search for: scannf

...Rmpi version: 0.4-9 Rmpi is an interface (wrapper) to MPI APIs with interactive R slave functionalities. See `library (help=Rmpi)' for details. 2 slaves are spawned successfully. 0 failed. > lapply(list(a=as.data.frame(a),b=as.data.frame(b)),dudi.pca,scannf=F) $a Duality diagramm class: pca dudi $call: FUN(df = X[[1]], scannf = ..1) .. $b Duality diagramm class: pca dudi $call: FUN(df = X[[2]], scannf = ..1) .. > parLapply(mycluster,list(a=as.data.frame(a),b=as.data.frame(b)),dudi.pca,scannf=F) [1] "Error in FUN(X[[1]], ...) : couldn'...

...I found through the R website, but when I try to use this code, I don't know how to assign a name for the df, or what to put for "fac", and what is worse, I get an error message saying that the program cannot find the "discrimin.coa" command. Usage discrimin.coa(df, fac, scannf = TRUE, nf = 2) Arguments df a data frame containing positive or null values fac a factor defining the classes of discriminant analysis scannf a logical value indicating whether the eigenvalues bar plot should be displayed nf if scannf FALSE, an integer indicating the number of kept axes Exam...

Hi all, I am trying to compare two distance matrices with R. I would like to create a XY plot of these matrices and do some linear regression on it. But, I am a bit new to R, so i have a few questions (I searched in the documentation with no success). The first problem is loading a distance matrix into R. This matrix is the output of a the Phylip program Protdist and lookes like this: 5

...mpl-rstr" "angl-rndd" "ascn-dscn" "asym- symm" "end-bgnn" ... Thus the 37 rownames in both are the same. Now I do a pca of op: > (op.dudi <- dudi.pca(op, scale = F, scan = F)) Duality diagramm class: pca dudi $call: dudi.pca(df = op, scale = F, scannf = F) $nf: 2 axis-components saved $rank: 5 eigen values: 0.09233 0.03109 0.01322 0.002024 0.0001017 vector length mode content 1 $cw 5 numeric column weights 2 $lw 37 numeric row weights 3 $eig 5 numeric eigen values data.frame nrow ncol content 1 $tab 37 5...

Dear R users, How can I extract the residuals from a pcaiv/rda in ade4? In Vegan there is the residuals() function, giving the approximation of the original data from the unconstrained ordination Is there something similar in ade4? Nikos

...e) : infinite or missing values in 'x' Does anyone know what could be wrong. I do not have missing values in my dataset. Please follow the codes I used for my analysis so far: library (adehabitat) library (ade4) (dataenfa1 <- data2enfa(var, locs)) pc <- dudi.pca(dataenfa1$tab, scannf = FALSE) (enfa1 <- enfa(pc, dataenfa1$pr, scannf = FALSE)) Error in eigen(Se) : infinite or missing values in 'x' Any help will be much appreciated. Thank you, Leandro [[alternative HTML version deleted]]

...ión me arrojara la lista de cuáles son las variables que más influyen sobre el resultado. Revisando la información que arroja inertia.dudi, creo que con las contribuciones a los ejes podría conseguirlo. Los comandos que utilizo son los siguientes: acp <- dudi.pca(df = DATOS[,(2:1013)], scannf = FALSE, nf = 2) acpI <- inertia.dudi(acp, row.inertia = T, col.inertia = T) #CONTRIBUCIONES DE LAS COLUMNAS A LOS EJES acpI$col.abs/100 Con esto obtengo una lista similar a: Comp1 Comp2 X0 0.02 0.03 X1 0.04 0.00 X2 0.25 0.08 X3 0.12 0.07 X4 0.08 0.10 X5 0.0...

...t;- sweep(sol, 2, reve, "*") out <- out + ifelse(res > 0, sol <= 0, sol >= 0) } out/permutations } I tried to aply it to the case of dudi.mix instead of princomp this way: netoboot1<-function (x, permutations=1000,...) { dudinull <- dudi.mix(x, scannf = FALSE, nf = 3) res <- dudinull$c1 out <- matrix(0, nrow=nrow(res), ncol=ncol(res)) N <- nrow(x) for (i in 1:permutations) { dudi <- dudi.mix(x[sample(N, replace=TRUE), ], scannf = FALSE, nf = 3) pred <- predict(dudi, newdata = x) r <- cor(du...

...Sucede que al comparar las coordenadas de cada individuo que obtiene cada función, las que corresponden al segundo componente principal tienen idéntica magnitud pero con signos contrarios: Función dudi.pca: Comando: PCA1 <- dudi.pca(df = DATOS[,(2:ncol(DATOS))], center = TRUE, scale = TRUE, scannf = FALSE, nf = 6) Individuo Comp1 Comp2 1 -14.18 -4.47 2 -14.63 -4.53 3 -14.77 -2.57 4 -14.12 -1.71 5 -16.32 4.22 6 -17.03 5.94 7 -16.90 3.68 8 -17.75 5.86 9 13.86 -13.33 10 13.16 -12.71 11 13.24 -14.18 12 12.68 -13.07 13...

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

...Sucede que al comparar las coordenadas de cada individuo que obtiene cada función, las que corresponden al segundo componente principal tienen idéntica magnitud pero con signos contrarios: Función dudi.pca: Comando: PCA1 <- dudi.pca(df = DATOS[,(2:ncol(DATOS))], center = TRUE, scale = TRUE, scannf = FALSE, nf = 6) Individuo Comp1 Comp2 1 -14.18 -4.47 2 -14.63 -4.53 3 -14.77 -2.57 4 -14.12 -1.71 5 -16.32 4.22 6 -17.03 5.94 7 -16.90 3.68 8 -17.75 5.86 9 13.86 -13.33 10 13.16 -12.71 11 13.24 -14.18 12 12.68...

> Hi > I'm Ph.D student and I need an R code to compute the chi square diistance between n profile rows in a matrix. > > could you help me please? > Thanks > > Paola > ____________________________________________________________

...R_tryEval(VECTOR_ELT(e2,0), rho, &hadError); UNPROTECT(2); if(LOGICAL(e3)[0]) // succes else // echec Until this point, all my function succes ! When I try to call function in ade4 library, I have error 1 : PROTECT( e1 = mkString("a<-dudi.pca(b,scannf=FALSE, nf=2)") PROTECT( e2 = R_ParseVector(e1, 1, &status, R_NilValue) ); R_tryEval(VECTOR_ELT(e2,0), rho, &hadError); UNPROTECT(2); You know where come from the problem ? Bonus question 1 : I can't call directely the function plot(x, type="l") without p...

...uáles son las > variables que más influyen sobre el resultado. > > Revisando la información que arroja inertia.dudi, creo que con las > contribuciones a los ejes podría conseguirlo. Los comandos que utilizo son > los siguientes: > > acp <- dudi.pca(df = DATOS[,(2:1013)], scannf = FALSE, nf = 2) > > acpI <- inertia.dudi(acp, row.inertia = T, col.inertia = T) > > #CONTRIBUCIONES DE LAS COLUMNAS A LOS EJES > acpI$col.abs/100 > > Con esto obtengo una lista similar a: > > Comp1 Comp2 > X0 0.02 0.03 > X1 0.04 0.00 > X2...

...atrix2.RData") best<-function(liste=alt.transf,nombre=99){ x<-liste[[nombre]] library(ade4) p<-99 xx<-cov(x[,-(1:3)]) a<-eigen(xx,only.values=T) poids<-cumsum(a$values/sum(a$values)) nombre<-min(which(poids>=(p/100)),na.rm=T) acp<-dudi.pca(x[,-(1:3)],scale=T,scannf=F,nf=nombre) #if ve or vt print(acp) d<-discrimin(acp, as.factor(x[,1]),scan=F,nf=4) return(d) } b<-best(k,1) #look at the print out ... .... $rank: 166 eigen values: 86.02 17.09 12.76 8.727 8.338 ... vector length mode content 1 $cw 167 numeric column weights 2 $lw...

Hi R-community, I am doing a PCA and I need plots for different combinations of axes (e.g., PC1 vs PC3, and PC2 vs PC3) with the arrows indicating the loadings of each variables. What I need is exactly what I get using biplot (pca.object) but for other axes. I have plotted PC2 and 3 using the scores of the cases, but I don't get the arrows proportional to the loadings of each variables on

bonjour, Je voudrais faire une analyse des correspondances multiples avec R. avec les repr?sentation graphiques correspondantes avec R. je ne sais pas comment proc?der .. en vour remerciant par avance Faouzi

...rmación me arrojara la lista de cuáles son las variables que más influyen sobre el resultado. Revisando la información que arroja inertia.dudi, creo que con las contribuciones a los ejes podría conseguirlo. Los comandos que utilizo son los siguientes: acp <- dudi.pca(df = DATOS[,(2:1013)], scannf = FALSE, nf = 2) acpI <- inertia.dudi(acp, row.inertia = T, col.inertia = T) #CONTRIBUCIONES DE LAS COLUMNAS A LOS EJES acpI$col.abs/100 Con esto obtengo una lista similar a: Comp1 Comp2 X0 0.02 0.03 X1 0.04 0.00 X2 0.25 0.08 X3 0.12 0.07 X4 0.08 0.10 X5 0.09...

Hi all, thank you for your answers; i've tried both cca from vegan library, and dudi.coa from ade4 library; one last question: my deal is mainly with contingency tables, like the one i'm posting here acciaieria<-c(.41,.02,.44,.04,.09) laminatoio<-c(.34,.28,.26,.01,.11) fonderia<-c(.48,.05,.34,.08,.05) leghe<-c(.45,.19,.25,.03,.08)

Hi all: How can I calculate the cumulative variance (or variance for each component) in correspondence analysis? If were possible in ADE4 package Thank you -- Antonio Punzón Merino O__---- Instituto Español de Oceanografía c/ /'_ --- Centro Oceanográfico de Santander (*) \(*) -- Promontorio de San Martín S/N ~~~~~~~~~~ 39004-Santander; Spain PO BOX: 240 Tlf: +34 942 29 10 60 Fax: +34