NMath Reference Guide

## PLS |

Class PLS1 performs a Partial Least Squares (PLS) regression calculation on a
set of predictive and one-dimensional response values. The result is used to
predict response variable values.

Inheritance Hierarchy

Syntax

The PLS1 type exposes the following members.

Constructors

Name | Description | |
---|---|---|

PLS1 | Constructs a PLS1 instance. The default calculator. | |

PLS1(IPLS1Calc) | Constructs a PLS1 instance that used the given calculator. | |

PLS1(DoubleMatrix, DoubleVector, Int32) | Constructs a PLS1 instance with the default PLS1 calculator and performs a PLS1 calculation on the given data. | |

PLS1(IPLS1Calc, DoubleMatrix, DoubleVector, Int32) | Constructs a PLS1 instance with the given PLS1 calculator and performs a PLS1 calculation on the given data. |

Properties

Name | Description | |
---|---|---|

Calculator | Gets and sets the calculator. | |

IsGood | Whether the most recent calculation was successful. | |

Message | Gets any message that may have been generated by the algorithm. For example, if the calculation was unsuccessful, the message should indicate the reason. | |

NumComponents | Gets and sets the number of predictor variable components to use in the PLS calculation. | |

PredictorMatrix | Gets the predictor matrix. | |

ResponseVector | Gets the response vector. |

Methods

Name | Description | |
---|---|---|

Calculate(DataFrame, DoubleVector, Int32) | Calculates the partial least squares fit. | |

Calculate(DoubleMatrix, DoubleVector, Int32) | Calculates the partial least squares fit. | |

Clone | Creates a deep copy of this PLS1. | |

HotellingsT2 | Calculaties Hotelling's T2 statistic for each sample. T2 can be viewed as the squared distance from a samples projection into the subspace to the centroid of the subspace, or, more simply, the variation of the sample point within the model. | |

HotellingsT2(DoubleVector) | Computes the Hotelling's T2 statistic for a new sample. | |

Predict(DoubleMatrix) | Predict the responses for a set of predictor values. | |

Predict(DoubleVector) | Calculates the predicted value of the response variable for the given value of the predictor variable. | |

QResiduals | Calculates the Q residuals for in sample in the model. The Q residual for a given sample is the distance between the sample and its projection in the subspace of the model. |

Fields

Name | Description | |
---|---|---|

DEFAULT_CALCULATOR | If no calculation object is specified during construction of PLS2 objects, this is the default calculator that will be used. |

See Also