In statistical inference, there are many fundamental statistical principles, such as likelihood principle and repeated sampling principle. I am wondering whether there are any other principles? And what's the meaning of these principles? What's the difference between these principles, especially between likelihood principle and repeated sampling principle?
From the book "Likelihood Methods in Statistics" by T.A.Severini, "the repeated sampling principle states that statistical procedures should be evaluated on the basis of their behavior in hypothetical repetitions of the experiment that generated the original data. Of course, there is considerable arbitrariness in how this principle is interpreted, in particular, in how the hypothetical repetitions are defined. The basic idea however, which is simply that a given statistical procedure should be evaluated based on how it would perform inf adopted for routine use, is certainly reasonable."