Re: [R] Distance matrix for Spatial Filtering {spdep}
Erica Cseko Nolasco ecnolasco at gmail.com writes: Hi all, I´m working on a species distribution modeling, and I want to build eigenvectors to represent my spatial varuable. I´m trying to use SpatialFiltering(spdep) for it, but I´m having problems to create the nb object. My weights would be a truncated pairwise distance matrix that I was pretty able to build. However, I´m going out resources to create a nb object. Or it doesn´t match the matrix or the R-Studio crashes. Here is the code I´m trying: You have not provided a reproducible example, it usually helps. Also always run code that fails in R-Studio outside it, as this frees memory and aids debugging (nothing between you and R). In addition, we know nothing of your platform, I guess Windows (G: isn't common elsewhere). Your posting is HTML which is discouraged. matriz3=earth.dist(coor1, dist=T) This function takes a matrix of geographical coordinates, and returns a triangular matrix of distances (n*(n-1)), hence the length: length(matriz3) [1] 12110581 ###truncating the distance matrix matriz3[matriz3=230]=230 ###creating the nb object to link to the distance matrix library(spdep) coord=read.table(coordinates16.txt,sep= , header=T) coo=cbind(coord[,1],coord[,2]) length(coo[,1]) [1] 4922 nb=dnearneigh(coo,0, 1, longlat=T) ###large nb (4922 elements,92.9Mb) nb2listw(nb,glist=matriz3,style=W) *Error in nb2listw(nb, glist = matriz3, style = W) : glist wrong length* The documentation of nb2listw says that the glist argument is a list, not a triangular matrix. In addition, it is highly unlikely that you expect the spatial autocorrelation to increase in distance. The examples for the nb2listw function show how to construct truncated inverse distance weights using km distances, here with a cutoff at 230km and using geographical coordinates: nb - dnearneigh(coo, 0, 230, longlat=TRUE) dists - nbdists(nb, coo, longlat=TRUE) glist - lapply(dists, function(x) 1/x) lw - nb2listw(nb, glist, style=W) The use of functions to create nb objects is described in vignette(nb) in the spdep package. ... *R session aborted. R encoutered a fatal error. The session was terminated* Such things have happened before with R-Studio as a front end when Windows platforms have run out of memory, but do not repeat outside R-Studio (reported but no action taken that I know of). nb=knearneigh(coo,500,longlat=T) ###tentativa de criar nb *Error in knearneigh(coo, 500, longlat = T) : too many ties in knearneigh* Almost certainly your choice of k=500 is erroneous, and also suggests that you are flailing around without a clear grasp of what you should be doing. 1) until the problem is resolved, drop R-Studio; once resolved outside R-Studio, you may go back to using it, but beware of memory problems. 2) construct the list of weights object as shown (maybe modify the threshold if too many observations have no neighbour) 3) think carefully about the use of SpatialFiltering - is your response continuous? You have about 5000 observations, so you will be operation on 5000x5000 matrices in order to construct the Moran eigenvectors, and will be doing a brute force search for combinations of these eigenvectors to add to your model. Are you sure that the model you are starting from is well-specified (included variables and their functional forms)? If not, you risk including many eigenvectors that simply mop up other misspecifications. This search will be very time-consuming. Consider using the R-sig-geo list, which may be more appropriate for this kind of question. Roger ... Any ideas would help a lot! Thanks in advance *Erica Csekö Nolasco* __ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.
Re: [R] distance matrix from metaMDS
Yes I looked at this and I tried metaMDSdist but got an error and for some reason I didn't try metaMDSredist which seems to be the right thing. So the main thing I was confused about was what to call dist() on -i.e., getting the correct ordinal distance, and then if I assume that the NMDS scores are the coordinates, which I believe they are, then how do I call dist() on one column? But, I just found the answer in a translation from matlab to R - you have to use drop=FALSE (and hopefully I am calling dist() on the right thing) euc.dist.axis1=dist(NMDS2[,1, drop=FALSE], method=euclidean) Maybe this is obvious to other folks but just in case there is anyone like me out there I figured I'd write back. Thanks for the info I have never written to this list before because I always found what I needed online. I appreciate your help and patience. Cara On Thu, Aug 28, 2014 at 10:19 PM, David L Carlson dcarl...@tamu.edu wrote: Don't the functions metaMDSdist() and metaMDSredist() that are documented on the metaMDS manual page give you the distance matrix? If you want to compute the distances based on a single axis, you could use vegdist(). David C -Original Message- From: r-help-boun...@r-project.org [mailto:r-help-boun...@r-project.org] On Behalf Of Cara Fiore Sent: Thursday, August 28, 2014 7:02 PM To: r-help@r-project.org Subject: [R] distance matrix from metaMDS Dear R users, I would like to access the distance matrix generated by metaMDS as well as use the dist function to calculate the euclidean distance for each axis in the NMDS. I am having trouble finding a way to access these variables and any help is greatly appreciated. For the distance matrix I know I could just calculate the bray-curtis distance but it would be nice to know how to get it from the NMDS function. For the euclidean distance, the only thing I can find within metaMDS is the score function but there must be some way for me to call on/access the ordination distance for one axis right? The reason for this is I would like to do something like the stressplot function but for each axis. Thank you, Cara [[alternative HTML version deleted]] __ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code. [[alternative HTML version deleted]] __ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.
Re: [R] distance matrix from metaMDS
Don't the functions metaMDSdist() and metaMDSredist() that are documented on the metaMDS manual page give you the distance matrix? If you want to compute the distances based on a single axis, you could use vegdist(). David C -Original Message- From: r-help-boun...@r-project.org [mailto:r-help-boun...@r-project.org] On Behalf Of Cara Fiore Sent: Thursday, August 28, 2014 7:02 PM To: r-help@r-project.org Subject: [R] distance matrix from metaMDS Dear R users, I would like to access the distance matrix generated by metaMDS as well as use the dist function to calculate the euclidean distance for each axis in the NMDS. I am having trouble finding a way to access these variables and any help is greatly appreciated. For the distance matrix I know I could just calculate the bray-curtis distance but it would be nice to know how to get it from the NMDS function. For the euclidean distance, the only thing I can find within metaMDS is the score function but there must be some way for me to call on/access the ordination distance for one axis right? The reason for this is I would like to do something like the stressplot function but for each axis. Thank you, Cara [[alternative HTML version deleted]] __ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code. __ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.
Re: [R] distance matrix and hclustering
Look at the examples for the functions dist() and hclust(), ?dist ?hclust Jean eliza botto eliza_bo...@hotmail.com wrote on 07/30/2012 01:43:55 AM: Dear R Users,i am very new to R. I want your help on an issue regarding distance matrix and cluster analysis i had discharge data of 4 rivers(a,b,c,d) in 4 vectors each having 364 values dput(qmu)structure(list(a = c(0.26, 0.25, 0.25, 0.25, 0.24, 0.23, 0.22, 0.21, 0.21, 0.21, 0.2, 0.19, 0.19, 0.19, 0.19, 0.18, 0.18, 0. 18, 0.17, 0.17, 0.17, 0.17, 0.17, 0.17, 0.17, 0.17, 0.17, 0.17, 0. 17, 0.17, 0.17, 0.17, 0.17, 0.17, 0.18, 0.19, 0.19, 0.19, 0.2, 0.21, 0.21, 0.21, 0.21, 0.21, 0.21, 0.19, 0.19, 0.18, 0.17, 0.17, 0.15, 0. 18, 0.2, 0.21, 0.2, 0.19, 0.19, 0.19, 0.2, 0.24, 0.3, 0.3, 0.3, 0. 32, 0.34, 0.42, 0.46, 0.48, 0.67, 0.82, 0.79, 0.73, 0.69, 0.67, 0. 67, 0.66, 0.64, 0.61, 0.58, 0.56, 0.55, 0.55, 0.55, 0.52, 0.49, 0. 48, 0.51, 0.53, 0.52, 0.49, 0.48, 0.48, 0.46, 0.46, 0.44, 0.43, 0. 43, 0.41, 0.48, 0.55, 0.57, 0.55, 0.56, 0.6, 0.64, 0.67, 0.73, 0.84, 0.94, 1.09, 1.24, 1.28, 1.19, 1.11, 1, 0.92, 0.86, 0.79, 0.76, 0.76, 0.76, 0.76, 0.92, 0.98, 1.03, 1.03, 1.03, 1.03, 1.07, 1.11, 1.24, 1. 44, 2.12, 3.26, 15, 9.45, 5.07, 4.59, 3.5, 2.84, 2.54, 2.57, 3.01, 2.32, 2.32, 2.97, 2.92, 3.88, 4.76, 5.99, 3.74, 2.92, 2.65, 2.57, 2. 97, 3.4, 4.13, 4.31, 3.89, 3.45, 3.01, 2.88, 2! .5, 2.29, 2.39, 2.25, 2.02, 1.87, 1.87, 2.54, 2.69, 2.76, 3.18, 3. 74, 4.59, 4.76, 4.36, 6.56, 5.07, 3.84, 3.55, 3.84, 3.84, 5.49, 5. 32, 3.74, 3.31, 3.4, 3.26, 3.09, 2.69, 2.54, 2.46, 2.39, 2.25, 2.22, 2.22, 2.25, 2.29, 2.22, 2.18, 2.05, 2.18, 2.39, 2.18, 2.29, 2.11, 1. 81, 1.6, 1.44, 1.41, 1.32, 1.37, 1.37, 1.65, 2.31, 2.25, 1.68, 1.41, 1.26, 1.15, 3.28, 1.93, 1.6, 1.53, 1.28, 1.13, 1.03, 1.03, 1.03, 1. 03, 1, 0.96, 0.92, 0.87, 0.82, 0.79, 0.76, 0.73, 0.7, 0.67, 0.64, 0. 64, 0.61, 0.61, 0.61, 1.76, 1.19, 1.24, 1.37, 1.68, 2.39, 2.05, 1. 78, 1.58, 1.41, 1.39, 1.5, 1.41, 1.32, 1.19, 1.11, 1.02, 1.07, 4.57, 1.96, 1.68, 1.5, 1.37, 1.24, 1.11, 1.03, 0.96, 0.94, 2.93, 2.88, 2. 92, 2.76, 2.02, 1.71, 1.5, 1.37, 1.22, 1.09, 1, 0.94, 0.87, 0.81, 0. 76, 0.73, 0.7, 0.67, 0.61, 0.58, 0.57, 0.55, 0.53, 0.51, 0.48, 0.47, 0.44, 0.43, 0.43, 0.41, 0.41, 0.38, 0.4, 0.4, 0.42, 0.42, 0.41, 0. 46, 0.53, 0.55, 0.52, 0.49, 0.51, 0.53, 0.55, 0.7, 1.03, 1.03, 1.17, 1.24, 1.19, 1.11, 1.03, 0.98, 0.92, 0.84,! 0.79, 0.75, 0.7, 0.67, 0.61, 0.58, 0.56, 0.56, 0.55, 0.53, 0.51, 0.48 , 0.46, 0.43, 0.41, 0.38, 0.37, 0.35, 0.34, 0.32, 0.31, 0.3, 0.29, 0.28, 0.27, 0.25, 0.26, 0.24, 0.23, 0.22, 0.22, 0.21, 0.21, 0.21), b = c(0.19, 0.19, 0.19, 0.18, 0.18, 0.18, 0.17, 0.17, 0.17, 0.17, 0. 16, 0.17, 0.17, 0.15, 0.15, 0.15, 0.15, 0.15, 0.15, 0.15, 0.15, 0. 15, 0.15, 0.15, 0.15, 0.15, 0.15, 0.15, 0.15, 0.15, 0.14, 0.14, 0. 14, 0.14, 0.14, 0.14, 0.14, 0.14, 0.14, 0.14, 0.14, 0.14, 0.14, 0. 14, 0.14, 0.15, 0.15, 0.15, 0.15, 0.15, 0.15, 0.15, 0.16, 0.16, 0. 17, 0.17, 0.18, 0.18, 0.18, 0.18, 0.18, 0.18, 0.18, 0.18, 0.19, 0. 21, 0.21, 0.21, 0.22, 0.23, 0.24, 0.24, 0.23, 0.24, 0.24, 0.25, 0. 25, 0.25, 0.28, 0.29, 0.29, 0.3, 0.31, 0.31, 0.34, 0.41, 0.46, 0.51, 0.57, 0.61, 0.64, 0.67, 0.7, 0.76, 0.82, 0.86, 1.05, 1.24, 1.05, 0. 94, 0.92, 0.9, 0.86, 0.82, 0.76, 0.76, 0.76, 0.78, 0.82, 0.9, 1.07, 1.76, 3.13, 3.64, 3.45, 3.01, 2.39, 2.02, 1.87, 2.11, 2.02, 1.78, 1. 63, 1.53, 1.63, 4.84, 12.5, 8.11, 3.89, 2.73, 2.11, 1.96, 3.17, 2. 65, 2.54, 3.01, 3.31, 3.6, 3.36, 2.76, 2.39, 2.11, 2.! 25, 2.08, 1.99, 2.11, 2.36, 3.13, 7.16, 5.39, 5.52, 5.32, 4.25, 3. 45, 3.26, 3.18, 3.74, 4.35, 5.79, 5.45, 4.42, 3.84, 3.36, 2.84, 2. 39, 3.84, 3.18, 3.22, 2.97, 2.73, 2.65, 2.92, 4.33, 3.01, 3.01, 3. 26, 3.09, 3.6, 3.64, 4.05, 4.25, 4.48, 3.69, 3.74, 3.6, 3.18, 2.76, 4.11, 2.92, 2.69, 2.73, 2.69, 3.93, 2.69, 2.18, 2.52, 2.69, 1.99, 2. 57, 1.81, 1.55, 1.44, 1.37, 1.28, 1.19, 1.19, 1.03, 1.03, 1, 0.94, 0.89, 0.87, 0.86, 0.86, 2.3, 1.55, 1.19, 1.11, 1.5, 1.39, 1.22, 1. 24, 1.07, 1.02, 0.96, 0.92, 1.34, 1.15, 1.03, 2.06, 1.76, 1.3, 1.15, 1.05, 0.98, 0.92, 0.89, 0.84, 0.81, 0.76, 0.73, 1.59, 5.2, 3.01, 2. 05, 1.65, 1.68, 5.29, 2.73, 1.96, 1.6, 1.41, 1.28, 1.15, 1.11, 1.13, 1.09, 1.03, 6.99, 10.6, 5.39, 3.45, 2.5, 1.87, 1.68, 1.78, 1.53, 1. 41, 1.3, 1.17, 1.05, 0.98, 0.92, 0.9, 0.87, 0.86, 0.82, 0.78, 0.75, 0.72, 0.67, 0.82, 1.6, 0.89, 0.94, 0.96, 0.92, 0.87, 0.82, 0.79, 0. 75, 0.7, 0.67, 0.64, 0.61, 0.58, 0.56, 0.53, 0.51, 0.48, 0.47, 0.46, 0.43, 0.41, 0.41, 0.68, 16.3, 17.2, 6.05, 3.6! 9, 2.92, 2.25, 1.87, 1.63, 1.46, 1.32, 1.19, 1.07, 1, 0.94, 0.89, 0.87 , 0.86, 0.81, 0.76, 0.73, 0.7, 0.7, 0.7, 0.7, 0.7, 0.67, 0.67, 0.66, 0.64, 0.61, 0.58, 0.56, 0.55, 0.53, 0.51, 0.48, 0.46, 0.44, 0.43, 0. 43, 0.41, 0.4, 0.38, 0.37, 0.36, 0.35, 0.34, 0.33, 0.32, 0.31, 0.31, 0.3, 0.3, 0.29, 0.29, 0.28, 0.27, 0.27), c = c(0.27, 0.25, 0.25, 0. 25, 0.24, 0.24, 0.23, 0.22, 0.22, 0.21, 0.21, 0.21, 0.21, 0.21, 0.2, 0.19, 0.19, 0.19, 0.19, 0.19, 0.19, 0.19, 0.19, 0.19, 0.19, 0.19, 0. 19, 0.19, 0.19, 0.18,
Re: [R] distance matrix and hclustering
For basic hierarchical clustering use groups - hclust(dist(qmu)) But there are many options for function dist() and for function hclust() and these will affect the results. For basic plotting use plot(groups) But as you will see, there are too many cases for the labels to be legible. Hierarchical clustering gives you from 1 to ncases groups. You have to decide where to cut the dendrogram to define a particular number of clusters. Since you are clustering on a single value, you may find kmeans clustering to be more useful You must specify the number of groups in advance, but you can try several group sizes to see what makes the most sense for your data. -- David L Carlson Associate Professor of Anthropology Texas AM University College Station, TX 77843-4352 -Original Message- From: r-help-boun...@r-project.org [mailto:r-help-bounces@r- project.org] On Behalf Of eliza botto Sent: Monday, July 30, 2012 1:44 AM To: r-help@r-project.org; smartpink...@yahoo.com Subject: [R] distance matrix and hclustering Dear R Users,i am very new to R. I want your help on an issue regarding distance matrix and cluster analysis i had discharge data of 4 rivers(a,b,c,d) in 4 vectors each having 364 values dput(qmu)structure(list(a = c(0.26, 0.25, 0.25, 0.25, 0.24, 0.23, 0.22, 0.21, 0.21, 0.21, 0.2, 0.19, 0.19, 0.19, 0.19, 0.18, 0.18, 0.18, 0.17, 0.17, 0.17, 0.17, 0.17, 0.17, 0.17, 0.17, 0.17, 0.17, 0.17, 0.17, 0.17, 0.17, 0.17, 0.17, 0.18, 0.19, 0.19, 0.19, 0.2, 0.21, 0.21, 0.21, 0.21, 0.21, 0.21, 0.19, 0.19, 0.18, 0.17, 0.17, 0.15, 0.18, 0.2, 0.21, 0.2, 0.19, 0.19, 0.19, 0.2, 0.24, 0.3, 0.3, 0.3, 0.32, 0.34, 0.42, 0.46, 0.48, 0.67, 0.82, 0.79, 0.73, 0.69, 0.67, 0.67, 0.66, 0.64, 0.61, 0.58, 0.56, 0.55, 0.55, 0.55, 0.52, 0.49, 0.48, 0.51, 0.53, 0.52, 0.49, 0.48, 0.48, 0.46, 0.46, 0.44, 0.43, 0.43, 0.41, 0.48, 0.55, 0.57, 0.55, 0.56, 0.6, 0.64, 0.67, 0.73, 0.84, 0.94, 1.09, 1.24, 1.28, 1.19, 1.11, 1, 0.92, 0.86, 0.79, 0.76, 0.76, 0.76, 0.76, 0.92, 0.98, 1.03, 1.03, 1.03, 1.03, 1.07, 1.11, 1.24, 1.44, 2.12, 3.26, 15, 9.45, 5.07, 4.59, 3.5, 2.84, 2.54, 2.57, 3.01, 2.32, 2.32, 2.97, 2.92, 3.88, 4.76, 5.99, 3.74, 2.92, 2.65, 2.57, 2.97, 3.4, 4.13, 4.31, 3.89, 3.45, 3.01, 2.88, 2! .5, 2.29, 2.39, 2.25, 2.02, 1.87, 1.87, 2.54, 2.69, 2.76, 3.18, 3.74, 4.59, 4.76, 4.36, 6.56, 5.07, 3.84, 3.55, 3.84, 3.84, 5.49, 5.32, 3.74, 3.31, 3.4, 3.26, 3.09, 2.69, 2.54, 2.46, 2.39, 2.25, 2.22, 2.22, 2.25, 2.29, 2.22, 2.18, 2.05, 2.18, 2.39, 2.18, 2.29, 2.11, 1.81, 1.6, 1.44, 1.41, 1.32, 1.37, 1.37, 1.65, 2.31, 2.25, 1.68, 1.41, 1.26, 1.15, 3.28, 1.93, 1.6, 1.53, 1.28, 1.13, 1.03, 1.03, 1.03, 1.03, 1, 0.96, 0.92, 0.87, 0.82, 0.79, 0.76, 0.73, 0.7, 0.67, 0.64, 0.64, 0.61, 0.61, 0.61, 1.76, 1.19, 1.24, 1.37, 1.68, 2.39, 2.05, 1.78, 1.58, 1.41, 1.39, 1.5, 1.41, 1.32, 1.19, 1.11, 1.02, 1.07, 4.57, 1.96, 1.68, 1.5, 1.37, 1.24, 1.11, 1.03, 0.96, 0.94, 2.93, 2.88, 2.92, 2.76, 2.02, 1.71, 1.5, 1.37, 1.22, 1.09, 1, 0.94, 0.87, 0.81, 0.76, 0.73, 0.7, 0.67, 0.61, 0.58, 0.57, 0.55, 0.53, 0.51, 0.48, 0.47, 0.44, 0.43, 0.43, 0.41, 0.41, 0.38, 0.4, 0.4, 0.42, 0.42, 0.41, 0.46, 0.53, 0.55, 0.52, 0.49, 0.51, 0.53, 0.55, 0.7, 1.03, 1.03, 1.17, 1.24, 1.19, 1.11, 1.03, 0.98, 0.92, 0.84,! 0.79, 0.75, 0.7, 0.67, 0.61, 0.58, 0.56, 0.56, 0.55, 0.53, 0.51, 0.48 , 0.46, 0.43, 0.41, 0.38, 0.37, 0.35, 0.34, 0.32, 0.31, 0.3, 0.29, 0.28, 0.27, 0.25, 0.26, 0.24, 0.23, 0.22, 0.22, 0.21, 0.21, 0.21), b = c(0.19, 0.19, 0.19, 0.18, 0.18, 0.18, 0.17, 0.17, 0.17, 0.17, 0.16, 0.17, 0.17, 0.15, 0.15, 0.15, 0.15, 0.15, 0.15, 0.15, 0.15, 0.15, 0.15, 0.15, 0.15, 0.15, 0.15, 0.15, 0.15, 0.15, 0.14, 0.14, 0.14, 0.14, 0.14, 0.14, 0.14, 0.14, 0.14, 0.14, 0.14, 0.14, 0.14, 0.14, 0.14, 0.15, 0.15, 0.15, 0.15, 0.15, 0.15, 0.15, 0.16, 0.16, 0.17, 0.17, 0.18, 0.18, 0.18, 0.18, 0.18, 0.18, 0.18, 0.18, 0.19, 0.21, 0.21, 0.21, 0.22, 0.23, 0.24, 0.24, 0.23, 0.24, 0.24, 0.25, 0.25, 0.25, 0.28, 0.29, 0.29, 0.3, 0.31, 0.31, 0.34, 0.41, 0.46, 0.51, 0.57, 0.61, 0.64, 0.67, 0.7, 0.76, 0.82, 0.86, 1.05, 1.24, 1.05, 0.94, 0.92, 0.9, 0.86, 0.82, 0.76, 0.76, 0.76, 0.78, 0.82, 0.9, 1.07, 1.76, 3.13, 3.64, 3.45, 3.01, 2.39, 2.02, 1.87, 2.11, 2.02, 1.78, 1.63, 1.53, 1.63, 4.84, 12.5, 8.11, 3.89, 2.73, 2.11, 1.96, 3.17, 2.65, 2.54, 3.01, 3.31, 3.6, 3.36, 2.76, 2.39, 2.11, 2.! 25, 2.08, 1.99, 2.11, 2.36, 3.13, 7.16, 5.39, 5.52, 5.32, 4.25, 3.45, 3.26, 3.18, 3.74, 4.35, 5.79, 5.45, 4.42, 3.84, 3.36, 2.84, 2.39, 3.84, 3.18, 3.22, 2.97, 2.73, 2.65, 2.92, 4.33, 3.01, 3.01, 3.26, 3.09, 3.6, 3.64, 4.05, 4.25, 4.48, 3.69, 3.74, 3.6, 3.18, 2.76, 4.11, 2.92, 2.69, 2.73, 2.69, 3.93, 2.69, 2.18, 2.52, 2.69, 1.99, 2.57, 1.81, 1.55, 1.44, 1.37, 1.28, 1.19, 1.19, 1.03, 1.03, 1, 0.94, 0.89, 0.87, 0.86, 0.86, 2.3, 1.55, 1.19, 1.11, 1.5, 1.39, 1.22, 1.24, 1.07, 1.02, 0.96, 0.92, 1.34, 1.15, 1.03, 2.06, 1.76, 1.3, 1.15, 1.05, 0.98, 0.92, 0.89, 0.84, 0.81, 0.76, 0.73, 1.59, 5.2, 3.01, 2.05, 1.65, 1.68, 5.29,
Re: [R] distance matrix
Em 5/5/2011 07:34, antu escreveu: Hello all, I am wondering if there is anyway to create distance matrix for replicated data for example, I have a data like sample pop id var1var2var3var4 1.1 1 a 1 1 0 1 1.2 1 a 0 0 1 0 1.3 1 a 1 1 0 1 2.1 2 b 0 0 1 0 2.2 2 b 1 1 1 1 2.3 2 b 0 1 0 0 2.4 2 b 1 0 1 1 3.1 3 a 0 1 0 1 3.2 3 a 1 1 1 0 3.3 3 a 0 0 0 0 dist(data[,c(4:7)] gives the distance of samples, but I also need the distances of pop ie (1,2,3) and also id (a,b) how can I achieve this?? Just a doubt: does the idea of comparing (ordering) the variable pop and id make sense? Or expressed in more direct way: what would a distance between b and a mean (same for the pop labels)? __ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.
Re: [R] distance matrix
I don't know whether I understood your question, but 1.1, 1.2 , 1.3 all are subsample of 1 , so, rather than comparing 1000 subsample, comparison of 20 pop level makes more sense in my case. thanks for query - Ananta Acharya Graduate Student -- View this message in context: http://r.789695.n4.nabble.com/distance-matrix-tp3498033p3498890.html Sent from the R help mailing list archive at Nabble.com. __ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.
Re: [R] distance matrix?
x - 0:10 y - t(replicate(11, 0:10)) abs(sweep(y, 1, x)) Hope this helps. On Mon, Jun 28, 2010 at 5:21 AM, clips10 m.mcquil...@lancaster.ac.uk wrote: I have a vector 0 to 10 and want to create a matrix with the differences between the numbers in it for instance: 0 1 2 3 4 5 6 7 8 9 10 0 0 1 2 3 4 5 6 7 8 9 10 1 1 0 1 2 3 4 5 6 7 8 9 2 3 4 5 6 7 8 9 10 Etc etc. So that the matrix is filled with the differences between in absolute value so there are no negatives. Any ideas? Thanks -- View this message in context: http://r.789695.n4.nabble.com/distance-matrix-tp2270722p2270722.html Sent from the R help mailing list archive at Nabble.com. __ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code. -- John A. Ramey, M.S. Ph.D. Candidate Department of Statistics Baylor University http://www.ramhiser.com __ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.
Re: [R] distance matrix?
abs(outer(1:10, 1:10, FUN=-)) [,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10] [1,]012345678 9 [2,]101234567 8 [3,]210123456 7 [4,]321012345 6 [5,]432101234 5 [6,]543210123 4 [7,]654321012 3 [8,]765432101 2 [9,]876543210 1 [10,]987654321 0 Kjetil On Mon, Jun 28, 2010 at 5:44 PM, John Ramey johnra...@gmail.com wrote: x - 0:10 y - t(replicate(11, 0:10)) abs(sweep(y, 1, x)) Hope this helps. On Mon, Jun 28, 2010 at 5:21 AM, clips10 m.mcquil...@lancaster.ac.uk wrote: I have a vector 0 to 10 and want to create a matrix with the differences between the numbers in it for instance: 0 1 2 3 4 5 6 7 8 9 10 0 0 1 2 3 4 5 6 7 8 9 10 1 1 0 1 2 3 4 5 6 7 8 9 2 3 4 5 6 7 8 9 10 Etc etc. So that the matrix is filled with the differences between in absolute value so there are no negatives. Any ideas? Thanks -- View this message in context: http://r.789695.n4.nabble.com/distance-matrix-tp2270722p2270722.html Sent from the R help mailing list archive at Nabble.com. __ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code. -- John A. Ramey, M.S. Ph.D. Candidate Department of Statistics Baylor University http://www.ramhiser.com __ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code. __ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.
Re: [R] distance matrix as text file - how to import?
On Tue, Apr 8, 2008 at 1:50 PM, Hans-Jörg Bibiko [EMAIL PROTECTED]
wrote:
I was sent a text file containing a distance matrix à la:
1
2 3
4 5 6
Thanks a lot for your hints.
At the end all hints ends up more or less in my stony way to do it.
Let me summarize it.
The clean way is to initialize a matrix containing my distance matrix
and generate a dist object by using as.dist(mat).
Fine. But how to read the text data (triangular) into a matrix?
#1 approach - using 'read.table'
mat = read.table(test.txt, fill=T)
The problem here is that the first line doesn't contain the correct
number of columns of my matrix, thus 'read.table' sets the number of
columns to 5 as default.
Ergo I have to know the number of columns (num_cols) in beforehand in
order to do this:
mat = read.table(test.txt, fill=T, col.names=rep('', num_cols))
Per definitionem the last line of test.txt contains the correct
number of columns.
On a UNIX/Mac you can do the following:
num_cols - as.numeric(system(tail -n 1 'test.txt' | wc -
w,intern=TRUE))
In other words, read the last line of 'test.txt' and count the number
of words if the delimiter is a space. Or one could use 'readLines' and
split the last array element to get num_cols.
#2 approach - using 'scan()'
mat = matrix(0, num_cols, num_cols)
mat[row(mat) = col(mat)] - scan(test.txt)
But this also leads to my problem:
1
2 4
3 5 6
instead of
1
2 3
4 5 6
one solution
The approach #2 has two advantages: it's faster than read.table AND I
can calculate num_cols. The only problem is the correct order. But
this is solvable via: reading the data into the upper triangle and
transpose the matrix
mat - matrix(0, num_cols, num_cols)
mat[row(mat) = col(mat)] - scan(test.txt)
mat - t(mat)
Next. If I know that my text file really contains a distance matrix
(i.e. the diagonals have been removed) then I can do the following:
data - scan(test.txt)
num_cols - (1 + sqrt(1 + 8*length(data)))/2 - 1
mat - matrix(0, num_cols, num_cols)
mat[row(mat) = col(mat)] - data
mat - t(mat)
#Finally to get a 'dist' object:
mat - rbind(0, mat)
mat - cbind(mat, 0)
dobj - as.dist(mat)
Again, thanks a lot!
--Hans
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and provide commented, minimal, self-contained, reproducible code.
Re: [R] distance matrix as text file - how to import?
On Tue, Apr 8, 2008 at 1:50 PM, Hans-Jörg Bibiko [EMAIL PROTECTED] wrote: Dear all, I have -hopefully- a tiny problem. I was sent a text file containing a distance matrix à la: 1 2 3 4 5 6 Try this! I put your test data in text.txt and voila: mat - matrix(0, 3,3) mat[row(mat) = col(mat)] - scan(test.txt) I found this Idea after RSiteSearch(scan triangular) led to this item as the very first link: http://finzi.psych.upenn.edu/R/Rhelp02a/archive/22369.html PJ -- Paul E. Johnson Professor, Political Science 1541 Lilac Lane, Room 504 University of Kansas __ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.
Re: [R] distance matrix
Suppose you have: x - runif(25) y - rnorm(25) x.df - data.frame(x,y) dist(x.df) The default is euclidean distance. Hope this helps! Sincerely, Erin On Jan 20, 2008 2:41 PM, WCD [EMAIL PROTECTED] wrote: Hello, I want do get the point to point distance matrix. Suppose, I have a data frame where the first column is X and second column is Y coordinate of points. I define a function dst(x1,y1,x2,y2) to claculate distance between two points. But I don't know how to tell R to calculate dst for every two points and create a matrix of these distances. Can you give me a little guidance, please? I am quite new to R and programming. Thanks for every advice. Filip Kral. -- View this message in context: http://www.nabble.com/distance-matrix-tp14986595p14986595.html Sent from the R help mailing list archive at Nabble.com. __ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code. -- Erin Hodgess Associate Professor Department of Computer and Mathematical Sciences University of Houston - Downtown mailto: [EMAIL PROTECTED] __ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.
Re: [R] Distance matrix in SpDep-package
Elke Moons elke.moons at uhasselt.be writes: 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 dnearneigh based on x-y coordinates. Or is there another package that can transform a distance matrix into fake x-y coordinates, so that the SpDep-package can work with it? If you use the mat2listw() function in spdep on (slices of) your matrix, you can get to usable listw objects. If the distance matrix is full (that is all sites to all sites), you could impose very large values on distances which fall outside a given slice, say outside 0-100m, to create a listw object corresponding to a dnearneigh(xy, 0, 100) neighbours list. See the mat2listw help page for more details: The function converts a square spatial weights matrix to a weights list object, optionally adding region IDs from the row names of the matrix, as a sequence of numbers 1:nrow(x), or as given as an argument. Note that the input matrix is expected to contain spatial weights, so inverse distances would be closer than distances in their native metric. You should also look at the glist= argument to nb2listw() if you want generalised spatial weights. Roger Bivand Thank you very much for your answer. Kind regards, Elke Moons __ Elke Moons, PhD Transportation Research Institute/ Instituut voor Mobiliteit (IMOB) Universiteit Hasselt Wetenschapspark 5, bus 6 3590 Diepenbeek Belgium Tel. +32-11- 26.91.26 Fax. +32-11-26.91.99 E-mail: mailto:elke.moons at uhasselt.be elke.moons at uhasselt.be [[alternative HTML version deleted]] __ R-help at r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code. __ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.
