mult_mat: Multiply element-wise the rows or columns of a _matrix_ times...

In algoquant/HighFreq: High Frequency Time Series Management

Multiply element-wise the rows or columns of a matrix times a vector.

Description

Multiply element-wise the rows or columns of a matrix times a vector.

Usage

mult_mat(vectorv, matrixv, byrow = TRUE)

Arguments

vector	A numeric vector.
matrix	A numeric matrix.
byrow	A Boolean argument: if TRUE then multiply the rows of matrix by vector, otherwise multiply the columns (the default is byrow = TRUE.)

Details

The function mult_mat() multiplies element-wise the rows or columns of a matrix times a vector.

If byrow = TRUE (the default), then function mult_mat() multiplies the rows of the argument matrix times the argument vector. Otherwise it multiplies the columns of matrix.

In R, matrix multiplication is performed by columns. Performing multiplication by rows is often required, for example when multiplying asset returns by portfolio weights. But performing multiplication by rows requires explicit loops in R, or it requires matrix transpose. And both are slow.

The function mult_mat() uses RcppArmadillo C++ code, so when multiplying large matrix columns it's several times faster than vectorized R code, and it's even much faster compared to R when multiplying the matrix rows.

The function mult_mat() performs loops over the matrix rows and columns using the Armadillo operators each_row() and each_col(), instead of performing explicit for() loops (both methods are equally fast).

Value

A matrix equal to the product of the elements of matrix times vector, with the same dimensions as the argument matrix.

Examples

## Not run: 
# Create vector and matrix data
matrixv <- matrix(round(runif(25e4), 2), nc=5e2)
vectorv <- round(runif(5e2), 2)

# Multiply the matrix rows using R
matrixr <- t(vectorv*t(matrixv))
# Multiply the matrix rows using C++
matrixp <- HighFreq::mult_mat(vectorv, matrixv, byrow=TRUE)
all.equal(matrixr, matrixp)
# Compare the speed of Rcpp with R code
library(microbenchmark)
summary(microbenchmark(
    Rcpp=HighFreq::mult_mat(vectorv, matrixv, byrow=TRUE),
    Rcode=t(vectorv*t(matrixv)),
    times=10))[, c(1, 4, 5)]  # end microbenchmark summary
    
# Multiply the matrix columns using R
matrixr <- vectorv*matrixv
# Multiply the matrix columns using C++
matrixp <- HighFreq::mult_mat(vectorv, matrixv, byrow=FALSE)
all.equal(matrixr, matrixp)
# Compare the speed of Rcpp with R code
library(microbenchmark)
summary(microbenchmark(
    Rcpp=HighFreq::mult_mat(vectorv, matrixv, byrow=FALSE),
    Rcode=vectorv*matrixv,
    times=10))[, c(1, 4, 5)]  # end microbenchmark summary

## End(Not run)

algoquant/HighFreq documentation built on Oct. 26, 2024, 9:20 p.m.