## R: matrix by vector multiplication - Stack Overflow.

In mathematics, matrix multiplication or matrix product is a binary operation that produces a matrix from two matrices with entries in a field, or, more generally, in a ring or even a semiring.The matrix product is designed for representing the composition of linear maps that are represented by matrices. Matrix multiplication is thus a basic tool of linear algebra, and as such has numerous.

Here is an example of Matrix arithmetic - add, subtract, multiply, and divide in time!: xts objects respect time. Course Outline. Exercise. Matrix arithmetic - add, subtract, multiply, and divide in time! xts objects respect time. By design when you perform any binary operation using two xts objects, these objects are first aligned using the intersection of the indexes. This may be surprising.

Matrix multiplication and linear combinations. by Marco Taboga, PhD. The product of two matrices can be seen as the result of taking linear combinations of their rows and columns. This way of interpreting matrix multiplication often helps to understand important results in matrix algebra. Table of contents. Terminology. Post-multiplying a matrix by a vector. Pre-multiplying a matrix by a.

From: r-help-bounces at r-project.org (mailto:r-help-bounces at r-project.org) On Behalf Of Megh Dal Sent: Wednesday, 30 January 2008 5:20 PM To: r-help at stat.math.ethz.ch Subject: (R) Multiplying each row of a big matrix with a vector I have a big matrix 'ret'. I want to multiply each row of it with a 2nd.

Geometrical meaning of a matrix multiply by a vector I'm currently study vectors and matrix, but I get confused about the geometrical meaning of multiplies a vector by a matrix. For example, I know that apply a cross product between two vectors, the geometrical meaning is that you get a vector which is perpendicular to the plane that two vectors form.

Enumerators and Higher Order Functions. Since looping over all entries of a matrix or vector with direct access is inefficient, especially with a sparse storage layout, and working with the raw structures is non-trivial, both vectors and matrices provide specialized enumerators and higher order functions that understand the actual layout and can use it more efficiently.

I have a matrix m and a vector v.I would like to multiply first column of matrix m by the first element of vector v, and multiply the second column of matrix m by the second element of vector v, and so on.I can do it with the following code, but I am looking for a way which does not require the two transpose calls.