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...t; process-prediction-interval > > [2] https://stats.stackexchange.com/questions/9131/obtaining- > a-formula-for-prediction-limits-in-a-linear-model/9144#9144 > -- > Sent from my phone. Please excuse my brevity. > > On December 11, 2017 9:53:01 AM PST, Damjan Krstajic < > dkrstajic at hotmail.com> wrote: > >Thank you Charles Berry for your kind reply. I don't see anything wrong > >with the word "struggling". I have spent several hours trying various R > >packages like kernlab and GPfit to use GP to create a binary > >classification mod...

...tackexchange.com/questions/177677/gaussian-process-prediction-interval [2] https://stats.stackexchange.com/questions/9131/obtaining-a-formula-for-prediction-limits-in-a-linear-model/9144#9144 -- Sent from my phone. Please excuse my brevity. On December 11, 2017 9:53:01 AM PST, Damjan Krstajic <dkrstajic at hotmail.com<mailto:dkrstajic at hotmail.com>> wrote: >Thank you Charles Berry for your kind reply. I don't see anything wrong >with the word "struggling". I have spent several hours trying various R >packages like kernlab and GPfit to use GP to create a binary &gt...

...inary classification." Cheers, Bert Bert Gunter "The trouble with having an open mind is that people keep coming along and sticking things into it." -- Opus (aka Berkeley Breathed in his "Bloom County" comic strip ) On Mon, Dec 11, 2017 at 4:53 AM, Damjan Krstajic <dkrstajic at hotmail.com> wrote: > Dear All, > > > I am struggling to find an R package which contains a function for > building a Gaussian Process model for binary classification which may > produce prediction intervals for predicted probabilities. I would be > grateful if somebody...

Dear All, I am struggling to find an R package which contains a function for building a Gaussian Process model for binary classification which may produce prediction intervals for predicted probabilities. I would be grateful if somebody could point me to such package. Thank you very much in advance. DK [[alternative HTML version deleted]]

...inary classification." Cheers, Bert Bert Gunter "The trouble with having an open mind is that people keep coming along and sticking things into it." -- Opus (aka Berkeley Breathed in his "Bloom County" comic strip ) On Mon, Dec 11, 2017 at 4:53 AM, Damjan Krstajic <dkrstajic at hotmail.com<mailto:dkrstajic at hotmail.com>> wrote: Dear All, I am struggling to find an R package which contains a function for building a Gaussian Process model for binary classification which may produce prediction intervals for predicted probabilities. I would be grateful if some...

...st wishes DK ________________________________ From: Berry, Charles <ccberry at ucsd.edu> Sent: 11 December 2017 17:04 To: Damjan Krstajic Cc: Bert Gunter; r-help at r-project.org Subject: Re: Gaussian Process Classification R packages > On Dec 11, 2017, at 8:06 AM, Damjan Krstajic <dkrstajic at hotmail.com> wrote: > > I have kindly asked for help and I am sad to receive such a reply from some on the r-help list. > > Well, you only said you were `struggling' to find a package. Bert may well have done the Google search himself and found numerous resources on such mod...

...ackexchange.com/questions/177677/gaussian-process-prediction-interval [2] https://stats.stackexchange.com/questions/9131/obtaining-a-formula-for-prediction-limits-in-a-linear-model/9144#9144 -- Sent from my phone. Please excuse my brevity. On December 11, 2017 9:53:01 AM PST, Damjan Krstajic <dkrstajic at hotmail.com> wrote: >Thank you Charles Berry for your kind reply. I don't see anything wrong >with the word "struggling". I have spent several hours trying various R >packages like kernlab and GPfit to use GP to create a binary >classification model which produces a...

> On Dec 11, 2017, at 8:06 AM, Damjan Krstajic <dkrstajic at hotmail.com> wrote: > > I have kindly asked for help and I am sad to receive such a reply from some on the r-help list. > > Well, you only said you were `struggling' to find a package. Bert may well have done the Google search himself and found numerous resources on such...

Dear all, Is there any R package which would help in analysing election results between two elections? Does anybody know any good papers which are related to this field? I am a statistician and my main research area so far has been regression and classification modelling. The analysis of two election results is new to me. Thanks in advance. Kind regards DK

Hello, We have a system which creates thousands of regression/classification models and in cases where we have only one input variable NaiveBayes throws an error. Maybe I am mistaken and I shouldn't expect to have a model with only one input variable. We use R version 2.6.0 (2007-10-03). We use caret (v4.1.19), but have tested similar code with klaR (v.0.5.8), because caret relies on

...answer is not enought explanatory... Thanks a lot, Francesco [[alternative HTML version deleted]] ------------------------------ Message: 33 Date: Fri, 10 Dec 2010 09:07:42 -0600 From: Terry Therneau <therneau at mayo.edu> To: r-help at r-project.org, Damjan Krstajic <dkrstajic at hotmail.com> Subject: Re: [R] survival: ridge log-likelihood workaround Message-ID: <1291993662.26439.22.camel at punchbuggy> Content-Type: text/plain ------ begin inclusion --------- Dear all, I need to calculate likelihood ratio test for ridge regression. In February I have reported...

I am using R version 2.6.0 on Linux (CentOS 4.5) and have a problem with executing nearZeroVar function in the package caret. I am using the latest release of caret v4.17. I have a matrix X with 266 rows and 4 columns and when implementing nearZeroVar function from caret package I get following error message. > C <- nearZeroVar(X); Error in table(data, useNA = "no") : all

It seems to me that summary for ridge coxph() prints summary but returns NULL. It is not a big issue because one can calculate statistics directly from a coxph.object. However, for some reason the score test is not calculated for ridge coxph(), i.e score nor rscore components are not included in the coxph object when ridge is specified. Please find the code below. I use 2.9.2 R with 2.35-4 version

Dear All, I have a question regarding predict.rpart. I use rpart to build classification and regression trees and I deal with data with relatively large number of input variables (predictors). For example, I build an rpart model like this rpartModel <- rpart(Y ~ X, method="class", minsplit =1, minbucket=nMinBucket,cp=nCp); and get predictors used in building the model like

It seems to me that R returns the unpenalized log-likelihood for the ratio likelihood test when ridge regression Cox proportional model is implemented. Is this as expected? In the example below, if I am not mistaken, fit$loglik[2] is unpenalized log-likelihood for the final estimates of coefficients. I would expect to get the penalized log-likelihood. I would like to check if this is as expected.

Dear all, I am interested to calculate confidence interval for fitted values in general for non-linear regressions. Lets say we have y=f(x1,x2,..xN) where f() is a non-linear regression. I would like to calculate a confidence interval for new prediction f(a1,..,aN). I am aware of techniques for calculating confidence intervals for coeffiecients in specific non-linear regressions and with them

Dear all, If I am not mistaken, I think that I have found a bug in glmnet 1.7.1 (latest version) for multinomial when alpha=0. Here is the code > library(glmnet) Loading required package: Matrix Loading required package: lattice Loaded glmnet 1.7.1 > x=matrix(rnorm(40*500),40,500) > g4=sample(1:7,40,replace=TRUE) > fit=glmnet(x,g4,family="multinomial",alpha=0) >

Dear all, I am confused with the behaviour of survfit with newdata option. I am using the latest version R-2-15-0. In the simple example below I am building a coxph model on 90 patients and trying to predict 10 patients. Unfortunately the survival curve at the end is for 90 patients. Could somebody please from the survival package confirm that this behaviour is as expected or not - because I

Dear all, I will present R language and R software environment to the Statistical Society of Serbia. As I will doing it to professional statisticians it seems unneccesary to me to present them how R language works in details. I am more interested to present them with the latest facts regarding R (approximately number of users, number of add-on packages etc.) and in general why they should start

Dear all, I need to calculate likelihood ratio test for ridge regression. In February I have reported a bug where coxph returns unpenalized log-likelihood for final beta estimates for ridge coxph regression. In high-dimensional settings ridge regression models usually fail for lower values of lambda. As the result of it, in such settings the ridge regressions have higher values of lambda (e.g.