,5,6,7,8,9) var <- c(826,119,168,90,572,323,122,10,42,900,250,180,120,650,400,130,12,33) visit <- c(1,1,1,1,1,1,1,1,1,2,2,2,2,2,2,2,2,2)