Description Usage Arguments Details Author(s) Examples

Create a series of projection plots corresponding to a random tour through the data.

1 2 3 4 5 6 7 8 9 10 11 12 13 14 | ```
randomTour(object, ...)
## S4 method for signature 'ANY'
randomTour(object, ...)
## S4 method for signature 'matrix'
randomTour(object, ...)
## S4 method for signature 'flexclust'
randomTour(object, data=NULL, col=NULL, ...)
randomTourMatrix(x, directions=10,
steps=100, sec=4, sleep = sec/steps,
axiscol=2, axislab=colnames(x),
center=NULL, radius=1, minradius=0.01, asp=1,
...)
``` |

`object, x` |
A matrix or an object of class |

`data` |
Data to include in plot. |

`col` |
Plotting colors for data points. |

`directions` |
Integer value, how many different directions are toured. |

`steps` |
Integer, number of steps in each direction. |

`sec` |
Numerical, lower bound for the number of seconds each direction takes. |

`sleep` |
Numerical, sleep for as many seconds after each picture has been plotted. |

`axiscol` |
If not |

`axislab` |
Optional labels for the projected axes. |

`center` |
Center of the coordinate system to use in projected space. Default is the center of the plotting region. |

`radius` |
Relative size of the arrows. |

`minradius` |
Minimum radius of arrows to include. |

`asp, ...` |
Passed on to |

Two random locations are chosen, and data then projected onto
hyperplanes which are orthogonal to `step`

vectors interpolating
the two locations. The first two coordinates of the projected data are
plotted. If `directions`

is larger than one, then after the first
`steps`

plots one more random location is chosen, and the
procedure is repeated from the current position to the
new location, etc..

The whole procedure is similar to a grand tour, but no attempt is made
to optimize subsequent directions, `randomTour`

simply chooses a random
direction in each iteration. Use `rggobi`

for the real thing.

Obviously the function needs a reasonably fast computer and graphics
device to give a smooth impression, for `x11`

it may be
necessary to use `type="Xlib"`

rather than cairo.

Friedrich Leisch

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 | ```
if(interactive()){
par(ask=FALSE)
randomTour(iris[,1:4], axiscol=2:5)
randomTour(iris[,1:4], col=as.numeric(iris$Species), axiscol=4)
x <- matrix(runif(300), ncol=3)
x <- rbind(x, x+1, x+2)
cl <- cclust(x, k=3, save.data=TRUE)
randomTour(cl, center=0, axiscol="black")
## now use predicted cluster membership for new data as colors
randomTour(cl, center=0, axiscol="black",
data=matrix(rnorm(3000, mean=1, sd=2), ncol=3))
}
``` |

flexclust documentation built on May 2, 2019, 10:59 a.m.

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