search for: tensors

Dear All, I have tried to install the tensor package (from: http://cran.r-project.org/src/contrib/PACKAGES.html#tensor ), using the comand: " shell("Rcmd INSTALL tensor") " then I got the following mensage: ---------------------------------------------------------------------------------- make: Entering directory `/d/bin/cran/rw1022/src/gnuwin32' make DLLNM= EXTRADOCS= \

Hi, I have tried to install 'tensor' as a new package in these phases: 1. via 'Install package from local Zip-File' in Rgui/Windows98: install.packages("D:/R/_Pakets12MB/tensor.zip", .lib.loc[1], CRAN = NULL) 2. Looking at the library folder, there was now a new entry 'tensor' including some files e.g. \library\tensor\R\tensor.R 3. Then I have done

Hi Everyone, To complete the outer() and kronecker() functions in the base, may I suggest the following tensor() function, which allows the multiplication of arrays through sets of conformable dimensions. I am happy to write a help page if required. The code also needs a setdiff() function which prompts me to ask: what about simple set functions? I expect many of us have written our own

Dear all, I need to compute tensor product of B-spline defined over equi-spaced break-points. I wrote my own program (it works in a 2-dimensional setting) library(splines) # set the break-points Knots = seq(-1,1,length=10) # number of splines M = (length(Knots)-4)^2 # short cut to splineDesign function bspline = function(x) splineDesign(Knots,x,outer.ok = T) # bivariate tensor product of

Hi guys, I need some help to analyzing my data. I start to describe my data: I have 21 matrices, every matrix on the rows has users and on columns has items, in my case films. Element of index (i, j) represent the rating expressed by user i about item j. I have a matrix for each of professions. An example of a this type of matrix is: item 1 item 2 item 3 item4 id

I'd like to compare tests based on the mixed model representation of additive models, testing among others y=f(x1)+f(x2) vs y=f(x1)+f(x2)+f(x1,x2) (testing for additivity) In mixed model representation, where X represents the unpenalized part of the spline functions and Z the "wiggly" parts, this would be: y=X%*%beta+ Z_1%*%b_1+ Z_2%*%b_2 vs y=X%*%beta+ Z_1%*%b_1+ Z_2%*%b_2 + Z_12

Dear R-users, I am searching to the "best" way to compute a series of n matrix multiplications between each matrix (mXm) in an array (mXmXn), and each column of a matrix (mXn). Please find below an example with four possible solutions. The first is a simple for-loop which one might avoid; the second solution employs the tensor product but then manually selects the right outcomes. The

Hi list, I'm working with gamm models of this sort, using Simon Wood's mgcv library: gm<- gamm(Z~te(x,y),data=DATA,random=list(Group=~1)) gm1<-gamm(Z~te(x,y,by=Factor)+Factor,data=DATA,random=list(Group=~1)) with a dataset of about 70000 rows and 110 levels for Group in order to test whether tensor product smooths vary across factor levels. I was wondering if comparing those two

Hi, I am trying to fit a smoothing model where there are three dimensions over which I can smooth (x,y,z). I expect interactions between some, or all, of these terms, and so I have set up my model as mdl <- gam(PA ~ s(x) + s(y) + s(z) + te(x,y) + te(x,z) + te(y,z) + te(x,y,z),...) I have recently read about the ti(), "tensor product interaction smoother", which takes care of these

Hi everyone, I ran a binomial GAM consisting of a tensor product of two continuous variables, a continuous parametric term and crossed random intercepts on a data set with 13,042 rows. When trying to plot the tensor product with vis.gam(), I get the following error message: Error in persp.default(m1, m2, z, col = col, zlim = c(min.z, max.z), xlab = view[1], : invalid 'z' limits In

Hello, I am trying to estimate a multivariate regression of Y on X with regression splines. Y is (nx1), and X is (nxd), with d>1. I assume the data is generated by some unknown regression function f(X), as in Y = f(X) + u, where u is some well-behaved regression error. I want to estimate f(X) via regression splines (tensor product splines). Then, I want to get the predicted values for some new

I've set up a simple tensor with indices 'a' and 'b'. > ftable(B) b u v w x y a a1 0.001868954 0.403345197 0.030088185 0.137252368 0.142634612 a2 0.396935972 0.945219795 0.068828465 0.314180585 0.446338719 a3 0.752412200 0.748810918 0.125532631 0.471686930 0.345062348 a4 0.191103000 0.536607533 0.257740399

Hello, I have been wondering of an efficient way to do this: I have an n x m x p array Z and a p x n matrix Y. I want to multiply each of the n matrices with the corresponding column vector of Y. In other words, I am wanting to matrix multiply: Z[i, ,] %*% Y[, i] which will give me a (two-dimensional) array or matrix of dimension n x p with the i'th row storing the above. Any pointers

Hi All, I'd like to plot something like http://www.nawcwpns.navy.mil/~weather/mugu/mesodata/analysis.html Looking through the galleries at http://addictedtor.free.fr/graphiques/allgraph.php http://r-spatial.sourceforge.net/gallery/ http://fawn.unibw-hamburg.de/cgi-bin/Rwiki.pl?GraphGallery demo(graphics) I did not find a function to plot a 2d field on a matrix. I did find mention of a

Hi all, In preparation for teaching a class next week, I've been reviewing R's standard modelling algebra. I've used it for a long time and have a pretty good intuitive feel for how it works, but would like to understand more of the technical details. The best (online) reference I've found so far is the section in "An Introduction to R"

Hi! I'm learning mgcv, and reading Simon Wood's book on GAMs, as recommended to me earlier by some folks on this list. I've run into a question to which I can't find the answer in his book, so I'm hoping somebody here knows. My outcome variable is binary, so I'm doing a binomial fit with gam(). I have five independent variables, all continuous, all uniformly

Avi, I was not trying to provide the most economical solution. I was trying to anticipate that people (either the OP or others searching for how to stack columns of a matrix) might be motivated by calculations in multilinear algebra, in which case they might be interested in the rTensor package. On Sun, Aug 6, 2023 at 6:16?PM <avi.e.gross at gmail.com> wrote: > > Eric, > > I

PTAk_1.1-1 ( Principal Tensor Analysis on k modes) has been released on CRAN A multiway method to decompose a tensor (array) of any order, as a generalisation of SVD also supporting non-identity metrics and penalisations. 2-way SVD with these extensions is also available. The package includes also some other multiway methods: PCAn (Tucker-n) and

PTAk_1.1-1 ( Principal Tensor Analysis on k modes) has been released on CRAN A multiway method to decompose a tensor (array) of any order, as a generalisation of SVD also supporting non-identity metrics and penalisations. 2-way SVD with these extensions is also available. The package includes also some other multiway methods: PCAn (Tucker-n) and

Hi all, Could anybody recommend some easy-to-understand and example based notes/tutorials on how to use cubic splines to do filtering on multi-dimension data? I am confused by the 1-dimensional case, and more confused by multi-dimensional case. I found all the books suddenly become very abstract when it comes to this subject. They don't provide examples in R or Splus at all. Specifically,