Predictions of ridge regression in R
<p>I've been really stuck on this, hope anyone can help me! I have a dataset with 54 columns and I want to make predictions on a test set with ridge regression. </p>

<pre><code>nn &lt;-nrow(longley)
index &lt;- 1:nrow(longley)
testindex &lt;- sample(index, trunc(length(index)/3))
testset &lt;- longley[testindex,]
trainset &lt;-longley[-testindex,]
trainset1 &lt;- trainset[,-7]

# Fit the ridge regression model:

mod &lt;- lm.ridge(y ~., data = trainset, lambda = 0.661)

# Predict and evaluate it by using MAE function:

mae &lt;- function(model) {
  y = trainset$Employed  
  y.pred &lt;- predict(model, trainset)
  return(mean(abs(y-y.pred)))
}
</code></pre>

<p>When I do this I get the following error message:</p>

<pre><code>Error in UseMethod("predict") : 
  no applicable method for 'predict' applied to an object of class "ridgelm"
</code></pre>

<p>What could be another way to make predictions with ridge regression that works (also with evaluation metrics such as rsquared and MAE)? </p>