similar to: Mahalanobis

If you look at the structure, you'll see: > x$V4 <- 0 > str(x) `data.frame': 4 obs. of 4 variables: $ V1: int 1 2 3 4 $ V2: int 5 6 7 8 $ V3: int 9 10 11 12 $ V4: num 0 Don't know if this is the intended result. In any case, you're probably better off using data.matrix, as > data.matrix(x) V1 V2 V3 V4 1 1 5 9 0 2 2 6 10 0 3 3 7 11 0 4 4 8 12

Dear all I have tried to estimate the confidence intervals for predicted values of a nonlinear model fitted with nls. The function predict gives the predicted values and the lower and upper limits of the prediction, when the class of the object is lm or glm. When the object is derived from nls, the function predict (or predict.nls) gives only the predicted values. The se.fit and interval aguments

I expected that something like > for(i in names(my.data.frame)){j <- as.name(i); print(my.data.frame$j)} should work in R (and S). There's always the possibility of using > for(i in names(my.data.frame)){print(my.data.frame[,i])} but can someone someone tell me why doesn't the 1st option work also? Thanks Alberto -- Alberto G. Murta

Hi I have written a small function to calculate distances between pairs of landmarks ('my.dist' bellow). I gave it to a colleague that works with MSWindows and the function doesn't give the right answer: R 1.4.1 for Linux: > my.dist() [1] 22 561 R 1.4.1 for Windows: > my.dist() [1] 22 560 Warning message: Replacement length not a multiple of the elements to replace in

Dear all I was writing some code that needed functions from packages 'MASS' and 'CircStats', and I received a warning saying that the function 'eqscplot' in one of the packages was masked by another 'eqscplot' from the other package (in fact 'eqscplot' from 'CircStats' seems a short version of 'eqscplot' from 'MASS'). This masking of

Hello R helpers, I'm trying to use Mahalanobis distance to calculate distance of two time series, to make some comparations with euclidean distance, DTW, etc, but I'm having some dificults. I have, for example, two objects: s.1 <- c( 5.6324702, 1.3994353, -3.2572327, -3.8311846, -1.2248719, 0.9894694, -2.2835332, -5.1969285, -5.2823988, -3.1499400, -1.7307950, 2.8221209,

Dear R-experts, Searching the help archives I found a recommendation to do multivariate outlier identification by mahalanobis distances based on a robustly estimated covariance matrix and compare the resulting distances to a chi^2-distribution with p (number of your variables) degrees of freedom. I understand that compared to euclidean distances this has the advantage of being scale-invariant.

http://www.nabble.com/file/p24569511/mahalanobis.txt mahalanobis.txt http://www.nabble.com/file/p24569511/concentrations.txt concentrations.txt Dear Forum members, I have a problem calculating mahalanobis distances. My data file mahalanobis.txt and categories file concentrations.txt are attached. I do the following steps: x <- as.matrix(read.table("mahalanobis.txt", header=TRUE))

I am a new R user. i have a question about Mahalanobis distance.actually i have 300 rows and 7 columns. columns are different measurements, 300 rows are genes. since genes can classify into 4 categories. i used dist() with euclidean distance and cmdscale to do MDS plot. but find out Mahalanobis distance may be better. how do i use Mahalanobis() to generate similar dist object which i can use

Hello, I am a new R user and trying to learn how to implement the mahalanobis function to measure the distance between to 2 population centroids. I have used STATISTICA to calculate these differences, but was hoping to learn to do the analysis in R. I have implemented the code as below, but my results are very different from that of STATISTICA, and I believe I may not have interpreted the help

Hello all, I am a 2 month newbie to R and am stumped. I have a data set that I've run multivariate stats on using the manova function (I included the data set). Now it comes time for a table of effect sizes with significance. The univariate tests are easy. Where I run into trouble filling in the table of effect sizes is the Mahalanobis D as an effect size. I've included the table so

I want to calculate the probability that a group will include a particular point using the squared Mahalanobis distance to the centroid. I understand that the squared Mahalanobis distance is distributed as chi-squared but that for a small number of random samples from a multivariate normal population the Hotellings T2 (T squared) distribution should be used. I cannot find a function for

Hi, help on 'mahalanobis' (in the stats package in Rv2.2.0) now says: "Description: Returns the Mahalanobis distance of all rows in 'x' and the vector mu='center' with respect to Sigma='cov'. This is (for vector 'x') defined as D^2 = (x - mu)' Sigma^{-1} (x - mu)" It does return D^2 as written. However,

On Tue, 03 Oct 2000 10:55:28 +0000, Alberto Murta <amurta at ipimar.pt> wrote: > And objectively, it's a fact that "<-" >makes the code easier to read than "_". I don't follow this argument. Underscore isn't used anywhere else in the language, so when you see one, you know it's an assignment. On the other hand, both "<" and

Hello all, I am a 2 month newbie to R and am stumped. I have a data set that I've run multivariate stats on using the manova function (I included the data set). Now it comes time for a table of effect sizes with significance. The univariate tests are easy. Where I run into trouble filling in the table of effect sizes is the Mahalanobis D as an effect size. I've included the table so

Dear R ExpeRts, I'm having memory difficulties using mahalanobis distance to trying to cluster in R. I was wondering if anyone has done it with a matrix of 6525x17 (or something similar to that size). I have a matrix of 6525 genes and 17 samples. I have my R memory increased to the max and am still getting "cannot allocate vector of size" errors. My matrix "x" is

Dear R community Have just recently got back into R after a long break and have been amazed at how much it has grown, and how active the list is! Thank you so much to all those who contribute to this amazing project. My question: I am trying to calculate Mahalanobis distances for a matrix called "fgmatrix" >dim(fgmatrix) [1] 76 15 >fg.cov <- cov.wt(fgmatrix)

> Date: Tue, 03 Oct 2000 14:45:32 +0000 > From: Alberto Murta <amurta at ipimar.pt> > > Duncan Murdoch wrote: > > > I don't follow this argument. Underscore isn't used anywhere else in > > the language, so when you see one, you know it's an assignment. On > > the other hand, both "<" and "-" have multiple other uses.

The help on mahalanobis {stats} does not include any reference. I'm interested in understand why Mahalanobis is defined in its current way and how to use it. Could somebody point me a good book on this? I have looked through a few books, but they all give very light explanation on it.

Dear R list, I'm trying to calculate Mahalanobis distances for 'Species' of 'iris' data as obtained below: Squared Distance to Species From Species: Setosa Versicolor Virginica Setosa 0 89.86419 179.38471 Versicolor 89.86419 0 17.20107 Virginica 179.38471 17.20107 0 This distances above were obtained with proc