loss function

  1. M

    Leave-one-out error strictly decreasing when number of parameters is increased, when it should not be?

    People may or may not be able to help intuitively shed light on my problem. Maybe I haven't considered some aspects. I'm running a non-parametric (kernel) regularized least squares estimation on some binary training data to then predict probabilistic values for the non-training data. I have 9...
  2. T

    decision under loss function, discrete Bayes

    Hi guys, This is my first post here. I am currently enrolled in the Coursera Bayesian Statistics course from Duke University. While I've enjoyed the Statistics with R specialization so far, I think this course is not at the same level as the other ones. In one of the quizzes from the course...
  3. S

    Absolute Loss Function

    I am quite honestly at an "absolute loss" with this one... I know the answer can't be 2 yet I keep getting it.. any help is much appreciated. Question: A reinsurer decides to use a continuous uniform distribution on the interval (0,θ) to model a claim size X. She wishes to estimate θ on...