Description Usage Arguments Value Examples

Create three-dimensional, interactive plotly graphics for exploration and diagnostics.

1 2 | ```
threewise_plot(x, y, type = "pca", pair_x = 1, pair_y = 2, pair_z = 3,
rank = "full", k = 0, point_size = 2.5)
``` |

`x` |
data frame or matrix of predictor variables |

`y` |
data frame or matrix of response variables |

`type` |
type of reduced-rank regression model to fit. |

`pair_x` |
variable to be plotted on the |

`pair_y` |
variable to be plotted on the |

`pair_z` |
variable to be plotted on the |

`rank` |
rank of coefficient matrix. |

`k` |
small constant added to diagonal of covariance matrices to make inversion easier. |

`point_size` |
size of points in scatter plot. |

three-dimensional plot. If `type = "pca"`

returns three principal components scores - defaulted to the first three - against each other.
If `type = "cva"`

returns three-dimensional plot of residuals. If `type = "lda"`

returns three-dimensional plot of three linear discriminant scores plotted against each other.

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 | ```
## Not run:
data(pendigits)
digits_features <- pendigits[, -35:-36]
threewise_plot(digits_features, digits_class, type = "pca", k = 0.0001)
library(dplyr)
data(COMBO17)
galaxy <- as_data_frame(COMBO17)
galaxy <- select(galaxy, -starts_with("e."), -Nr, -UFS:-IFD)
galaxy <- na.omit(galaxy)
galaxy_x <- select(galaxy, -Rmag:-chi2red)
galaxy_y <- select(galaxy, Rmag:chi2red)
threewise_plot(galaxy_x, galaxy_y, type = "cva")
data(iris)
iris_x <- iris[,1:4]
iris_y <- iris[5]
threewise_plot(iris_x, iris_y, type = "lda")
## End(Not run)
``` |

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