similar to: Data reconstruction following PCA using Eigen function

Dear Dr.Goslee and anyone may intrested in matrix manipulate, I am using your ecodist to do mantel and partial mantel test, I have locality data and shape variation data, and the two distance matrixs are given as belowings. When I run the analysis, it is always report that the matrix is not square, but I didn't know what's wrong with my data. Would you please help me on this. I am quite

Starting with data from a microarray experiment and I would like to analyse the influence of two factors (age, treatment) on gene expression. Looking through the r-help archives and the web I tried the following: I put my data in a dataframe similar to this one: > example.df <- as.data.frame(matrix(data=runif(32,100,1000), nrow=4, ncol=4)) > example.df <-

Dear list I'd like to have your opinion about my case study. I'm analizing a dataset of 9 experiments and 15 variables with the aim to highlight the variables that can majorly explain the variance between the experiments. This is an example with only 3 rows and 5 variables var1 var2 var3 var4 var5 sample5 0,067 0,005 0,008 0,100 0,005 sample6 0,069 0,001

Dear All, I have to use loop over an array so I am using following procedure count<-1 repeat{ count<-count + 1 c(g[count],1:i[count]) ->qw if(count>5)break } as a result qw is [1] 0.9643836 1.0000000 2.0000000 3.0000000 4.0000000 5.0000000 [7] 6.0000000 7.0000000 8.0000000 9.0000000 10.0000000 11.0000000 [13] 12.0000000 13.0000000 14.0000000 15.0000000 16.0000000

is there a way to do element-by-element multiplication as in Gauss and MATLAB, as shown below? Thanks. --- a 1.0000000 2.0000000 3.0000000 x 1.0000000 2.0000000 3.0000000 2.0000000 4.0000000 6.0000000 3.0000000 6.0000000 9.0000000 a.*x 1.0000000 2.0000000 3.0000000 4.0000000

below is my data frame. I would like to compute summary statistics for mgl for each river mile (mean, median, mode). My apologies in advance- I would like to get something like the SAS print out of PROC Univariate. I have performed an ANOVA and a tukey LSD and I would just like the summary statistics. thanks stephen RM mgl 1 215 0.9285714 2 215 0.7352941 3 215 1.6455696 4 215

Hello, I am calculating this thing with vectors (b) and matrices (G,P): b'G/sqrt(b'Pb) where the denominator is a quadratic form and therefore always a scalar. In Scilab, it is quite simple: b'*G/sqrt(b'*P*b) However, in R, the denominator is an (1x1)matrix and R claims it is non conformable and I have to use drop() or as.numeric(). Like this: > b = 1:2 > G=diag(1,2) >

Hi, I want to simulate a data set with similar covariance structure as my observed data, and have calculated a covariance matrix (dimensions 8368*8368). So far I've tried two approaches to simulating data: rmvnorm from the mvtnorm package, and by using the Cholesky decomposition (http://www.cerebralmastication.com/2010/09/cholesk-post-on-correlated-random-normal-generation/). The problem is

Hi R, y1 <- zoo(matrix(1:10, ncol = 2), 1:5) colnames(y1)=c("a","b") y2 <- zoo(matrix(rnorm(10), ncol = 2), 6:10) colnames(y2)=c("b","a") > y1 a b 1 1 6 2 2 7 3 3 8 4 4 9 5 5 10 > y2 b a 6 0.9070204 0.3527630 7 1.2405943 0.8275001 8 -0.1690653 -0.1724976 9 -0.6905223 -1.1127670 10

Hello all! I have a problem with ggplot2 library. I want to do an heat map and the y variables are the year months. If I use the following code, he y values are in alphabetical order, but I want it in month order. The code is: library(reshape) library(ggplot2) library(scales) p <- ggplot(data.m, aes(variable, Month)) + geom_tile(aes(fill = value),

I'm replacing a SoundPoint IP 600 with a SoundPoint IP 650. I attempted to simply reuse the existing config files for the old phone on the new phone, but the new phone would lock up on the 4th digit when attempted to dial out certain numbers. So, I downloaded the newest firmware and config templates from Polycom, and attempted to migrate the settings. Seems I'm missing something from

Dear list I wish to extract from a population genotypized for 10 SNP a subsample of the same population of size n with similar allele frequencies. Essentially i have a matrix of 200 rows (df) like this Name,Condition,rs1385699_X,rs6625163_X,rs962458_X,Rs4658627_1, sample01,Case,1,1,1,-1 sample02,Control,1,1,1,1 sample06,Control,1,-1,1,0 sample10,Case,1,1,1,0 sample11,Control,1,1,1,1

Dear all, I am trying to use Rcpp to write some files in C++ for use in R. Below is an example for a cpp-file (crossp.cpp). Then I use >sourceCpp("crossp.cpp") in R and the corresponding function is availabe in R. Now I have to question related to this worklfow: 1) Is there a way to see the source file of the "final" cpp-file? (I mean is it possible to see how the

Buenas Tengo un Data table de la siguiente manera: datos<-data.table(grupo=rep(c("a","b"),5),x=c(1:10),y=rnorm(10,2,1)) Lo que quiero es añadir una fila por cada grupo y en esa nueva fila, al valor de la x ponerle el valor anterior de la y Lo que hago es añadir una nueva fila por grupo, con: datos[,.SD[1:(.N+1)],by=grupo] Y para añadir el valor anterior uso la función

Hi dears, I am from saudi arabia and using asterisk 1.6.2.13,Dahdi-2.3.0 and Digium, Inc. Wildcard AEX800 8-port analog card (PCI-Express) . I am facing problem with detecting caller id before first ring.I recorded the dahdi channel using dahdi_monitor command. Where I am able to see and hear caller-id dtmf tones. Pl tell me the procedure to upload recorded file if you needed. Something I want

Hi, dear R pros I try to understand eigen(). I have seen, that eigen() gives the eigenvectors normalized to unit length. What shall I do to get the eigenvectors not normalized to unit length? E.g. take the example: A [,1] [,2] V1 0.7714286 -0.2571429 V2 -0.4224490 0.1408163 Calculating eigen(A) "by hand" gives the eigenvectors (example from Backhaus,

Hello everybody, this is my first request about R so I am sorry if I send it to a bad mail or if I am not very clear. So my problem is about the use of rfImpute from randomForest package. I am interested in imputations of missing values and I read that randomForest can make it. So i write the following code : set.seed(100); library(mlbench) library(randomForest) data(BreastCancer)

Hello R people, i'm trying to implement the Partial Least Squares algorithm called SAMPLS from "J.Comp-Aided Molecular Design", 7 (1993), 587-619. It's faster than the classical PLS algorithm for fat matrix (m>>n). Here's the algorithm from the article of Bush B. L. and Nachbar R.B.: X is the matrix of explanatories proprieties (m*n) , y the matrix of responses, h

Hi there ! I've got 7 Samples that may contain 29 differents kinds of material.... every line below corresponds to a differente kind of material, example: Sample 1, 2,3,5 and 6 has material 1 .... So I want to know how can I do a Venn Diagram with the data below .... ps ( it was generated by a csv, where every line is sep with (";")) Can someone helps me ? thanks csv file :