# NMath User's Guide

48.1 Computing a PLS Regression (.NET, C#, CSharp, VB, Visual Basic, F#)

NMath Stats provides two classes for performing partial least squares (PLS) regression, PLS1 and PLS2:

PLS1 is used when the responses, Y, in the model Y=XB+E consist of a single variable. In this case Y is a vector containing the n response values.

PLS2 is used when the responses are multivariate. In this case Y is a matrix composed of n rows with each row containing the m response variable values.

Computing a PLS regression is accomplished by simply constructing a PLS1 or PLS2 instance. The basic parameters are:

the matrix of predictor variables values

the response variable values (a vector for PLS1 and a matrix for PLS2)

an integer specifying the number of factors or components

For example:

Code Example – C# partial least squares (PLS)

```DoubleMatrix A = ...
```
```DoubleVector y = = ...
```
```int numComponents = 3;

```

```var pls = new PLS1( A, y, numComponents );
```

Code Example – VB partial least squares (PLS)

```Dim A As DoubleMatrix = ...
```
```Dim Y As DoubleVector = ...
```
```Dim NumComponents As Integer = 3

```

```Dim PLS As New PLS1(A, Y, NumComponents)
```

You can also invoke the Calculate() function on PLS1 or PLS2 to calculate a regression on an existing instance:

Code Example – C# partial least squares (PLS)

```pls.Calculate( A, y, numComponents );
```

Code Example – VB partial least squares (PLS)

```PLS.Calculate(A, Y, NumComponents)
```

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