The PLS1NipalsAlgorithm type exposes the following members.
Constructors
| Name | Description | |
|---|---|---|
 | PLS1NipalsAlgorithm |
Constructs an instance of the PLS1NipalsAlgorithm class.
|
Methods
| Name | Description | |
|---|---|---|
| Calculate |
Calculates a partial least squares from the given data and number of
components.
(Overrides IPLS1Calc..::.Calculate(DoubleMatrix, DoubleVector, Int32).) |
| Clone |
Creates a deep copy of this PLS1NipalsAlgorithm.
(Overrides IPLS1Calc..::.Clone()()().) |
| Equals | (Inherited from Object.) |
| GetHashCode |
Serves as a hash function for a particular type.
(Inherited from Object.) |
| GetType |
Gets the Type of the current instance.
(Inherited from Object.) |
| 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.
(Inherited from IPLS1Calc.) |
| OnDeserialized |
Sets most of the attributes only if isGood_
|
| OnSerializing |
Conditionally sets most of the values for serialization only if isGood_
|
| Predict | Overloaded. |
| 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.
(Overrides IPLS1Calc..::.QResiduals()()().) |
| ToString | (Inherited from Object.) |
Properties
| Name | Description | |
|---|---|---|
 | IsGood |
Whether the most recent calculation was successful.
(Overrides IPLS1Calc..::.IsGood.) |
| Loadings |
Gets the loadings matrix for PredictorMatrix. The loadings matrix
is described in the class summary.
(Overrides IPLS1Calc..::.Loadings.) |
| Message |
Gets any message that may have been generated by the algorithm. For example,
if the calculation is unsuccessful, the message indicates the reason.
(Overrides IPLS1Calc..::.Message.) |
| PredictorMean |
Gets the vector of means for the predictor variables.
|
| RegressionVector |
Gets the vector of regression, r, which can be used for making
predictions as follows:
Let ybar and xbar be the means of the response and
predictor variables, respectively, used to create the model. Then
the predicted response, yhat, for a predictor vector, z
is given by the formula
|
| ResponseMean |
Gets the vector of means for the response variables.
|
| ResponseWeights |
Gets the vector of response weights. The ith element of this vector
corresponds to the regression coefficient calculated by ordinary linear
regression of the response vector on the ith score vector.
|
| Scores |
Gets the scores matrix for PredictorMatrix. The scores matrix
is described in the class summary.
(Overrides IPLS1Calc..::.Scores.) |
| Weights |
Returns the matrix of weights computed by the algorithm.
|
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