search for: multilinear

...alf Of Eric Berger Sent: Sunday, August 6, 2023 3:34 AM To: Bert Gunter <bgunter.4567 at gmail.com> Cc: R-help Mailing List <r-help at r-project.org>; Steven Yen <styen at ntu.edu.tw> Subject: Re: [R] Stacking matrix columns Stacking columns of a matrix is a standard operation in multilinear algebra, usually written as the operator vec(). I checked to see if there is an R package that deals with multilinear algebra. I found rTensor, which has a function vec(). So, yet another way to accomplish what you want would be: > library(rTensor) > vec(as.tensor(x)) Eric On Sun, Aug 6,...

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 am not sure your solution is particularly economical albeit it works for arbitrary arrays of any dimension, presumably. But i...

Stacking columns of a matrix is a standard operation in multilinear algebra, usually written as the operator vec(). I checked to see if there is an R package that deals with multilinear algebra. I found rTensor, which has a function vec(). So, yet another way to accomplish what you want would be: > library(rTensor) > vec(as.tensor(x)) Eric On Sun, Aug 6,...

...there is for regression and anova). When I enter: step(Model1, data=Mydata) R returns the message: Error in drop1.mlm(fit, scope$drop, scale = scale, trace = trace, k = k, : no 'drop1' method for "mlm" models Which tells me that there is no step, drop1 or add1 function for multilinear models (mlm). Correct? My model looks like this: Model1 <- lm(cbind(Var1, Var2, Var3, Var4, Var5) ~ X, data=Mydata) But is there another way to do a stepwise manova? Thanks a lot for your help, Veronika **************************************************************************************...

Or just dim(x) <- NULL. (as matrices in base R are just vectors with a dim attribute stored in column major order) ergo: > x [1] 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 > x<- 1:20 ## a vector > is.matrix(x) [1] FALSE > dim(x) <- c(5,4) > is.matrix(x) [1] TRUE > attributes(x) $dim [1] 5 4 > ## in painful and unnecessary detail as dim() should

...ackage provides tools to perform linear regressions using various models, to manipulate the genetic effects, and to compute genotype to phenotype maps, i.e. the function explaining how the genes expresses a given character. In addition, the 'noia' package provides a tool to perform 'multilinear' regression, an attempt of non-linear genotype-phenotype mapping. In summary, 'noia' is a wrapper for lm() and nls() functions in a very specific context: estimating the effects of genes on a given trait. NB: 'noia' is useless if the location of the genes is not known. Loca...

...ackage provides tools to perform linear regressions using various models, to manipulate the genetic effects, and to compute genotype to phenotype maps, i.e. the function explaining how the genes expresses a given character. In addition, the 'noia' package provides a tool to perform 'multilinear' regression, an attempt of non-linear genotype-phenotype mapping. In summary, 'noia' is a wrapper for lm() and nls() functions in a very specific context: estimating the effects of genes on a given trait. NB: 'noia' is useless if the location of the genes is not known. Loca...