similar to: LDA and RDA: different training errors

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, ] m.valid <- x2[-sel, ] t<- fit.variogram(v,vgm(0.0437, "Exp", 26, 0)) cv69

Hello, I used the lda function from the MASS (VR) package and the rda function from the klaR package. I wanted to compare the result of this two functions by using the same training set. Thus, I used the rda function with lambda=1 an gamma=0, I should emulate the lda function and I should obtain the same result. But this it not the case, the two result are very different. My training set is

I've got something that might be a clue to understand the strange behaviour of lda in R --gui="gnome": in R --vanilla: library(MASS) load("mod23puriflda.rda") > a <- lda.default(x=mod23puriflda[,2:5],grouping=mod23puriflda[,6],CV=F) works fine. I save lda.default as a local rda file: > milda.nognome <- lda.default >

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

can you do Logistic regression in R, if so how do you do it and how do you test the fit of a model? -- View this message in context: http://n4.nabble.com/Logistic-regression-tp1059870p1059870.html Sent from the R help mailing list archive at Nabble.com.

Hi, I am trying to do multinomial regression using the glmnet package, but the following gives me an error (for no reason apparent to me): library(glmnet) cv.glmnet(x=matrix(c(1,2,3,4,5,6,1,2,3,4,5,6), nrow=6),y=as.factor(c(1,2,1,2,3,3)),family='multinomial',alpha=0.5, nfolds=2) The error i get is: Error in if (outlist$msg != "Unknown error") return(outlist) : argument is of

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

Hi, a colleague ran a stepwise discriminant analysis twice in a row and got different results, suggesting some "sochasticity" in the algorithms involved. I looked at her data and found that there was a lot of collinearity, so that I reckoned that maybe "stepclass" (klaR) cannot find a clear winner when trying to include a new variable and makes a random choice. Is that true?

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'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 ~

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:

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 am trying to implement a simple r-svm example using the iris data (only two of the classes are taken and data is within the code). I am running into some errors. I am not an expert on svm's. If any one has used it, I would appreciate their help. I am appending the code below. Thanks../Murli ####################################################### ### R-code for R-SVM ### use leave-one-out

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

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.