# VN Multivariate Regression (INTERNAL CALL FOR VN.reg)

### Description

Called by `VN.reg`

for multivariate regression analysis.

### Usage

1 2 3 |

### Arguments

`B` |
Complete dataset of independent variables (IV) in matrix form. |

`y` |
Dependent variable (DV). |

`order` |
Controls the number of the |

`s.t.n` |
Signal to noise parameter, sets the threshold of |

`n.best` |
Sets the number of closest regression points to use in kernel weighting. Defaults to 1. Should be validated on hold-out set in conjunction with |

`type` |
Controls the partitioning in |

`point.est` |
Generates a fitted value of |

`plot` |
Generates a 3d scatter plot with regression points using plot3d |

`residual.plot` |
Generates a |

`location` |
Sets the location of the legend |

`precision` |
Increases speed of computation at the expense of precision. 2 settings offered: |

`text` |
If performing a text classification, set |

`noise.reduction` |
In low signal:noise situations, |

`norm` |
Normalizes regressors between 0 and 1 for multivariate regression when set to |

### Value

Returns the values: `"Fitted"`

for only the fitted values of the DV; `"regression.points"`

provides the points for each IV used in the regression equation for the given order of partitions; `"rhs.partitions"`

returns the partition points for each IV; `"partition"`

returns the DV, quadrant assigned to the observation and fitted value, and `"Point.est"`

for predicted values.

### Author(s)

Fred Viole, OVVO Financial Systems

### References

Viole, F. and Nawrocki, D. (2013) "Nonlinear Nonparametric Statistics: Using Partial Moments" http://amzn.com/1490523995