search for: eigenanalysi

...this is a stats question. when undertaking factor analysis should the variables included always be continiuos random variables? could one include categorical data? e.g some survey type data my gut feeling is that one should not include categorical type data since factor analysis is based on the eigenanalysis of the correlation matrix of a group of variables. The introduction of categorical data into a data set might "mess up" the corelation matrix.

Dear all, I have just uploaded to CRAN the version 1.4 of the package 'adehabitat'. Significant changes are listed below: - The eigenanalysis of selection ratios (Calenge and Dufour, 2006, Ecology) can now be performed using the function eisera(). It can be used for the analysis of habitat selection when habitat can be considered to consist of several habitat types (e.g. vegetation types). - A new class, the class "ltraj&q...

...aak (1995) Section 5.9 in Jongman, Ter Braak, and van Tongeren "Data Analysis in Community and Landscape Ecology". Actually, there are two versions: one which follows Ter Braak's iterative method (slower, but feasible for large problems), the other which directly uses an eigenanalysis (fast, but uses too much memory for large datasets). Although the code does spit out those funny-looking tri-plots, etc., I don't really consider it "finished", because i found the references that i had access to very ambiguous in their description of the method, and the desired out...

Hello, We are trying to find a function to compute "stress" in our multidimensional scaling analysis of a dissimilarity matrix. We've used "dist()" to create the matrix and "cmdscale()" for the scaling. In order to determine the number of dimensions we would like to plot stress vs. dimensions. However, we cannot find a pre-made command. It seems that other

Dear all, I have just uploaded to CRAN the version 1.4 of the package 'adehabitat'. Significant changes are listed below: - The eigenanalysis of selection ratios (Calenge and Dufour, 2006, Ecology) can now be performed using the function eisera(). It can be used for the analysis of habitat selection when habitat can be considered to consist of several habitat types (e.g. vegetation types). - A new class, the class "ltraj&q...

Dear all, I've a correlation matrix with rows and columns headings. I've two questions: 1) How can i import it in R, setting first row as row heading and first column as column heading? 2) Which is the best principal component anlysis package in R? Thanks in advance -- View this message in context: http://r.789695.n4.nabble.com/Help-with-PCA-tp4239756p4239756.html Sent from the R help

Some webpage has described prcomp and princomp, but I am still not quite sure what the major difference between them is. Can they be used interchangeably? In help, it says 'princomp' only handles so-called R-mode PCA, that is feature extraction of variables. If a data matrix is supplied (possibly via a formula) it is required that there are at least as many units as

...Some of these are already implemented, but clearly not all of them. > Package CCA has package fda as dependency. > And package fda defines a function geigen. > The first 14 lines of this function are > > geigen<- function(Amat, Bmat, Cmat) > { > # solve the generalized eigenanalysis problem > # > # max {tr L'AM / sqrt[tr L'BL tr M'CM] w.r.t. L and M > # > # Arguments: > # AMAT ... p by q matrix > # BMAT ... order p symmetric positive definite matrix > # CMAT ... order q symmetric positive definite matrix > #...

I know this question is very simple, but I am not figure it out I have the data frame:   test<- data.frame(year=c(2000,2000,2001,2001),x=c(54,41,90,15), y=c(29,2,92,22), z=c(26,68,46,51)) test   year    x   y   z 1 2000 54 29 26 2 2000 41  2  68 3 2001 90 92 46 4 2001 15 22 51   I want to sum the vectors x, y and z within each year (2000

estimados, ajusté una superficie de respuesta con el paquete "rsm" de R y hago un grafico 2D de la superficie de respuesta con contour(), pero como el argumento de esta función es la superficie de respuesta ajustada y ésta se ha ajustado codificando las variables, de acuerdo a la recomendación de la documentación del paquete rsm, obtengo un gráfico con los ejes en unidades codificadas