similar to: RE: [R] Mapping actual to expected columns for princomp object

I am working with data sets in which the number and order of columns may vary, but each column is uniquely identified by its name. E.g., one data set might have columns MW logP Num_Rings Num_H_Donors while another has columns Num_Rings Num_Atoms Num_H_Donors logP MW I would like to be able to perform a principal component analysis (PCA) on one data set and save the PCA object to

Hi All, I have been trying to get to plot my PCA legend outside of the PCA plot, but success still alludes me. Can you guys please advise how I can achieve this. I used locater() to obtain coordinates for below the Comp.1 axis. Using these coordinates the legend disappears. Below is the code for the PCA and legend. Thanks in advance for the help. Regards Tinus r.cols <-

Hallo everybody! I am trying to perform a TiTAN (Baker & King 2010) analysis with R 2.14.1. I have come that far: h89Abund <- read.csv("Fish89Abund.csv") > names (Fish89Abund) [1] "StationCode" "Abramisbrama" "Alburnoidesbipunctatus" "Alburnusalburnus" [5] "Ameiurusmelas" >

Hi, I was trying as well as looking for an answer without success (a bit strange since it should be an easy problem) and therefore I will appreciate you help: My simple script is: # Loadings data of 5 columns and 100 rows of data data1<-read.csv("C:/?/MyPCA.csv") pairs(data1[,1:4]) pca1 <- princomp(data1[,1:4], score=TRUE, cor=TRUE) biplot(pca1) The biplot present the data

Dear Forum, I have a class variable 1 (populations A-E), and two other class variables, variable 2 and variable 3. What I want is to see if the combination of var 2 and var 3, will give me a pattern that allows to distinguish populations. I found several packages like ade4, with pcaiv function and factoMineR. but there are not working. Using the ade4 package, when I try to build the pca: pca1

Hi!! I'm having trouble selecting 10 out of 41 attributes of the KDD data set. In order to identify the components with the higher variance I'm using princomp. the result i get for summary(pca1) is: Comp.1 Comp.2 Comp.3 Comp.4 Comp.5 Comp.6 Comp.7 Comp.8 Comp.9

I am examining the following nlme model. asymporig<-function(x,th1,th2)th1*(1-exp(-exp(th2)*x)) mod1<-nlme(fa20~(ah*habdiv+ad*log(d)+ads*ds+ads2*ds2+at*trout)+asymporig(da.p,th1,th2), fixed=ah+ad+ads+ads2+at+th1+th2~1, random=th1+th2~1, start=c(ah=.9124,ad=.9252,ads=.5,ads2=-.1,at=-1,th1=2.842,th2=-6.917), data=pca1.grouped) However, the two random effects (th1 and th2)

Is there an option to draw concentration ellipses in biplots ? It seems really nice to summarize large number of points of each group. Cheers../ Murli

Hola compañeros de la lista, qué tal. Estoy haciendo un análisis de componentes principales utilizando las funciones "dudi.pca" (paquete "ade4") y "PCA" (paquete "FactoMineR"). 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

I am working on a nlme model that has multiple fixed effects (linear and nonlinear) with a nonlinear (asymptotic) random effect. asymporig<-function(x,th1,th2)th1*(1-exp(-exp(th2)*x)) asymporigb<-function(x,th1b,th2b)th1b*(1-exp(-exp(th2b)*x)) mod.vol.nlme<-nlme(fa20~(ah*habdiv+ads*ds+ads2*ds2+at*trout)+asymporig(da.p,th1,th2)+ asymporigb(vol,th1b,th2b),

hello all R experts, how do I calculate the reliability between the two groups using the ICCs? I'll appreciate your reply, Thanks Sincerely, Supreet kaur, Biomedical research engineer, Nationwide Childrens Hospital, Columbus, OH (614)355-3509 [[alternative HTML version deleted]]

Instalo ade4 correctamente y no me abren los datos como por ejemplo data(bsetal97) ¿Qué piensan de eso? De: r-help-es-bounces en r-project.org [mailto:r-help-es-bounces en r-project.org] En nombre de Francesc Carmona Enviado el: Tuesday, October 01, 2013 7:30 AM Para: r-help-es en r-project.org Asunto: Re: [R-es] Análisis de componentes principales con ade4 y FactoMineR Por definición

Por definición la primera componente principal es una combinación lineal que maximiza la varianza de modo que si la componente 1 es el vector de coeficientes a, entonces, el vector -a también puede ser dicha componente. Las otras componentes, por ejemplo la segunda, es incorrelacionada con la primera y también maximiza la varianza, luego el signo no importa. Así pues, el signo de cada

Hi all I have a samba pdc(master LDAP Server) with 1 BDC(slave ldap server), the version of Samba at PDC and BDC is samba 3.0.21c. At BDC , there are some shares declared. The shares are used to store Fox pro files. The client uses foxpro and opens DBF file in the share declared. and also Roaming profiles is also used at BDC. The problem is samba hangs frequently. Once rebooted works for some

Efectivamente. Puedes cambiar el signo de todos los valores de la segunda componente, por ejemplo al hacer un gráfico de dispersión. No creo que se pueda hacer directamente en la función. Saludos Francesc El 01/10/13 17:53, Argel Gastélum Arellánez ha escrit: > Hola Francesc, muchas gracias por tu respuesta. > > Entonces, si quisiera que las gráficas de los resultados de

Hi Group, Here is some data. p <- runif(1000) # sample data groups <- rep(c(1,2),each=500) #conditioning variable mydata <- cbind(p,groups) n <- length(p) u <- (1:n)/(n + 1) # uniform distribution reference for qqplot logp <- -log(p,base=10) logu <- -log(u,base=10) qqplot(logp,logu) How can I make the above qqplot in lattice and/or ggplot2. The sample is uniform, and I take

Hi there, I just found that if an user is assigned in the "admin users", and if the user grab a file from window to samba share, the file will be owned by root from unix view. I am believing this is a bug. The samba version I am using is 2.2.4. Weixing Hao (631) 858-6341 Forest Labs -------------- next part -------------- HTML attachment scrubbed and removed

Given a vector : pvec=(p1,p2,.... p J) with sum(pvec)=1, all the elements are non-negative, that is, they are probabilities a matrix A ( N* J ), with the elements alpha(ij) are 0 or 1 I want to MAXIMIZE THE RESULT RESULT= product( i=1, to N [ sum ( alpha(ij)* pj , j =1,to J ) ] ) thus, I need to get pvec. how should I do ? for example

Fellow R users, I'm using the BCE {BCE} function to run a Bayesian sediment mixing model. The aim is to find the optimum % contribution from each of the 4 source areas that can yield the target geochemistry. I have geochemistry for 4 source areas called Rat: Rat<-read.table(text="CaO MgO Na2O Al2O3 Topsoils 2.511250 0.7445500 0.7085500 14.10375 ChannelBanks

This is significant because it's a plugin which was from the last stable release containing undefined symbols (in the internal plugins). $ ldd -r tests/old-plugins/x86_64/Linux/v1.18.2/nbdkit-file-plugin.so linux-vdso.so.1 (0x00007ffe86cdd000) libgcc_s.so.1 => /lib64/libgcc_s.so.1 (0x00007f551b3e5000) libc.so.6 => /lib64/libc.so.6 (0x00007f551b21b000) /lib64/ld-linux-x86-64.so.2