# distance: Calculate the squared Euclidean distance between pairs of... In laGP: Local Approximate Gaussian Process Regression

## Description

Calculate the squared Euclidean distance between pairs of points and return a distance matrix

## Usage

 `1` ```distance(X1, X2 = NULL) ```

## Arguments

 `X1` a `matrix` or `data.frame` containing real-valued numbers `X2` an optional `matrix` or `data.frame` containing real-valued numbers; must have `ncol(X2) = ncol(X1)`

## Details

If `X2 = NULL` distances between `X1` and itself are calculated, resulting in an `nrow(X1)`-by-`nrow(X1)` distance matrix. Otherwise the result is `nrow(X1)`-by-`nrow(X2)` and contains distances between `X1` and `X2`.

Calling `distance(X)` is the same as `distance(X,X)`

## Value

The output is a `matrix`, whose dimensions are described in the Details section above

## Author(s)

Robert B. Gramacy [email protected]

`darg`

## Examples

 ```1 2 3 4 5 6 7 8``` ```x <- seq(-2, 2, length=11) X <- as.matrix(expand.grid(x, x)) ## predictive grid with NN=400 xx <- seq(-1.9, 1.9, length=20) XX <- as.matrix(expand.grid(xx, xx)) D <- distance(X) DD <- distance(X, XX) ```

### Example output

```
```

laGP documentation built on Dec. 8, 2018, 1:04 a.m.