similar to: nnclust: nnfind() distance metric?

>?step .... 'step' uses 'add1' and 'drop1' repeatedly; it will work for any method for which they work, and that is determined by having a valid method for 'extractAIC'. When the additive constant can be chosen so that AIC is equal to Mallows' Cp, this is done and the tables are labelled appropriately. so my question is :what constant

Hi I am looking for an implementation (or alternative to) Mallow's distance or the Earth Mover's distance to compare distributions or unnormalized distributions (signatures). Is there an implementation in R or can somebody recommend an alternative? Thanks Rainer -- Rainer M. Krug, PhD (Conservation Ecology, SUN), MSc (Conservation Biology, UCT), Dipl. Phys. (Germany) Centre of

Hello: What I want to do is quite simple, but I can't find a way. I have a data frame with several points (x and y coords). I want to add another column with cluster membership. For example aggregate all the points that stand within a distance of 40 from each other. I've tried using "nncluster" from the package nnclust, but the results are not correct, for some

Dear all, Does R or S-plus or any of their packages provide any command to form any of the following procedures to find Best Regression Equation - 1. 'All Possible Regressions Procedures' (is there any automated command to perform 2^p regressions and ordering according to criteria R2(adj), mallows Cp, s2- by not setting all the regression models manually), 2. 'Backward

Sorry, forgot to send this to the list originally. -----Original Message----- From: Mike Waters [mailto:dr.mike at ntlworld.com] Sent: 06 May 2005 18:40 To: 'Campbell' Subject: RE: [R] distance between distributions -----Original Message----- From: r-help-bounces at stat.math.ethz.ch [mailto:r-help-bounces at stat.math.ethz.ch] On Behalf Of Campbell Sent: 06 May 2005 11:19 To:

On Thu, 11 Feb 2010, Christian Hennig wrote: >It is well know that hierarchical methods are problematic with too large >dissimilarity matrices; even if you resolve the memory problem, the number of >operations required is enormous. There is at least one exception to this. Single-linkage hierarchical clustering with a convex distance such as Euclidean distance is feasible for quite

Hi, This is more of a general stat question. I am looking for a easily computable measure of a distance between two empirical distributions. Say I have two samples x and y drawn from X and Y. I want to compute a statistics rho(x,y) which is zero if X = Y and grows as X and Y become less similar. Kullback-Leibler distance is the most "official" choice, however it needs estimation of

Hello dear R-help members, I recently became interested in using biglm with leaps, and found myself somewhat confused as to how to use the two together, in different settings. I couldn't find any example codes for the leaps() package (except for in the help file, and the examples there are not as rich as they could be). That is why I turn to you in case you could share some good tips and

Hi, I'm analyzing a large number of large simulation datasets, and I've isolated one of the bottlenecks. Any help in speeding it up would be appreciated. `dat` is a dataframe of samples from a regular grid. The first two columns are the spatial coordinates of the samples, the remaining 20 columns are the abundances of species in each cell. I need to calculate the species richness in

Hi, There are two packages providing knn classification: class and knnTree. However, it seems both uses Eucleadian distances only. How can I uses a custom distance function with either package? Thanks, Xiao-Jun

So I recognize that: 1. many people hate forward stepwise regression (i've read the archives)--but I need it 2. step() or stepAIC are two ways to get a stepwise regression in R But here's the thing: I can't seem to figure out how to specify that I want the criteria to be Mallow's Cp (and then to subsequently tell me what the Cp stat is). I know it has something to do with

I need to use the Bhattacharyya distance metric to determine population separation. Has anyone written a Bhattacharyya distance metric function in R? -- View this message in context: http://old.nabble.com/Bhattacharyya-distance-metric-tp26221259p26221259.html Sent from the R help mailing list archive at Nabble.com.

I am hoping someone can help translate some WinBUGS code into R code. I would like to use R to create the C[] matrix required for a car.proper model in WinBUGS, but I am having a difficult time negotiating the coding. The C matrix provides normalized weights for each pair of spatial areas. So the WinBUGS example is as follows: # of the weight matrix with elements Cij. The first J1 elements

Hello, I'm new to R and to Spatial Analysis and got a problem trying to create a Spatial Weights Matrix. *I us the following code to create the Neighbourslist:* >library(maptools) >library(spdep) >library(rgdal) >location_County<- readShapePoly("....") >proj4string(location_County)<- CRS("+proj=longlat ellps=WGS84") >location_nbq<-

I would like to figure out the equations for calculating "AIC" in both "step() function" and "AIC () function". They are different. Then I just type "step" in the R console, and found the "AIC" used in "step() function" is "extractAIC". I went to the R help, and found: "The criterion used is AIC = - 2*log L + k *

Dear R users, I used nndist() to gain the distance of 2 nearest neighbours of the points in my dataset. Is there a way of getting the ID numbers of these nearest neighbours (along with their distances). The command I used: nn2 <- nndist(X2, k=1:2). This is the output of the nearest neighbour distances I got (the IDs of the given points are there but their IDs aren't). Any help or

Hello everybody, I would like to use the SpDep-package (especially the Local Moran index analysis and the Getis-Ord statistics) in R for analysing my data. However, I don't have x-y coordinates, but my data is in a distance matrix format. Is it possible to use the SpDep package with predefined distances as well instead of letting the program determining the distance itself by the function

hello, I want to do a test for spatial correlation. I tried it with geary.test() but I don't understand the required input. x= a numeric vector the same length as the neighbours list in listw (my sampled data, I assume) listw= a listw object created for example by nb2listw (well when I check nb2listw() I get to "neighbours - an object of class nb" - but I couldn't figure

Hi All, I am still learning R, but making, IMO, great strides. I learned about Kohonen/Self-Organizing Maps in class and I would like to try to replicate some of the things we have seen in class. Below is my code. I am trying to create a u-matrix. In the documentation on page 9 it appears the type of plot, dist.neighbours should do the trick, however, I am getting an error: (Error in

Hi I want to create a nice picture about my result of k -the nearest neighbours algorithm. Here is my easy code: ################################# library(klaR) library(ipred) library(mlbench) data(PimaIndiansDiabetes2) dane=na.omit(PimaIndiansDiabetes2)[,c(2,5,9)] dane[,2]=log(dane[,2]) dane[,1:2]=scale(dane[,1:2]) zbior.uczacy=sample(1:nrow(dane),nrow(dane)/2,F)