# Ridge

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### Purpose

Ridge regression by the Hoerl-Kennard-Baldwin method.

### Synopsis

- [b,theta] = ridge(x,y,thetamax,divs,tf)

### Description

RIDGE creates a ridge regression model, using a matrix containing the values of multiple predictor variables for a set of samples (x-block) `x`, and a vector containing the values of a single predictor variable for the same set of samples (y-block) `y`.

#### Inputs

**x**= matrix of input data for the predictor variables**y**= vector of input data for the predicted variable**thetamax**= the maximum value of the ridge parameter`theta`to consider (`thetamax`> 0).**divs**= the number of values of the ridge parameter between 0 and**thetamax**to be used for calculating the regression vector shown in the plots

**Note:** In most instances the optimum ridge parameter will be less than 0.1, often as low as 0.01. A good starting guess when working with the method is to specify thetamax = 0.1 with divs = 20.

#### Optional Inputs

**tf**= text flag input; allows the user to place the labels on the plot with the mouse when it is set to 1

#### Outputs

**b**= final regression vector, corresponding to the best guess value for the ridge parameter**theta****theta**= best-guess value of the ridge parameter by the Hoerl-Kennard method