similar to: 3-d splinefun

Colleagues, I have a routine in package labdsv that calls a FORTRAN subroutine. Recently, I was informed that it sometimes gives different results on a PC and Mac, and that the PC version is clearly wrong. I tested it on linux (because I don't have a PC), and I get the same (incorrect) behavior as the PC. Simply by inserting debug WRITE statements in the FORTRAN I would get different,

Hello, Is the an analogous function to splinefun or approxfun for multivariate data sets? For example, if I have a data set w/ x's and corresponding y's, I can use either splinefun or approx fun to find values of y for interpolated values of x. Now, what if I want to do the same thing except with a 3 dim. system? If I have a data set with x's, y's, and corresponding

Hello, We are trying to find a function to compute "stress" in our multidimensional scaling analysis of a dissimilarity matrix. We've used "dist()" to create the matrix and "cmdscale()" for the scaling. In order to determine the number of dimensions we would like to plot stress vs. dimensions. However, we cannot find a pre-made command. It seems that other

At present R has separate functions "spline" and "splinefun". The first of these carries out spline interpolation of a data set and returns the interpolated values; the second returns the interpolating function itself (approx and approxfun are similar). I would like to combine these into a single function "spline" with an (optional) argument which determines which

Hi there, I would like to find a more efficient way of permuting the rows and columns of a symmetrical matrix that represents ecological or actual distances between objects in space. The permutation is of the type used in a Mantel test. Specifically, the permutation has to accomplish something like this: Original matrix addresses: a11 a12 a13 a21 a22 a23 a31 a32 a33 Example

Dear mailing group, I have loaded an Excel file into R by calling it ".csv" and using the "read.csv" function in R. However then I want to use the (limma package specific, I believe) function "hclust", which clusters data in a tree dendrogram, by similarity. However, I receive the errors msg.s: 1) "missing observations in cov/cor" 2) "In

hi all, i'm trying to get elements in a matrix into a vector. i need a "streamlined" way to do it as the way i'm doing it is not very serviceable. an example is a 3x3 matrix like 0 0 3 2 0 0 0 4 0 to a vector like 3 2 4 thanks...mj [[alternative HTML version deleted]]

Is there a way of calculating the derivative of a function returned by splinefun()? Such a function is a cubic spline, whence it has a calculable derivative, but is there a (simple) way of getting at it? One workaround that I have thought of is to take a fine grid of points, evaluate the function returned by splinefun() at these points, put an interpolating spline through these points using

Hi, In my version of R, the stats package splinefun code for fitting a Fritsch and Carlson monotonic spline does not appear to guarantee a monotonic result. If two adjoining sections both have over/undershoot the way the resulting adjustment of alpha and beta is performed can give modified values which still do not satisfy the required constraints. I do not think this is due to finite precision

This is a low priority bug that has been around for a while, but I came acr= oss it again while alpha testing 2.8. The resulting function for splinefun gives incorrect deriv values when x is= less than the smallest x-value used to create the function (at least in on= e circumstance), but does the correct thing for x greater than the largest = x-value. Here is an example: > x <- 1:10 >

I am working with the function: splinefun() ... When plugging in the variables, I get the function program as if though having only entered '"splinefun". only way to get the values is by spline(xxx,yyy, n=length(xxx)/10, ties = mean)$x and spline(xxx,yyy, n=length(xxx)/10, ties = mean)$y. I'm just wondering if there is something wrong with the package or if I'm doing

hello R_team having perfomed a PCA on my fitted model with the function: data<- na.omit(dataset) data.pca<-prcomp(data,scale =TRUE), I´ve decided to aggregate two variables that are highly correlated. My first question is: How can I combine the two variables into one new predictor? and secondly: How can I predict with the newly created variable in a new dataset? Guess I need the

Could anybody help me in mixing the matrix values randomly (first rows and then columns)... for eg putting the 1 st row in the place of 3 rd and 3rd in place of 4 th and 4th in place of 1st row ...something like this in columns also.. Please suggest me some ways.. thanks a lot.. with regards, boopathy. --------------------------------- [[alternative HTML version deleted]]

Hi! I have faced a big problem with R on my LINUX machine. I want to load a Fortran code via R, but the program can't do it. I have tried to load simpler codes, which seem to work perfectly, but the code I would like to load - which is a little more complicated - can't be loaded. I have installed the R 2.2.1 version. Should I need anything else to install (e.g. a library)? Is there a way

Hello: I need to take a species-sample matrix and transpose it to the format used by PC-ORD for analysis. Unfortunately, the number of species is very large (>5000), and so this operation cannot be performed simply in an application like Excel, which has a 255 column limit. So, I wrote relatively simple code in R that I hoped would do this (appended below). But there are glitches. The

It would be nice to have a date stamp on an object. In S/Splus this was always available, because objects were files. I have looked around, but I presume this information is not available. -------------------------------------------------------------------- Trevor Hastie hastie at stanford.edu Professor, Department of Statistics, Stanford University Phone:

Dumb newbie question: I've searched the manual, R help and the mailing list archives, but can't seem to find the answer to this simple problem that I have. If I have a series of columns in a dataframe: (A, B, C ...) and I want to merge them with another series of columns (Z,Y,X ...) such that the resulting data frame has columns A,Z,B,Y,C,X ..., how do I do this? In other words, I'm

I am modeling a trend surface using trmat and want to trim the resulting matrix to the area enclosed by my real data (i.e., remove all the extrapolated areas). I was using chull and in.chull to calculate the convex hull and change all the other values created by trmat to NA. However, my real data has portions that are slightly concave so chull would give me slivers that are extrapolations from

Hi R-users: [R 2.2 on OSX 10.4.3] I have a (sparse) vegetation data frame with 500 rows (sampling units) and 177 columns (plant species) where the data represent % cover. I need to summarize the cover data by returning the names of the most dominant and the second most dominant species per plot. I reduced the data frame to omit cover below 5%; this is what it looks like stacked. I have

--MP_/Rxf/JAvsQx5JLkhZFc9Jmn4 Content-Type: text/plain; charset=US-ASCII Content-Transfer-Encoding: 7bit Content-Disposition: inline G'day Greg, On Mon, 6 Oct 2008 19:50:13 +0200 (CEST) Greg.Snow at imail.org wrote: > This is a low priority bug that has been around for a while, but I > came across it again while alpha testing 2.8. Indeed, that bug must have been around since