[R] Cross validation tidyLPA

Are there available some cross-validation method for LPA object?? Linda Rispetta l’ambiente: non stampare questa mail se non è necessario. Respect the environment: print this email only if necessary. __ R-help@r-project.org mailing list -- To

Re: [R] Cross validation multivariate kernel regression

> I am planning to implement Nadaraya-Watson regression model, with I'm not sure what you mean by "implement". Write a package, fit a model, or something else... Reading your whole post, I get the impression you want mid-level "building blocks", so you customize the model fitting process, in

[R] Cross validation multivariate kernel regression

Hi, This question is general- I have a data set of n observations, consisting of a single response variable y and p regressor variables.( n ~50, p~3 or 4). I am planning to implement Nadaraya-Watson regression model, with bandwidths optimized via cross-validation. For cross-validation, I will

[R] Cross-validation : can't get the predicted response on the testing data

Dear R-experts, Doing cross-validation for 2 robust regressions (HBR and fast Tau). I can't get the 2 errors rates (RMSE and MAPE). The problem is to predict the response on the testing data. I get 2 error messages. Here below the reproducible (fictional example) R code.

Re: [R] cross validation in random forest using rfcv functin

> On Aug 23, 2017, at 10:59 AM, Elahe chalabi via R-help > wrote: > > Any responds?! When I look at the original post a I see a question about a function named `rfcv` but do not see a `library` call to load such a function. I also see a reference to a help page or

[R] cross validation in random forest using rfcv functin

Any responds?! On Wednesday, August 23, 2017 5:50 AM, Elahe chalabi via R-help wrote: Hi all, I would like to do cross validation in random forest using rfcv function. As the documentation for this package says: rfcv(trainx, trainy, cv.fold=5, scale="log",

[R] cross validation in random forest using rfcv functin

Hi all, I would like to do cross validation in random forest using rfcv function. As the documentation for this package says: rfcv(trainx, trainy, cv.fold=5, scale="log", step=0.5, mtry=function(p) max(1, floor(sqrt(p))), recursive=FALSE, ...) however I don't know how to build trianx and

[R] cross validation in random forest rfcv functin

Hi all, I would like to do cross validation in random forest using rfcv function. As the documentation for this package says: rfcv(trainx, trainy, cv.fold=5, scale="log", step=0.5, mtry=function(p) max(1, floor(sqrt(p))), recursive=FALSE, ...) however I don't know how to build trianx and

Re: [R] Cross-Validation for Zero-Inflated Models

1) Helpdesk implies people whose job it is to provide support. R-help is a mailing list in which users help each other when they have spare time. 2) You sent an email to the R-help mailing list, not to Lara, whoever that is. I suggest you figure out what her email address is and send your

Re: [R] Cross-Validation for Zero-Inflated Models

Lara: I see you sent this email to the R helpdesk a really long time ago, but I was just wondering if you ever got an answer to this question. I was just thinking that I would build my own cross validation function, but if you figured out a way to do this automatically, could you let me know?

[R] cross validation with variables which have one factor only

Dear R-team I did a model selection by AIC which explain me the habitat use of my animals in six different study sites (See attached files: cross_val_CORINE04032014.csv and cross_val_CORINE04032014.r). Sites were used as random factor because they are distributed over

[R] Cross validation in R

Guys, I select 70% of my data and keep 30% of it for model validation. mydata - read.csv(file.choose(), header=TRUE) select - sample(nrow(mydata), nrow(mydata) * .7) data70 - mydata[select,] # select data30 - mydata[-select,] # testing temp.glm - glm(Death~Temperature, data=data70,

Re: [R] Cross validation in R

This code is untested, since you did not provide any example data. But it may help you get started. Jean mydata - read.csv(file.choose(), header=TRUE) library(ROCR) # ROC curve and assessment of my prediction plot(0:1, 0:1, type=n, xlab=False positive rate, ylab=True positive rate) abline(0,

Re: [R] Cross validation in R

How do i make a loop so that the process could be repeated several time, producing randomly ROC curve and under ROC values? Using the caret package http://caret.r-forge.r-project.org/ -- Max __ R-help@r-project.org mailing list

Re: [R] Cross validation for Naive Bayes and Bayes Networks

Hi Guilherme, On Sun, Apr 14, 2013 at 11:48 PM, Guilherme Ferraz de Arruda gu...@yahoo.com.br wrote: Hi, I need to classify, using Naive Bayes and Bayes Networks, and estimate their performance using cross validation. How can I do this? I tried the bnlearn package for Bayes Networks,

[R] Cross validation for Naive Bayes and Bayes Networks

Hi, I need to classify, using Naive Bayes and Bayes Networks, and estimate their performance using cross validation. How can I do this? I tried the bnlearn package for Bayes Networks, althought I need to get more indexes, not only the error rate (precision, sensitivity, ...). I also tried the

[R] Cross Validation with SVM

Good morning. I am using package e1071 to develop a SVM model. My code is: x - subset(dataset, select = -Score) y - dataset$Score model - svm(x, y,cross=10) print(model) summary(model) As 10-CV produces 10 models, I need two things: 1) To have access to each model from 10-CV.

[R] Cross validation for nls function

Hi, I've written a logistic function using nls and I'd like to do cross validation for this. Is there a package for that? Below is an example of my data and the function. N terms are presence/absence data and the response is succesful/failed data. y1-sample(0:1,100,replace=T)

[R] cross validation in glmnet

I am using cv.glmnet from glmnet package for logistic regression. my dataset is very imbalanced, 5% sample from one group, the rest from the other. I'm wondering when doing cv.glmnet for choosing lambda, is every fold having the same ratio for two groups(every fold has 5% sample from one group,

[R] cross validation in rvm not working? (kernlab package)

Hi, according to ?rvm the relevance vector machine function as implemented in the kernlab-package has an argument 'cross' with which you can perform k-fold cross validation. However, when I try to add a 10-fold cross validation I get the following error message: Error in match.arg(type,

Re: [R] cross validation in rvm not working? (kernlab package)

Please report bugs in packages to the corresponding package maintainer (perhaps suggesting a fix if you have an idea how to do that). Uwe Ligges On 14.02.2012 12:42, Martin Batholdy wrote: Hi, according to ?rvm the relevance vector machine function as implemented in the kernlab-package has

[R] Cross-validation error with tune and with rpart

Hello list, I'm trying to generate classifiers for a certain task using several methods, one of them being decision trees. The doubts come when I want to estimate the cross-validation error of the generated tree: tree - rpart(y~., data=data.frame(xsel, y), cp=0.1) ptree - prune(tree,

Re: [R] Cross-validation error with tune and with rpart

On 31/12/2011 12:34, Israel Saeta Pérez wrote: Hello list, I'm trying to generate classifiers for a certain task using several methods, one of them being decision trees. The doubts come when I want to estimate the cross-validation error of the generated tree: tree- rpart(y~.,

[R] cross-validation complex model AUC Nagelkerke R squared code

Hi there, I really tried hard to understand and find my own solution, but now I think I have to ask for your help. I already developed some script code for my problem but I doubt that it is correct. I have the following problem: Image you develop a logistic regression model with a binary

[R] cross-validation in rpart

I am trying to find out what type of sampling scheme is used to select the 10 subsets in 10-fold cross-validation process used in rpart to choose the best tree. Is it simple random sampling? Is there any documentation available on this? Thanks, Penny. -- View this message in context:

Re: [R] cross-validation in rpart

I assume you mean rpart::xpred.rpart ? The beauty of R means that you can look at the source. For the simple case (where xval is a single number) the code does indeed do simple random sampling xgroups- sample(rep(1:xval, length = nobs), nobs, replace = FALSE) If you want another sampling,

Re: [R] cross-validation in rpart

On Sat, 19 Mar 2011, Penny B wrote: I am trying to find out what type of sampling scheme is used to select the 10 subsets in 10-fold cross-validation process used in rpart to choose the best tree. Is it simple random sampling? Is there any documentation available on this? Not SRS (and least

[R] cross validation? when rlm, lmrob or lmRob

Dear community, I have fitted a model using comands above, (rlm, lmrob or lmRob). I don't have new data to validate de models obtained. I was wondering if exists something similar to CVlm in robust regression. In case there isn't, any suggestion for validation would be appreciated. Thanks,

Re: [R] Cross validation for Ordinary Kriging

Pearl, The error suggests that there is something wrong with x2, and that there is a difference between the row names of the coordinates and the data. If you call str(x2) see if the first element of @coords is different from NULL, as this can cause some problems when cross-validating. If it

Re: [R] Cross validation for Ordinary Kriging

On 1/7/2011 12:40 PM, Jon Olav Skoien wrote: Pearl, The error suggests that there is something wrong with x2, and that there is a difference between the row names of the coordinates and the data. If you call str(x2) see if the first element of @coords is different from NULL, as this can

[R] Cross validation for Ordinary Kriging

ear ALL, The last part of my thesis analysis is the cross validation. Right now I am having difficulty using the cross validation of gstat. Below are my commands with the tsport_ace as the variable: nfold - 3 part - sample(1:nfold, 69, replace = TRUE) sel - (part != 1) m.model - x2[sel, ]

Re: [R] cross validation using e1071:SVM

thank you so much for your help. if i am not wrong then createDataPartition can be used to create stratified random splits of a data set. is there other way to do that? Thank you -- View this message in context:

[R] cross validation using e1071:SVM

Hi everyone I am trying to do cross validation (10 fold CV) by using e1071:svm method. I know that there is an option (“cross”) for cross validation but still I wanted to make a function to Generate cross-validation indices using pls: cvsegments method.

Re: [R] cross validation using e1071:SVM

Hi everyone, Can you help me to plot Gamma(x/h+1) and Beta(x/h+1,(1-x)/h+1)?I want write x-seq(0,3,0.1) thank 2010/11/23 Neeti nikkiha...@gmail.com Hi everyone I am trying to do cross validation (10 fold CV) by using e1071:svm method. I know that there is an option (“cross”) for cross

Re: [R] cross validation using e1071:SVM

@Francial Giscard LIBENGUE please post your query again so that with different subject -- View this message in context: http://r.789695.n4.nabble.com/cross-validation-using-e1071-SVM-tp3055335p3055831.html Sent from the R help mailing list archive at Nabble.com.

Re: [R] cross validation using e1071:SVM

could anyone help me with my last problem. if the question is not clear please let me know thank you Hi everyone I am trying to do cross validation (10 fold CV) by using e1071:svm method. I know that there is an option (“cross”) for cross validation but still I wanted to make a

Re: [R] cross validation using e1071:SVM

Neeti, I'm pretty sure that the error is related to the confusionMAtrix call, which is in the caret package, not e1071. The error message is pretty clear: you need to pas in two factor objects that have the same levels. You can check by running the commands: str(pred_true1)

Re: [R] cross-validation for choosing regression trees

it. - Jubal Early, Firefly From: Shiyao Liu lsy...@iastate.edu To: r-help@r-project.org Date: 11/03/2010 09:04 PM Subject: [R] cross-validation for choosing regression trees Sent by: r-help-boun...@r-project.org Dear All, We came across a problem when using the tree package to analyze our data

[R] cross-validation for choosing regression trees

Dear All, We came across a problem when using the tree package to analyze our data set. First, in the tree function, if we use the default value mindev=0.01, the resulting regression tree has a single node. So, we set mindev=0, and obtain a tree with 931 terminal nodes. However, when we further

Re: [R] cross validation of SVM

From ?svm: cross if a integer value k0 is specified, a k-fold cross validation on the training data is performed to assess the quality of the model: the accuracy rate for classification and the Mean Squared Error for regression Uwe Ligges On 15.06.2010 23:14, Amy Hessen wrote: hi,

[R] cross validation of SVM

hi, could you please tell me what kind of cross validation that SVM of e1071 uses? Cheers, Amy _ View photos of singles in your area! Looking for a hot date? [[alternative

[R] cross-validation

Hi   I want to do leave-one-out cross-validation for multinomial logistic regression in R. I did multinomial logistic reg. by package nnet in R. How I do validation? by which function? response variable has 7 levels   please help me   Thanks alot Azam [[alternative HTML version

Re: [R] cross-validation

As far as my knowledge goes, nnet doesn't have a built-in function for crossvalidation. Coding it yourself is not hard though. Nnet is used in this book : http://www.stats.ox.ac.uk/pub/MASS4/ , which contains enough examples on how to do so. See also the crossval function in the bootstrap

Re: [R] cross-validation

Install the caret package and see ?train. There is also: http://cran.r-project.org/web/packages/caret/vignettes/caretTrain.pdf http://www.jstatsoft.org/v28/i05/paper Max On Tue, Jun 8, 2010 at 5:34 AM, azam jaafari azamjaaf...@yahoo.com wrote: Hi I want to do leave-one-out

[R] Cross-validation for parameter selection (glm/logit)

If my aim is to select a good subset of parameters for my final logit model built using glm(). What is the best way to cross-validate the results so that they are reliable? Let's say that I have a large dataset of 1000's of observations. I split this data into two groups, one that I use for

Re: [R] Cross-validation for parameter selection (glm/logit)

likelihood estimation is used within each model. Jay josip.2...@gmail.com Sent by: r-help-boun...@r-project.org 04/02/2010 09:14 AM To r-help@r-project.org cc Subject [R] Cross-validation for parameter selection (glm/logit) If my aim is to select a good subset of parameters for my final

Re: [R] Cross-validation for parameter selection (glm/logit)

Hi, On Fri, Apr 2, 2010 at 9:14 AM, Jay josip.2...@gmail.com wrote: If my aim is to select a good subset of parameters for my final logit model built using glm(). What is the best way to cross-validate the results so that they are reliable? Let's say that I have a large dataset of 1000's of

Re: [R] Cross-validation for parameter selection (glm/logit)

Inline below: Bert Gunter Genentech Nonclinical Statistics -Original Message- From: r-help-boun...@r-project.org [mailto:r-help-boun...@r-project.org] On Behalf Of Steve Lianoglou Sent: Friday, April 02, 2010 2:34 PM To: Jay Cc: r-help@r-project.org Subject: Re: [R] Cross-validation

Re: [R] cross-validation in plsr package

Peter Tillmann peter.tillm...@t-online.de writes: can anyone give an example how to use cross-validation in the plsr package. There are examples in the references cited on http://mevik.net/work/software/pls.html I miss to find the number of factors proposed by cross-validation as optimum.

Re: [R] cross-validation in plsr package

Kjaere Bjørn-Helge, can anyone give an example how to use cross-validation in the plsr package. There are examples in the references cited on http://mevik.net/work/software/pls.html I miss to find the number of factors proposed by cross-validation as optimum. The

Re: [R] cross-validation in plsr package

The cross-validation in the pls package does not propose a number of factors as optimum, you have to select this yourself.  (The reason for this is that there is AFAIK no theoretically founded and widely accepted way of doing this automatically.  I'd be happy to learn otherwise.) The caret

[R] cross-validation in plsr package

Dear readers, can anyone give an example how to use cross-validation in the plsr package. I miss to find the number of factors proposed by cross-validation as optimum. Thank you Peter -- View this message in context:

[R] cross validation function translated from stata

Hi, everyone: I ask for help about translating a stata program into R. The program perform cross validation as it stated. #1. Randomly divide the data set into 10 sets of equal size, ensuring equal numbers of events in each set #2. Fit the model leaving out the 1st set #3. Apply the fitted

Re: [R] cross validation function translated from stata

Hi, On Thu, Jan 21, 2010 at 8:55 AM, zhu yao mailzhu...@gmail.com wrote: Hi, everyone: I ask for help about translating a stata program into R. The program perform cross validation as it stated. #1. Randomly divide the data set into 10 sets of equal size, ensuring equal numbers of events

Re: [R] cross validation function translated from stata

Take a look at the validate.lrm function in the rms package. Note that the use of threshold probabilities results in an improper scoring rule which will mislead you. Also note that you need to repeat 10-fold CV 50-100 times for precision, and that at each repeat you have to start from zero

Re: [R] cross validation function translated from stata

Thanks Frank and Steve. I rewrite the R code as follows. # m is the number of fold to split sample, n is the loop number of cross validation library(caret) calcvnb-function(formula,dat,m,n) { cvnb-rep(0,2) dim(cvnb)-c(200,100) for (i in 1:n) { group-rep(0,length=110)

Re: [R] cross validation for species distribution

Dear, Thanks for the warmful help on New Year's EVE. Cross-validation is used to validate the predictive quality of the training data with testing data. As for the amount, the cross-validation (cv) is supposed to be based on k-fold cross-validation, k-1 for the training and 1 for the testing.

Re: [R] cross validation for species distribution

Elaine, That's a fair answer, but completely not what I meant. I was hoping that you would elaborate on the species data of species distribution models. What types of inputs and output for this particular modeling application etc. Is it the same with the function inside caret, ipred, and e1071 

Re: [R] cross validation for species distribution

You might want to be more specific about what you (exactly) intend to do. Reading the posting guide might help you get better answers. There are a few packages and functions to do what (I think) you desire. There is the train function in the caret package, the errorest function in ipred

[R] cross validation for species distribution

Dear, I wanna make cross-validation for the species data of species distribution models. Please kindly suggest any package containing cross validation suiting the purpose. Thank you. Elaine [[alternative HTML version deleted]] __

[R] cross validation/GAM/package Daim

Dear r-helpers, I estimated a generalized additive model (GAM) using Hastie's package GAM. Example: gam1 - gam(vegetation ~ s(slope), family = binomial, data=aufnahmen_0708, trace=TRUE) pred - predict(gam1, type = response) vegetation is a categorial, slope a numerical variable. Now I want to

[R] Cross-Validation for Zero-Inflated Models

Hi all I have developed a zero-inflated negative binomial model using the zeroinfl function from the pscl package, which I have carried out model selection based on AIC and have used likelihood ratio tests (lrtest from the lmtest package) to compare the nested models [My end model contains 2

[R] cross-validation

I have reviewed all the scripts that appear http://cran.es.r-project.org/ and I cann´t find any suitable for cross-validation with a model of the form y = aX^(b). exp(cZ). Please can someone help me? Thanks, a lot of!! -- View this message in context:

Re: [R] Cross-validation - lift curve

This may be somewhat useful, but I might have more later. http://florence.acadiau.ca/collab/hugh_public/index.php?title=R:CheckBinFit (the code below is copied from the URL above) CheckBinFit - function(y,phat,nq=20,new=T,...) { if(is.factor(y)) y - as.double(y) y - y-mean(y) y[y0] -

[R] Cross-validation - lift curve

Hi all, I'd like to do cross-validation on lm and get the resulting lift curve/table (or, alternatively, the estimates on 100% of my data with which I can get lift). If such a thing doesn't exist, could it be derived using cv.lm, or would we need to start from scratch? Thanks! -- Eric Siegel,

[R] Cross-validation question

Hello everyone, I have a data set that looks like the following: Year Days to the beginning of YearValue 1 30 100 1 60200 1..

[R] Cross-validation

Hi, I was trying to do cross-validation using the crossval function (bootstrap package), with the following code: - theta.fit - function(x,y){ model - svm(x,y,kernel = linear)

Re: [R] Cross Validation output

Good Day All, I have a negative binomial model that I created using the function glm.nb() with the MASS library and I am performing a cross-validation using the function cv.glm() from the boot library. I am really interested in determining the performance of this model so I can have

[R] cross validation for lme

Hello, We would like to perform a cross validation on a linear mixed model (lme) and wonder if anyone has found something analogous to cv.glm for such models? Thanks, Mark [[alternative HTML version deleted]] __ R-help@r-project.org mailing

Re: [R] cross-validation in rpart

-- begin included message I'm having a problem with custom functions in rpart, and before I tear my hair out trying to fix it, I want to make sure it's actually a problem. It seems that, when you write custom functions for rpart (init, split and eval) then rpart no longer cross-validates the

[R] cross-validation in rpart

Hello list, I'm having a problem with custom functions in rpart, and before I tear my hair out trying to fix it, I want to make sure it's actually a problem. It seems that, when you write custom functions for rpart (init, split and eval) then rpart no longer cross-validates the resulting tree to

Re: [R] Cross-validation in R

1) cv.glm is not 'in R', it is part of contributed package 'boot'. Please give credit where it is due. 2) There is nothing 'cross' about your 'home-made cross validation'. cv.glm is support software for a book, so please consult it for the definition used of cross-validation, or MASS (the

[R] Cross-validation in R

Folks; I am having a problem with the cv.glm and would appreciate someone shedding some light here. It seems obvious but I cannot get it. I did read the manual, but I could not get more insight. This is a database containing 3363 records and I am trying a cross-validation to understand the

[R] Cross Validation

Hi, I am trying to find out the best way to calculate the average LOOCV in R for several classifier for, KNN, centroid classification, DLDA and SVM. I have four types of diseases and 62 samples. Is there a R code available to do this? -- View this message in context:

Re: [R] Cross Validation

an example from my R table will calculating the average LOOCV for two treatments ALL and AML table ALL AML 11.2 .3 2.87.3 31.1.5 41.2.7 53.21.2 61.11.1 7.90 .99 81.1.32 92.1 1.2 JStainer wrote: Hi, I

Re: [R] Cross Validation

JStainer wrote: Hi, I am trying to find out the best way to calculate the average LOOCV in R for several classifier for, KNN, centroid classification, DLDA and SVM. I have four types of diseases and 62 samples. Is there a R code available to do this? -- View this message

[R] cross validation

Hi, I must have accidentally deleted my previous post. I am having a really difficult time calculating the LOOCV (leave out cross validation). table in excel genes ALL AML p.value 1 1.2 .3 .01 2 .87.3 .03 3 1.1.5 .05 4 1.2

[R] Cross Validation

Hello, How can I do a cross validation in R? Thank You! __ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal,

Re: [R] Cross Validation

http://www.burns-stat.com/pages/Tutor/bootstrap_resampling.html may be of some use to you. Patrick Burns [EMAIL PROTECTED] +44 (0)20 8525 0696 http://www.burns-stat.com (home of S Poetry and A Guide for the Unwilling S User) Carla Rebelo wrote: Hello, How can I do a cross validation in R?

[R] Cross Validation in rpart

Hello All, I'm writing a custom rpart function, and I'm wondering about cross-validation. Specifically, why isn't my splitting function being called more often with the xval increased? One would expect that, with xval=10 compared to xval=1, that the prior would call the splitting function