A plot of the regularised regression coefficients is shown.
Usage
ridge.plot(y, x, lambda = seq(0, 5, by = 0.1) )
Arguments
y
A numeric vector containing the values of the target variable. If the values are proportions or percentages,
i.e. strictly within 0 and 1 they are mapped into R using the logit transformation. In any case, they must be continuous only.
x
A numeric matrix containing the continuous variables. Rows are samples and columns are features.
lambda
A grid of values of the regularisation parameter \(\lambda\).
Value
A plot with the values of the coefficients as a function of \(\lambda\).
Details
For every value of \(\lambda\) the coefficients are obtained. They are plotted versus the \(\lambda\) values.
References
Hoerl A.E. and R.W. Kennard (1970). Ridge regression: Biased estimation for nonorthogonal problems. Technometrics, 12(1): 55-67.
Brown P. J. (1994). Measurement, Regression and Calibration. Oxford Science Publications.