similar to: ANCOVA

Hello R-user! I am running R 2.7.0 on a Power Book (Tiger). (I am still R and statistics beginner) I try to find the most important variables to divide my dataset as given in a categorical variable using randomForest. Is randomForest() able to deal with count data? Or is there no difference because only the ranks are used in the trees? Thanks in advance Birgit Birgit Lemcke Institut f?r

Hello R-user! I am running R 2.7.0 on a Power Book (Tiger). (I am still R and statistics beginner) I tried rfImpute (randomForest) and as far as I understood should it replace NA`s using a proximity matrix: > set.seed(100000) > Subset5Imputed<-rfImpute(Sex~., data=Subset5) ntree OOB 1 2 300: 11.78% 12.36% 11.21% ntree OOB 1 2 300: 12.07% 12.64%

Hello R-user! I am running R 2.7.0 on a Power Book (Tiger). (I am still R and statistics beginner) I try to find the most important variables to divide my dataset as given in a categorical variable. code: Test.rf4<-randomForest(Sex~.,na.action=na.roughfix, data=Subset4, importance=TRUE, proximity=TRUE, ntree=10000, do.trace=1000, keep.forest=FALSE) My dataset contains also ordered

Hello R-user community! I am running R 2.7.0 on a Power Book (Tiger). (I am still R and statistics beginner) Presently I try to run the function metaMDS (vegan) using an existing dissimilarity-matrix. As I would like to start with this matrix I thought I could just give the matrix using the x= -argument Test<-metaMDS(x=Dist.Gower) Fehler in inherits(comm, "dist") :

Hello R-user community! I am running R 2.7.0 on a Power Book (Tiger). (I am still R and statistics beginner) I did the following : pdf("InLnegthMaxHomogeneity.pdf") boxplot(inflorescence_length_Max~Sex, main="Bartletts Homogeneity for inflorescence length",data=FemMal_Sex) Homo<-bartlett.test(FemMal_Sex$inflorescence_length_Max,FemMal_Sex$Sex) text( 2, 500,

Hello R-Cracks, I am using R 2.6.1 on a PowerBook G4. I would like to perform a discriminant function analysis. I found lda in MASS but as far as I understood, is it only working with explanatory variables of the class factor. My dataset contains variables of the classes factor and numeric. Is there another function that is able to handle this? Thank you all in advance. Greetings Birgit

Hey folks, I'm new to the R Project so I'm facing a great problem. I've read a file into R: >myVal I V L F C M A G T W S Y P H Q D N E K R 1 4,5 4,2 3,8 2,8 2,5 1,9 1,8 -0,4 -0,7 -0,9 -0,8 -1,3 -1,6 -3,2 -3,5 -3,5 -3,5 -3,5 -3,9 -4,5 > mode(myVal) [1] list Now I want to multiplicate each of this values with this one:

Hello Stephen, I am happy that you help me. Thanks a million. It is a good feeling that you confirm my assumption that dsvdis is not able to deal with missing data, because it says me that I am not completely incapable. Okay now I have the problem what to do. I used this function ´cause there is an option to weight columns differently what I haven´t found in other functions. But now I

Hello you all! I am a completely new user of R and I have a problem to solve. I am using Mac OS X on a PowerBook. I have a table that looks like this: species X1 X2 X3 X4 X5 X6 X7 X8 X9 X10 X11 X12 X13 X14 X15 X16 X17 X18 X19 X20 X21 1 Anth_cap1 1 0 0 1 0 1 0 0 1 0 0 0 0 0 0 0 1 0 0 0 1 2 Anth_crin1 1 0 0 1 0 1 0 0 1 0 1

Hi All, my script tries to do the following on factors: > ## Check for case 3: Umsatz = 0 & Kunde = 1 > for (year in 2011:2015) { + Umsatz <- paste0("Umsatz_", year) + Kunde <- paste0("Kunde01_", year) + Check <- paste0("Check_U_0__Kd_1_", year) + + cat('Creating', Check, 'from', Umsatz, "and", Kunde,

Hi Your script is not reproducible. Creating Check_U_0__Kd_1_2011 from Umsatz_2011 and Kunde01_2011 Error in ifelse(Kunden01[[Umsatz]] == 0 & Kunden01[[Kunde]] == 1, 1, 0) : object 'Kunden01' not found > This is interesting x <- c(NA, FALSE, TRUE) names(x) <- as.character(x) outer(x, x, "&") ## AND table <NA> FALSE TRUE <NA> NA FALSE

Hallo, zur Analyse von Daten zum Artenreichtum von Pflanzen, habe ich ein Glm (glm) und anschlie?end eine Anova (anova) durchgef??hrt. Nun m??chte ich f??r die signifikanten Einflussfaktoren einen Post Hoc Tukey Test durchf??hren, um zu ermitteln in wie weit die einzelnen Faktorstufen sich signifikant voneinander unterscheiden. Mit dem Befehl (TukeyHSD) komme ich nicht

Hello everybody, I have a problem with the model.table of anova. I have data (datos2) with 4 cluster (V7), calculated with daisy and hclust. str(datos2) 'data.frame': 56 obs. of 7 variables: $ Estacion: Factor w/ 56 levels "Abradelo","AltoDoRodicio",..: 1 2 3 4 5 6 7 8 9 10 ... $ Invierno: num 36 53.9 37.1 63.6 12.5 ... $ X : int 643449 616292 562796

Hi your initial ds > str(ds) 'data.frame': 2 obs. of 3 variables: $ var1: num 1 1 $ var2: logi TRUE FALSE $ var3: logi NA NA first result > str(ds) 'data.frame': 2 obs. of 6 variables: $ var1 : num 1 1 $ var2 : logi TRUE FALSE $ var3 : logi NA NA $ value_and_logical: logi TRUE TRUE $ logical_and_na : logi TRUE NA

Hello, (Power Book G4, Mac OS X, R 2.5.0) I would like to repeat the function range for 85 Vectors (V1-V85). I tried with this code: i<-0 > repeat { + i<-i+1 + if (i<85) next + range (Vi, na.rm = TRUE) + if (i==85) break + } I presume that the Vi is wrong, because in this syntax i is not known as a variable. But I don´t know how to say that it is a variable here. Would be nice if

Hello and sorry that I still haven?t found a solution for my problem. I need to extract the lower and upper triangle from a square matrix including the diagonal. This diagonal is not zero in that special case. I tried with as.dist w<-as.dist(w, diag = TRUE) > w 1 2 3 4 5 1 0 2 2 0 3 3 8 0 4 4 9 14 0 5 5 10 15 20 0 but found no way to keep the diagonal that is in the

Dear all, (Mac OS X 10.4.11, R 2.6.0) I have a quantitative dataset with a lot of Na?s in it. So many, that it is not possible to delete all rows with NA?s and also not possible, to delete all variables with NA?s. Is there a function for a principal component analysis, that can deal with so many NA?s. Thanks in advance Birgit Birgit Lemcke Institut f?r Systematische Botanik

Hello! I am R beginner and I have a question obout a simple matching. I have to datasets that i read in with: MalVar29_37<-read.table("MalVar29_37.csv", sep = ";") FemVar29_37<-read.table("FemVar29_37.csv", sep = ";") They look like this and show binary variables: V1 V2 V3 V4 V5 V6 V7 V8 V9 1 0 0 0 0 0 1 0 0 0 2 0 0 0 0 0 1

Hello all you helpful people out there! I am stil R Beginner using R 2.5.1 on a Apple Power Book G4 with Mac OS X 10.4.10 . Perhaps you haven?t understood my question in the mail yesterday. So I will try to describe my problem in a different way You see the tables. I would like to test the variables between the tables. But for some variables in some species , I have more than 1

Hello Members, I try to convert variables in a data.frame (bract.awn) in the class ordered. str(bract.awn) 'data.frame': 348 obs. of 2 variables: $ bracts.length.relative.to.flower...............Min: Factor w/ 4 levels "1","2","3","4": 2 3 3 3 3 2 1 4 3 2 ... $ bract.awn.relative.to.body.................Max : Factor w/ 4 levels