Leave One Out Prediction Model
“In the model development, the “leave-one-out” prediction is a way of cross-validation, calculated as below:
1. First of all, after a model is developed, each observation used in the model development is removed in turn and then the model is refitted with the remaining observations
2. The out-of-sample prediction for the refitted model is calculated with the removed observation one by one to assemble the LOO, e.g. leave-one-out predicted values for the whole model development sample.
from Yet Another Statistics Blog