similar to: problems with the last version of R

R helpers, I am working with the R program performing multivariate regression trees (MRT). I have a matrix with species and environmental variables saved as a CSV file (sprot_matrix.csv), I have 42 species and 8 environmental variables (SECCHI+PH+TA+PTOT+NTOT+CHLA+AREA+ MEANDEP) for 104 samples Title SpA SpB SpC SpD Varible1 Variable2 Variable3 Sample1 Sample 2

Hello everybody! I’m trying to define the optimal number of surveys to detect the highest number of species within a monitoring season/session. To do this I want to run all the possible combinations between a set of samples and to calculate the total number of species for each combination of 2, 3, 4 …n samples events, so that at the end I will be able to define which is the lowest number of

--- included message ---- Thus, my question is: *What common measures exists for ranking/measuring variable importance of participating variables in a CART model? And how can this be computed using R (for example, when using the rpart package)* ---end ---- Consider the following printout from rpart summary(rpart(time ~ age + ph.ecog + pat.karno, data=lung)) Node number 1: 228 observations,

I have a question on generating multivariate time series surrogates using the "surrogates" function in the RTisean library. The surrogate data matrices are always much shorter than the input matrices. FYI, I'm using R version 2.12.2 on Windows XP RTisean library v 3.0.14 Tisean algorithms v 3.0.13 Creating a surrogate univariate time series returns a time series with the

As per `?intToUtf8`, and in the comments to `valid_utf8`[1], R intends to prevent illegal UTF-8 such as UTF-8 encoded UTF-16 surrogate pairs.? `R_nchar`, invoked via `base::nchar`, explicitly validates UTF-8 strings[2], but allows the surrogate: ??? > Encoding('\ud800') ??? [1] "UTF-8" ??? > nchar('\ud800')? // should be an error ??? [1] 1 The problem manifests

I'm trying to analyse some data using logistic regression in R, but I want to include random effects in the model. The glm function appears not to have options for including random effects, and the lme and nlme documentation indicates that these functions are for continuous, not dichotomous, response variables. Are there options in R for this type of analysis? Jason Marshal Bariloche,

Hi there! We have an old legacy norstar phone system m8x24-ds ( dr5 ) and a couple of m0x16. It has 5 external analog lines. It has no auto attendant, and no voicemail. So every incoming call is forwarded to a operator, she pick up the phone, talks to the caller and transfer the call to the right extension. We are in Argentina, so buying a star talk is out of the question, there is no selling of

A new version (0.7.1) of package 'subselect' has been uploaded to CRAN. Package 'subselect' provides functions which assess the quality of variable subsets as surrogates for a full data set, in an exploratory data analysis, and search for subsets which are optimal under various criteria. As of version 0.7 a new function 'leaps' has been added. 'Leaps' performs a

A new version (0.7.1) of package 'subselect' has been uploaded to CRAN. Package 'subselect' provides functions which assess the quality of variable subsets as surrogates for a full data set, in an exploratory data analysis, and search for subsets which are optimal under various criteria. As of version 0.7 a new function 'leaps' has been added. 'Leaps' performs a

Dear all, I have a probability of presence of distribution of a species of interest (varying from 0 to 1 in continuous form) and I have a set of points where I know that species really occurs. But I don´t have points of absence. So, for each true presence I know the estimated presence. I would like to know how can I compute AUC, taking account these Available data. Best wishes,

Estimados Disculpen la ignorancia, probablemente ya lo hayan respondido, pero al actualizar mi versiòn del programa y querer abrir un workspace creado con la versiòn anterior 2.11.1, indica el siguiente error. No es posible cargar el entorno de trabajo creado Gracias por su ayuda, Alejandro -- tel +54-+2944-422731 int 228 fax +54-+2944-424991 correo electrónico almarti en

Greetings, I checked the Indian diabetes data again and get one tree for the data with reordered columns and another tree for the original data. I compared these two trees, the split points for these two trees are exactly the same but the fitted classes are not the same for some cases. And the misclassification errors are different too. I know how CART deal with ties --- even we are using the

Hi all Greetings from Patagonia Argentina - this is my first message to this list. I''m having a weird problem: when I reboot some domU, some OTHER domU gets killed. Scenario: > cat /etc/SuSE-release SUSE Linux Enterprise Server 11 (x86_64) VERSION = 11 PATCHLEVEL = 1 > uname -sri Linux 2.6.32.43-0.4-xen x86_64 > rpm -qa | grep xen- kernel-xen-base-2.6.32.43-0.4.1

Dear R, Short verse of the question: Is there R code which will calculate surrogate splits and/or delta impurity for decision trees at each node? Long Version: I have local, legacy code which I use to calculate my decision trees. I would like to switch to R, but as I understand it surrogate splits are not implemented. Surrogate splits and feature ranking are described in Breiman et al

Hi there! I'm looking for a better way of getting the following code working -- can you help? Instead of having to type in: binarymissing(y ~ x1 + x2,data=mydata,na.action=na.keep) as my function call, I would prefer not having to type in na.action=na.keep each time as this will always be the same. The function na.keep is simply: na.keep <- function(X){X} The first few lines

Dear R-help, I would like to compute the variance for the proportion of treatment effect by a surrogate in a survival model (Lin, Fleming, and De Gruttola 1997 in Statistics in Medicine). The paper mentioned that the covariance matrix matches that of the covariance matrix estimator for the marginal hazard modelling of multiple events data (Wei, Lin, and Weissfeld 1989 JASA), and is implemented

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Hola, ¿qué tal? Juanjo Gibaja y yo hemos organizado un curso de R básico, no presencial, colaborativo y gratuito dirigido a aquellas personas que quieren introducirse en el mundo de R. Para más información, pueden consultarse los dos siguientes enlaces: http://www.datanalytics.com/blog/2012/06/01/curso-de-r-gratuito-no-presencial/

Thanks for the quick response Ivan. readLines with encoding='latin1' works for me (on Ubuntu). However I was more concerned with the inconsistency in results between substr and regexpr. I was expecting that if one of them errors because of an unknown encoding then the other should as well. Even better, if regexpr works, why shouldn't substr work as well? Incidentally the analogous

Hi, When I look at the summary of an rpart object run on my data, I get 7 nodes but when I plot the rpart object, I get only 3 nodes. Should the number of nodes not match in the results of the 2 functions (summary and plot) or it is not always the same? Look forward to your reply, Carol -------------------------------------------- ?summary(rpart.res) Call: rpart(formula = mydata$class ~ ., data