kNN_dist: k-nearest neighbours distance.
In nlhuong/buds: Bayesian Unidimensional Scaling (BUDS)
Description
Usage
Arguments
Value
Description
Compute average distance to k-nearest neighbours
for each data point from a dissimilarity matrix.
This approximates the data densities around
each data point.
Usage
1
Arguments
D
A dissimilarity matrix.
K
An integer indicating the number of points
to include in the neighbourhood. If not specified
one tenth of the total number of data points is used.
Value
A list with mean distances to k-nearest
neighbours and the associated variance of these
k-distances for each data point.
nlhuong/buds documentation built on May 17, 2019, 3:13 a.m.
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
Description Usage Arguments Value
Description
Compute average distance to k-nearest neighbours for each data point from a dissimilarity matrix. This approximates the data densities around each data point.
Usage
1 |
Arguments
D |
A dissimilarity matrix. |
K |
An integer indicating the number of points to include in the neighbourhood. If not specified one tenth of the total number of data points is used. |
Value
A list with mean distances to k-nearest neighbours and the associated variance of these k-distances for each data point.
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
Embedding an R snippet on your website
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.