# ab.dist: Distance Functions for nearest neighbours In MuViCP: MultiClass Visualizable Classification using Combination of Projections

## Description

These functions compute Absolute (`ab.dist`), Euclidean (`eu.dist`) or Mahalanobis (`mh.dist`) distances between two points. The variant functions (`*.matY`), accomplish the same task, but between a point on the one hand, and every point specified as rows of a matrix on the other.

## Usage

 ```1 2 3 4 5 6``` ```ab.dist(x, y) eu.dist(x, y) mh.dist(x, y, A) ab.dist.matY(x, Y) eu.dist.matY(x, Y) mh.dist.matY(x, Y, A) ```

## Arguments

 `x` The vector (point) from which distance is sought. `y` The vector (point) to which distance is sought. `Y` A set of points, specified as rows of a matrix, to which distances are sought. `A` The inverse matrix to use for the Mahalanobis distance.

## Details

These functions are used internally to decide how the nearest neighbours shall be calculated; the user need not call any of these functions directly. Rather, the choice of distance is specified as a string ('euclidean' or 'absolute' or 'mahal').

## Value

Either a single number for the distance, or a vector of distances, corresponding to each row of `Y`.

Mohit Dayal

get.NN

## Examples

 ``` 1 2 3 4 5 6 7 8 9 10 11``` ```x <- c(1,2) y <- c(0,3) mu <- c(1,3) Sigma <- rbind(c(1,0.2),c(0.2,1)) Y <- MASS::mvrnorm(20, mu = mu, Sigma = Sigma) ab.dist(x,y) eu.dist(x,y) mh.dist(x,y,Sigma) ab.dist.matY(x,Y) eu.dist.matY(x,Y) mh.dist.matY(x,Y,Sigma) ```

### Example output

```Warning message:
no DISPLAY variable so Tk is not available
[1] 2
[1] 2
[,1]
[1,]  2.5
[1] 2.2284123 2.2378047 1.1964977 0.9432708 1.8059748 2.3870570 1.6303574
[8] 2.5202570 0.7032441 2.7113114 1.7023114 2.7414863 2.1732236 1.5718124
[15] 2.3493425 3.6400791 3.2157438 1.9691935 1.5027929 1.9431484
[1]  2.7771813  3.4846290  0.9536751  0.4452661  1.9816146  3.2541393
[7]  1.4036025  3.2927857  0.2529855  3.9744493  1.4643519  4.1670429
[13]  2.3624025  1.8209725  2.8782691 11.6991019  5.3710730  1.9578152
[19]  1.4690891  2.6461325
[1]  3.3488639  3.9471429  0.8938424  0.3712160  1.7975297  2.8805821
[7]  1.7234324  4.0672579  0.2132002  3.4365597  1.2267182  5.0383164
[13]  2.9526064  2.0321842  3.5484347 11.8634240  4.5594646  2.4393717
[19]  1.6947381  2.5210353
```

MuViCP documentation built on May 1, 2019, 7:56 p.m.