A prediction interval is an interval associated with a random variable yet to be observed (forecasting). A confidence interval is an interval associated with a parameter and is a …

Jul 31, 2016 · Is there any bootstrap technique available to compute prediction intervals for point predictions obtained e.g. from linear regression or other regression method (k-nearest …

Oct 19, 2015 · $\begingroup$ It sounds like you are assuming (a) the OP wants a Bayesian prediction interval and (b) is willing to adopt a Normal conjugate prior for the process. …

Apr 23, 2015 · This makes sense to me. We have lots of data on Fish K, but not a lot of data on Fish L, so we are more confident in our guesstimate about Fish K's true swimming speed. …

May 2, 2015 · $\begingroup$ Prediction intervals for the response would seem to be be pretty useless. Where you have modeled >95% in one of the two categories, your interval will be …

May 14, 2016 · Conformal prediction seems like a useful approach for quantifying the confidence in predictions on new data. I have only scratched the surface thus far and others are probably …

Prediction is the "guessing" of a future observation. Assuming this "guessing" is based on past data- this might be a case of estimation; such as the prediction of the height of the next person …

Mar 13, 2015 · Your second question is a bit trickier since loess.sd doesn't come with a prediction function, but you can hack it together by linearly interpolating the predicted means and SDs …

Feb 2, 2023 · The prediction intervals you are looking at are most likely representative of something like the posterior predictive distribution, which provides a distribution of possible …

Aug 1, 2018 · After trying several models I have managed to obtain a relatively good prediction using lasso regression. However, given the importance of the problem, I would like to have …