Lecture 4 Flashcards
Reflect on the following opinion if d > n
Reflect on the following opinion if d > n
Reflect on the following opinion if d > n
Reflect on the following opinion if d > n
Reflect on the following opinion if d > n
Does the SPE help making decisions on the best model if the estimation method is non-unique? Please explain your answer
What is the assumption that is commonly made when d > n?
What are the centering and normalizing conditions? (there are three)
How can the centering and normalizing conditions be achieved?
What are the two advantages of using the centering and normalizing conditions?
2nd point: The penalty form of the LASSO also explains why we scale the data (see above)
before we estimate using the LASSO. If covariate x1i measures distance to
university in meters and x2i measures distance to the beach in kilometres they
would be penalized differently because of the different units used. Which does not
make sense.
What is the LASSO model? Why should you include an intercept?
Explain why Lasso is better than an other method with a different norm.
(I believe that this is a complicated way of saying that some values tend to be set to zero)
What is the alternative method of defining Lasso in the Lagrange form?
Why does a Lasso not have to be unique?
What is the Lasso for orthogonal design theorem? What is this theorem sometimes also called?
What is the Lasso Linear model theorem?
What is the Lasso Linear model continuous regressors theorem?
