similar to: Lda versus Rda

Dear all, I am trying to do a n-fold cross-validation for a regularized discrimant function analysis using rda from the package klaR. However, I have problems to predict the groups from the test/validation sample. The exmaples of the R documantation and some online webpage also do not work. Does anybody know what I have done wrong? Here my code # I want to use the first 6 observations for

Hello I try to fit a LDA and RDA model to the same data, which has two classes. The problem now is that the training errors of the LDA model and the training error of the RDA model with alpha=0 are not the same. In my understanding this should be the case. Am I wrong? Can someone explain what the reason for this difference could be? Here my code: LDA model: =========== % x is a dataframe tmp =

Dear all, I'm performing RDA on plant presence/absence data, constrained by geographical locations. I'd like to constrain the RDA by the "extended matrix of geographical coordinates" -ie the matrix of geographical coordinates completed by adding all terms of a cubic trend surface regression- . This is the command I use (package vegan): >rda(Helling ~

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

Hi, I run R 2.10.1 under ubuntu 10.04 LTS (Lucid Lynx) and klaR version 0.6-4. I compute a model over a 2 classes dataset (composed of 700 examples). To that aim, I use the function NaiveBayes provided in the package klaR. When I then use the prediction function : predict(my_model, new_data). I get the following warning : "In FUN(1:747[[747L]], ...) : Numerical 0 probability with

Hi ! Right now I am learning to use svm functions available in R and trying to use these function with given example. I was stuck with svmlight function which is available in klaR package. Any help would be appreciated regarding this function. 1. I am unable to use svmlight( ) which is available in package: klaR. Although I have downloaded klaR_0.6-3 package from

Dear All, Would you please tell me how to display the sample No. on the map ? ---Below commands don't display the sample No.(from 1 to 150).--- library(som) library(klaR) iris.som3 <- som(iris[,1:4], xdim = 14,ydim = 6) library(klaR); opar<- par(xpd = NA) shardsplot(iris.som3, data.or = iris,label = TRUE) legend(3.5,14.3, col = rainbow(3), xjust =0.5, yjust = 0,legend =

Dear developeRs, my package FrF2.catlg128 holds large catalogues and is supposed to gain additional ones. All the catalogues are intended for the user. So far, the catalogues were stored in the data directory, and LazyData was "no". I understand that this is not considered wise any more (if it ever was), so that I want to change to LazyData "yes" with the next release

I've tried a few things both with prcomp(), and rda() and its friends in vegan (including biplot.rda and ordiplot), but can't find a solution. I'd like to associate subsets of the points in a resulting biplot ("sites" in the rda object) with different plotting colors/text styles to emphasize certain sets of points. I can't figure out how to keep the arrows (for

Dear all, I did a RDA and when I looked to the signification of the test with permutest, the output was non-significant. But when I used the envfit function, some of the vectors are significant. All the test's conditions are respected. What it means? Is it an error in the script? Commands and output: > permutest(rda.ind, perm=999, first=TRUE) Permutation test for rda  Call:

Sorry, I forgot to mention that I used the package "klaR". > > Dear all, I am trying to do a n-fold cross-validation for a > regularized discrimant function analysis using rda from the package > klaR. However, I have problems to predict the groups from the > test/validation sample. The exmaples of the R documantation and > some online webpage also do not work.

Dear users, I would like to process all the lists from all *.rda files that I have in one folder. Up to now, I can load all the *.rda files without any problem. The problem is when I want to access the list saved within each *.rda file (only one list per rda file). Here is my code: fpath <- "D:/R" listnames <- list.files(path=fpath, pattern=glob2rx("*.rda"),

Hi, Does anyone know how to export .RDA file (in R program) to a normal text file (readable by any text editor)? Also, how to export an object in R program into a text file (not .RDA file)? Thank you. Jittima

Hi, I have a set of gene expression data in .RDA file. I have downloaded Bioconductor and R program for analyzing these data. Anyway, I am not sure how to open this RDA file in R program (what is the command?) in order to look at these data. And which package should I use for analyzing it e.g. plot the expression image? Thank you. Jittima

Hi Im using the VEGAN package to do an RDA ordination. In my plot I get my environmental scores as arrows/vectors, but my species scores as points. I would like to get the species scores as arrows as well. I tried the envfit function, and this creates arrows, but the lenght is not proportionate to the strengh of the correlation and the point is still there (so I both have point and arrow). fit

I'm trying to perform a RDA analysis in the vegan package using the "varpart" function. I have a matrix of community structure data in different sites (rows), which I want to explain using 3 matrices of environmental data. The 3 matrices are: water quality parameters; local land use variables; total land use variables. In each matrix, the number of the rows is the same (the

Hi, to speed up computations in our RobASt family of packages, we use interpolation on a grid of precomputed values which we save together with the interpolating functions (results of splinefun essentially) in sysdata.rda in the R folder of our pkg. After adding grids for some more models, this file has grown considerably, even after application of tools::resaveRdaFiles. At the moment we are at

I am not familiar with the vegan package, so I am just making a guess here. If 'na.action=na.omit' is part of the call to varpart, try removing it from the function call and moving it above as follows: options(na.action="na.omit") RDA_Ger <- varpart(comm, x1, x2, x3, transfo="hellinger", scale = FALSE) Maybe that will help. Regards, Eric On Sat, Sep 16, 2017 at

Hi, I have written a code in R for classifying microarray data using naive bayes, the code is given below: library(e1071) train<-read.table("Z:/Documents/train.txt",header=T); test<-read.table("Z:/Documents/test.txt",header=T); cl <- c(c(rep("ALL",10), rep("AML",10))); cl <- factor(cl) model <- NaiveBayes(train,cl);

Full_Name: Byron Ellis Version: 2.1.0 OS: OS X Submission from: (NULL) (67.124.246.46) > x = charToRaw("12345") > x [1] 31 32 33 34 35 > save(x,file="x.Rda") > rm(x) > load("x.Rda") > x [1] 00 00 00 00 00 Thats no fun.