similar to: how to interpolate multidimensional (3D) spatial data

Dear R cracks I am trying to fetch 38 Tables from 38 ESRI Geodatabases through an ODBC connection. I stored the 38 channels in a list and the 38 tablenames in an other list. With a for(i in 1:38) .... sqlFetch(....) I try to read the tables into a third list. But always after a certain amount of rounds (mostly 16) i get Fehler in odbcQuery(channel, query, rows_at_time) : Calloc konnte

Hello! I'm running Samba 3.0.0 with Openldap 2.1.22. Samba is my PDC and I'm using ldapsam as backend. Nearly everythings works, but I have a public share [tmp] which should be accessible without authentication from all clients even if they are no domain members. I think, my share definition is o.k. in smb.conf but if I click on the Samba server symbol on a client (Microsoft Windows

The vegan package has non-metric multidimensional scaling in addition to a variety of other ordination techniques. Regards, Helen Mills Poulos Yale University

my=function(x){ len=1 for(i in 1:len){ y[i]=x[i] } g=1 w=NULL t=NULL for(i in 1:len)w[i]=x[i+len] for(i in 1:len)t[i]=x[i+2*len] for(i in 1:len)g=g*dnorm(y[i])*dnorm(w[i])*dnorm(z[i]) return(g) } cuhre(6,1,my,rep(-100,6),rep(100,6)) Error in crff(match.call(), integrand, "cuhre", libargs, ...) : Additional argument not expected in the integrand function function change to

Hello, I apologize for eventual double-posting. I am trying to integrate a 2-dimensional function that already calls the function adapt. More precisely, I am calling adapt(2,lower=c(-100,-100),upper=c(100,100),functn=function(s){1-exp(-50*Unc enteredGauss(c(-10,10,-10,10),60,s)}) where UncenteredGauss is given by the following code in R:

Hi: I was wondering if someone could give me some examples of how to use the "integrate" function to perform multi-dimensional quadrature? I have a posterior density (up to a constant), for which I'd like to evaluate the normalizing constant. thanks for any help, Ravi.

i have a plain old array initialized like this: @columns = Array.new this array needs to be an array of arrays.. how do i tell ruby that this is an array of arrays? what i want to do is something like this: @columns[i] << ''some value'' where is is determined programattically.. obviously, ruby won''t let me do this since @columns[i] is not an array, but an

Hi, Suppose I have a matrix of size 256x14x32 in MATLAB. I want to import that into R. I used readMat and then do.call. But the variable is stored as an array as its done in R. However, I want to define a variable W=array(0,c(256,14,32)) in R and read the multidimensional matlab variable into W. I am not able to do this in R. Please, could you help ? Thanks Gopi [[alternative HTML version

Dear R-list, Hi everyone, Im trying to make an analysis of multidimensional contingency tables using R. I' working with the Agresti example where you have the data from 3 categories. The thing is how can I do the analisys using the G2 statistics. Somebody can send me an Idea? I attach the program where you can find the data. Best Regards, > prob1<-

Dear Statistics-Experts, Assume you have given a new and untested pseudo-random number generator (prng) and you want to test if it "works". The distribution function (cdf) from which the prng is supposed to sample is known. Further, you are given some finite (large) sample from the prng. If the sample is one-dimensional, we can apply the cdf to it and test the sample for being

I want to create a MDS plot with pairwise Fst values derived from a population genetics project. My Fst values are in a tab-delimited file (lower triangle only) that I view with Excel. When I use the cmdscale command I get the message: Error in cmdscale(x) : Distances must be result of dist or a square matrix In addition: Warning messages: 1: "^" not meaningful for factors in:

Hello, i want to create a multidimensional Array or Hash with group_by ''created_at''. 3 dimensions needed: myArray[week][day][data] currently i only created it with 2 dimesions: #model def self.group_per_day all.group_by{|t| t.created_at.strftime("%d. %B, %Y")}.sort #"%U" for Weeks end #controller @pdf_activities = Activity.group_per_day #view

Hi all, Does anyone know if there's R code available for doing Hybrid Multidimensional Scaling (or Semi-Strong HMDS, e.g. Belbin 1991 J. Veg. Sci. 2:491-)? I've found only commercial software that does it. Thanks, Anni

Hi Does anyone know if there's a package I can use to do Multidimensional scaling ? Thank's EJ -.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.- r-help mailing list -- Read http://www.ci.tuwien.ac.at/~hornik/R/R-FAQ.html Send "info", "help", or "[un]subscribe" (in the "body", not the subject !) To: r-help-request at

Hi, I was wondering if there is already some function implemented into R that reads in tables with more than 2 dimensions. There is probably something neat out there... Thanks, Werner Wissenswertes zum Thema PC, Zubeh?r oder Programme. BE A BETTER INTERNET-GURU! www.yahoo.de/clever

I sent a query to R-Help about the availability of nonmetric multidimensional scaling (MDS) algorithms in R. I would like to thank Tony Rossini, Jonathan Baron, Sundar Dorai-Raj, and Brian Ripley for helpful replies. The gist of the replies is that isoMDS in the MASS library provides Kruskal's method for nonmetric MDS, sammon in the MASS library provides Sammon's nonlinear mapping method

If something like the second-order function does not fit your data well, it may well be that the data do not admit a simple structure that you can easily code in C. If you expect the structure of the function to be simple, tell gam() so by specifying a small dimensional basis (via the k= argument in s()). This will probably ease the computational burden. HTH, Andy > -----Original

You can use R objects, such as the return from gam, and the predict.gam function, from C. See the R extensions manual. Reid Huntsinger -----Original Message----- From: RenE J.V. Bertin [mailto:rjvbertin at despammed.com] Sent: Thursday, February 27, 2003 3:42 PM To: Wiener, Matthew Cc: r-help at stat.math.ethz.ch Subject: Re: [despammed] RE: [R] multidimensional function fitting On Thu, 27

Hello, Is there a test for independence available based on a multidimensional contingency table? I've about 300 processes, and for each of them I get numbers for failures and successes. I've two or more conditions under which I test these processes. If I had just one process to test I could just perform a fisher or chisquare test on a 2x2 contigency table, like this: for one process:

Dear R list Would anyone be able to tell me whether it is possible to do "enhanced multidimensional scaling" (enhanced MDS) in R? In other words, something that goes beyond "cmdscale" by iteratively improving the fit between observed dissimilarities and inter-object distances, using the KYST algorithm (Kruskal, 1964). I have found several implementations of non-metric MDS