View source: R/NNCTFunctions.R

ipd.mat | R Documentation |

This function computes and returns the distance matrix computed by using the specified distance measure to
compute the distances between the rows of the set of points `x`

and `y`

using the
`dist`

function in the `stats`

package of the standard R distribution.
If `y`

is provided (default=`NULL`

) it yields a matrix of distances between the rows of `x`

and
rows of `y`

. Otherwise, it provides a square matrix with i,j-th entry being the distance between row
*i* and row *j* of `x`

.
This function is different from the `dist`

function in the `stats`

package.
`dist`

returns the distance matrix in a lower triangular form, and `ipd.mat`

returns in a full matrix.
... are for further arguments, such as `method`

and `p`

, passed to the `dist`

function.

ipd.mat(x, y = NULL, ...)

`x` |
A set of points in matrix or data frame form where points correspond to the rows. |

`y` |
A set of points in matrix or data frame form where points correspond to the rows (default= |

`...` |
Additional parameters to be passed on the |

A distance matrix whose i,j-th entry is the distance between row *i* of `x`

and row *j* of `y`

if `y`

is provided,
otherwise i,j-th entry is the distance between rows *i* and *j* of `x`

.

Elvan Ceyhan

`dist`

, `ipd.mat.euc`

, `dist.std.data`

#3D data points n<-3 X<-matrix(runif(3*n),ncol=3) mtd<-"euclidean" #try also "maximum", "manhattan", "canberra", "binary" ipd.mat(X,method=mtd) ipd.mat(X,method="minkowski",p=6) n<-5 Y<-matrix(runif(3*n),ncol=3) ipd.mat(X,Y,method=mtd) ipd.mat(X[1,],Y,method=mtd) ipd.mat(c(.1,.2,.3),Y,method=mtd) ipd.mat(X[1,],Y[3,],method=mtd) #1D data points X<-as.matrix(runif(3)) # need to be entered as a matrix with one column #(i.e., a column vector), hence X<-runif(3) would not work ipd.mat(X) Y<-as.matrix(runif(5)) ipd.mat(X,Y) ipd.mat(X[1,],Y) ipd.mat(X[1,],Y[3,])

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