similar to: Scaled MPSE as a test for regressors?

Hi Sacha, On second thought, perhaps this is more the direction that you want ... X2 = cbind(X_train,y_train) colnames(X2)[3] = "y" regr2<-randomForest(y~x1+x2, data=X2,maxnodes=10, ntree=10) regr regr2 #Make prediction predictions= predict(regr, X_test) predictions2= predict(regr2, X_test) HTH, Eric On Tue, May 9, 2023 at 6:40?AM Eric Berger <ericjberger at gmail.com>

Dear R-experts, Here below a toy example with some error messages, especially at the end of the code (Tuning the parameters). Your help to correct my R code would be highly appreciated. ####################################### #libraries library(lattice) library(ggplot2) library(caret) library(randomForest) ?? #Data

Hello all, I am relatively new to R, but enjoying it very much. I am hoping that someone on this list can help me with an issue I am having. I am having issues with iterations over nleqslv, in that the solver does not appear to clean up memory used in previous iterations. I believe I've isolated the/my issue in a small sample of code: library(nleqslv) cons_ext_test <- function(x){

Hi, Is there any way to load workspaces (e.g. stuff from save.image) from the command line? I'm on Linux, and would find this very helpful. I'm guessing this functionality can be duplicated with a skillful bash script to rename the particular file to .RData (and then back once R terminates), but I'm wondering if there's a better way. Zhou Fang

Hi guys I have been using R for a few months now and have come across an error that I have been trying to fix for a week or so now.I am trying to build a classifer that will classify the wine dataset using Naive Bayes. My code is as follows library (e1071) wine<- read.csv("C:\\Rproject\\Wine\\wine.csv") split<-sample(nrow(wine), floor(nrow(wine) * 0.5)) wine_training <-

The model matrix for the code at the end the email is shown below. Since the model matrix doesn't have -1, I think that it is made of dummy regressors rather than deviation regressors. I'm wondering how to make a model matrix using deviation regressors. Could somebody let me know? > model.matrix(aaov) (Intercept) A2 B2 B3 A2:B2 A2:B3 1 1 0 0 0 0 0 2

To make a long story short I was doing some in-sample testing in which some dynamically created regressors would end up either all true or all false based on the validation portion. In my case a new mainframe configuration (this is a crappy way to handle a level shift but I do what I can.) So here is the code snippet that finally let me pre-check my regressors and drop any of them that were all

Hello everyone, Hope you all are doing great! I have been fitting arima models and performing forecasts pretty straightforwardly in R. However, I wanted to add a couple of regressors to the arima model to see if it could improve the accuracy of the forecasts but have had a hard time trying to do so. I used the following R function: arima(x, order = c(0, 0, 0), seasonal = list(order = c(0, 0,

dear r-experts: there is probably a very easy way to do it, but it eludes me right now. I have a large data frame with, say, 26 columns named "a" through "z". I would like to define "sets of regressors" from this data frame. something like myregressors=c("b", "j", "x") lm( l ~ myregressors, data=... ) is the best way to create new

Hi, > ----- Original Message ----- >>> ----- Original Message ----- >>>> Hi all, >>>> My recent commit r187027 fixed a simple oversight of forgetting >>>> to >>>> check for __ppc__ (only checking __powerpc__), which broke my >>>> powerpc-apple-darwin8 stage1 tests, since the system gcc only >>>> provided

Hi everybody, I have built a model that includes subject ID as a random effect, and has a continous variable (time) and I want to test whether the slope of this line differs between treatments (this is tested with the interaction between treatment and "time"). My question now is that I also want to include regressors that might explain variation in this slope between subjects (and of

Hi, All. I have a logistic regression model that I have run. The question came up: which of these regressors is more important than another? (I'm using Design) Logistic Regression Model lrm(formula = iconicgesture ~ ST + SSP + magnitude + Condition + Expertise, data = d) Coef S.E. Wald Z P Intercept -3.2688 0.2854 -11.45 0.0000 ST 2.0871 0.2730 7.64

Hello, I need to perform a robust regression on data which contains errors in BOTH observations and regressors. Right now I am using rlm from the MASS package with 'method="MM"' and get visually very nice results. MASS is quite clear, however, that the described methodologies are only applicable to observation-error only data (p. 157, 4th Ed.). So here's the questions now:

Hi, Using arima on data that are in a data frame, especially when adding xreg, would be much easier if the arima function contained 1) a "data=" argument 2) the possibility to include the covariate(s) in a formula style. Ideally the call could be something like > arima(symptome, order=c(1,0,0), xreg=~trait01*mesure0, data=anxiete) ( or arima(symptome~trait01*mesure0,

Does anyone know if there is a way to specify regressors dynamically rather than explicitly? More specifically, I have a data set in "long format" that details a number of individuals and their responses to a question (which can be positive, negative, or no answer). Each individual answers as many questions as they want, so there are a different number of rows per individual. For each

On Fri, Dec 16, 2011 at 01:51:57AM -0500, David Fang wrote: > Hi, > Thanks for the quick reply again. > >> On Thu, Dec 15, 2011 at 1:17 PM, David Fang <fang at csl.cornell.edu> wrote: >>> Hi, >>> >>> I've bootstrapped llvm/clang from svn-trunk on powerpc-darwin8 (g++-4.0.1), and >>> have the following test results to share. >>>

Hi all, I've experienced this problem using step() and stepAIC() when a name of a regressors has blanks in between (R:R1.7.0, os: w2ksp4). Please look at the following code: "x" <- c(14.122739306734, 14.4831100207131, 14.5556459667089, 14.5777151911177, 14.5285815352327, 14.0217803203846, 14.0732571632964, 14.7801310180502, 14.7839362960477, 14.7862217992577)

[In future, please press reply all as there might be others in the mailing list who can help you] Without a (short) reproducible example, it would be difficult to say. BTW, I think you have mistyped the error/warning message. Does it actually say "cannot compute _correct_ p-value" or "cannot compute _exact_ p-value". See example below. > wilcox.test( 1:3, 1:10 )

Following the instruction in R website and downloading gcc and g77, I am trying to configure and build R in my Mac laptop, but got some error message that I do not know how to resolve. Do any of you know how to solve this problem? After type ./configure, I got the following message. R is now configured for powerpc-apple-darwin8.3.0 Source directory: . Installation

Hi, For anyone who might be interested, I've thrown together a little page to track my builds of llvm and clang, both release 3.0 and svn-trunk, on powerpc-darwin8. http://www.csl.cornell.edu/~fang/sw/llvm/ I'll update the list of logs each time I svn-update and build. It's nowhere as nice as a real buildbot page, but it's better than nothing. 3.0 still has over 20 test