# matrix_tau: Compute a matrix of differences given two vectors. In svdataman/sour: Cross-correlation of time series (which may be unevenly sampled)

## Description

`matrix_tau` returns a matrix of differences between two vectors.

## Usage

 `1` ```matrix_tau(x, y) ```

## Arguments

 `x` vector 1 `y` vector 2 (default to vector 1 if not specified)

## Details

Given two vectors - `x` (length `M`) and `y` (length `N`) - as input, return the `N*M` matrix of differences `result[i,j] = x[i] - y[j]`.

## Value

`N*M` array of differences, `result[i,j] = x[i] - y[j]`

## Notes

Note that in the special case that `x=y` we have a square symmetric matrix: `result[i,j] = result[j,i]`. In the even more special case that the two vectors are evenly spaced (`x[i] = y[i] = i * delta + const`) then we have a circulant matrix; the `j`th column `result[,j]` is the `(j-1)`th cyclic permutation of the first column. This matrix is symmetric, Toeplitz and circulant.

## Examples

 ```1 2``` ```result <- matrix_tau(c(1,2,3), c(2,3,4,5,6)) print(result) ```

svdataman/sour documentation built on April 6, 2018, 11:13 a.m.