Description Usage Arguments Details Value Author(s) References See Also Examples

View source: R/interactive2D.R

Uses `tkrplot`

to create a GUI for two-class classification
in two dimensions using the smoothed log-concave maximum likelihood estimates

1 | ```
interactive2D(data, cl)
``` |

`data` |
Data in |

`cl` |
factor of true classifications of the data set |

This function uses `tkrplot`

to create a GUI for two-class classification
in two dimensions using the smoothed log-concave maximum likelihood estimates. The construction of the
classifier is standard, and can be found in Chen and Samworth (2011). The slider controls the risk
ratio of two classes (equals one by default), which provides a way of demonstrating how the decision boundaries
change as the ratio varies. Observations from different classes are plotted in red and green respectively.

A GUI with a slider

Yining Chen

Madeleine Cule

Robert B. Gramacy

Richard Samworth

Chen, Y. and Samworth, R. J. (2013)
*Smoothed log-concave maximum likelihood estimation with applications*
Statist. Sinica, 23, 1373-1398. http://arxiv.org/abs/1102.1191v4

Cule, M. L., Samworth, R. J., and Stewart, M. I. (2010)
*Maximum likelihood estimation of a log-concave density*,
Journal of the Royal Statistical Society, Series B, 72(5) p.545-607.

1 2 3 4 5 6 7 8 9 10 | ```
## Simple bivariate normal data
## only works interactively, not run as a test example here
# set.seed( 1 )
# n = 15
# d = 2
# props=c( 0.6, 0.4 )
# x <- matrix( rnorm( n*d ), ncol = d )
# shiftvec <- ifelse( runif( n ) > props[ 1 ], 0, 1)
# x[,1] <- x[,1] + shiftvec
# interactive2D( x, shiftvec )
``` |

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