similar to: gdist and gower distance

Dear R community, I am analyzing plant communities with the function mvpart, using a dissimilarit matrix as input. The matrix is calculated with the funtion gdist. fit <- mvpart(gdist (ba12[,18:29], meth="maximum", full=TRUE, sq=F) ~ beers + slope_dem + elev_dem+ plc_dem + pr_curv+ +curv+max_depth+doc_rocks+ abandon+land_use+ca_old, data=ba12, xv="p") This

Hello I have 2 rows in a matrix and I want to calculate the Gower Distance between the 2 , how can I do it? I searched and found nothing that can help me, and my program doesn't know the gdist function and I couldn't find it on the R help site. Can anyone help me plz Thank u all [[alternative HTML version deleted]]

Dear all, I'm getting an error in one of the stock examples in the 'mvpart' package. I tried: require(mvpart) data(spider) fit3 <- rpart(gdist(spider[,1:12],meth="bray",full=TRUE,sq=TRUE)~water+twigs+reft+herbs+moss+sand,spider,method="dist") #directly from ?rpart summary(fit3) ...which returned the following: Error in apply(formatg(yval, digits - 3), 1,

Hi, I am very new to R and I've been trying to work through the R book to gain a better idea of the code (which is also completely new to me). Initially I imputed my data from a text file and that seemed to work ok, but I'm trying to examine linear relationships between gdist and gair, gdist and gsub, m6dist and m6air, etc. This didn't work and I think it might have something to do

I'm interested in clustering my data using the Gower Similarity Coefficient, and I was wondering if R is capable of using that metric Timothy Rye [[alternative HTML version deleted]]

Hello!!! I have a folder (C:/R/) with matrix files, named by number, i.e. 0.mat, 1.mat,...,1250.mat. In this case, they are 5x5 simetric matrices. I would like to compute a property for each matrix and put calculated values into a data frame for posterior ploting and printing. Below there is an example for 7 matrices (0.mat..6.mat) #define data frame L <- data.frame(frame=numeric(7),

In the manual page for prcomp(), it says that sdev is "the standard deviations of the principal components (i.e., the square roots of the eigenvalues of the covariance/correlation matrix, though the calculation is actually done with the singular values of the data matrix)." ?However, this is not what I'm finding. ?The values appear to be the standard deviations of a reprojection of

Hi, This is a beginner R question. I have a 4x4 matrix named 'lookup' with the following values: 1 2 3 4 1 0.000000 2.828427 5.656854 8.485281 2 2.828427 0.000000 2.828427 5.656854 3 5.656854 2.828427 0.000000 2.828427 4 8.485281 5.656854 2.828427 0.000000 I then create a new empty matrix named 'dd' with specfic row and col names :

Hi all, I would like to know a way of calculating the distance between 2 points when I already have the longitude and latitude of the points. For example : Point 1 : 52? 9'54.00"N 4?25'8.40"E Point 2 : 52?27'46.80"N 4?33'18.00"E Distance between point 1 and point in km .... Is there any functions already available for this ? Any help will be much

I could not figure out what was the default when I ran hclust() without specifying the method. For example: I just have a code like: hclust(dist(data)) Any input would be appreciated:) [[alternative HTML version deleted]]

Hello all, I'm having trouble creating an adjacency matrix. Basically, I need to turn the following distance matrix into an adjacency matrix based on whether values are >1.5 or not. If they are >1.5, then the returned value should be 0. If they are =<1.5, then the returned value should be 1. DistanceMatrix: A B C D E [1,]

I've never noticed this before, though it's probably not new. In 1.2.3 for Windows, if I print a short vector the formatting is different than if I print a long one, whether or not they fit on one line. The short/long split appears to be between 9 and 10 elements: > 1:9 [1] 1 2 3 4 5 6 7 8 9 > 1:10 [1] 1 2 3 4 5 6 7 8 9 10 > sqrt(1:9) [1] 1.000000 1.414214

Hello all, I am brand new to R and doing an exercise for a class. I need to find the nearest neighbour for points in the following matrix: > DistanceMatrix x1 x2 x3 x4 x5 [1,] 0.000000 2.828427 1.581139 2.236068 2.000000 [2,] 2.828427 0.000000 1.581139 4.123106 2.000000 [3,] 1.581139 1.581139 0.000000 2.549510 2.121320 [4,] 2.236068 4.123106 2.549510

This message is in MIME format. The first part should be readable text, while the remaining parts are likely unreadable without MIME-aware tools. Send mail to mime@docserver.cac.washington.edu for more info. ---559023410-1804928587-922106403=:691 Content-Type: TEXT/PLAIN; charset=US-ASCII A couple of weeks ago I asked if anyone had generalised outer to include bound extents -- effectively

Hi all, I am running an -MNP- multinomial probit model package using R. It gives me the following objection instead of giving me the results: Erreur : impossible d'allouer un vecteur de taille 137.9 Mo (in english: cannot allocate a 137.9 Mb vector memory).  I have already increased the memory size upto 2047Mb. This problem has been discussed in 2008 (archives) but no profitable answers were

Hi, I misunderstand the definition of Canberra distance in R. On Internet and in function description pages of dist() from stats and Dist() from amap, Canberra distance between vectors x and y, d(x,y), is : d(x,y) = sum(abs(x-y)/(x+y)) But in use, through simple examples, we find that the formula is : d(x,y) = (NZ + 1)/NZ * sum(abs(x-y)/(x+y)) with NZ = nb of pairs of coordinates that are

Full_Name: David Pleydell Version: 2.2.1 OS: Debian Etch Submission from: (NULL) (193.55.70.206) There appears to be a conflict between the chol functions from the Matrix and the SparseM packages. chol() can only be applied to a matrix of class dspMatrix if SparseM is not in the path. with gratitude David > library(Matrix) > sm <- as(as(Matrix(diag(5) + 1), "dsyMatrix"),

Hi the list, I need to compute Gower distance between a specific individual and all the other individual. The function DAISY from package cluster compute all the pairwise dissimilarities of a population. If the population is N individuals, that is arround N^2 distances to compute. I need to compute the distance between a specific individual and all the other individual, that is only N

Hello, I am running DAISY in R and using the GOWER metric since I am working with mixed variables. I am wondering if there is a way to weight the different variables. I see that there is a weight value for Gower but do not know if this is how to weight the diffrent variables with different weighting values. Please advise if there is a way to weight the different variables. Thank you. -- View

I am using DIANA/DAISY/GOWER. Some of my categorical data include NULLS. When assessing disimilarity, these NULLS are considered similar. I do not want these NULLS to contribute towards similarity. Instead is there a way for these NULLS to each be considered different so as to contribute to disimiliarity and not simillarity? Also, I do not want to change these NULLS in the data as I need them for