binaryOp_m3d: Matrix 3 dimentional product.
In nlr: Nonlinear Regression Modelling using Robust Methods

Description Usage Arguments Details Value Author(s) References See Also Examples

Binary Operator, for sample size (n), vector with size p of gradient stored in (n*p) matrix, transpose of gradient multiple by gradient for (n) points can be obtained by (gradient %m3d% gradient). Result save in (n*p*p) three dimentional array.

1	mat1 %m3d% mat2

`mat1`	n*p matrix, in gradient example n is sample size, p is number of parameters, mat1[i,] is (p) vector of gradient of ith sample.
`mat2`	p*n matrix.

It is Used to implement gradient product for n sample

Array_{n*p*p} =\nabla_{θ}^T f_i(θ) \nabla_{θ} f_i(θ),i=1,…,n

Hossein Riazoshams, May 2014. Email: riazihosein@gmail.com URL http://www.riazoshams.com/nlr/

Riazoshams H, Midi H, and Ghilagaber G, 2018,. Robust Nonlinear Regression, with Application using R, Joh Wiley and Sons.

%3d*m%, prodVA

##---- Should be DIRECTLY executable !! ----
##-- ==>  Define data, use random,
##--	or do  help(data=index)  for the standard data sets.

## The function is currently defined as
"%m3d%"
m1 <- matrix(c(1:4),nrow=2)
m2 <- matrix(c(1:4),nrow=2)
d=m1 %m3d% m2