A statistical hypothesis test is a method of statistical inference. Probabilities are not assigned to parameters or hypotheses in frequentist inference. SUTVA violation makes causal inference more difficult. The conclusion of a statistical inference is a statistical proposition. Comparing statistical models is fundamental for much of statistical inference. This percentile is theoretical and is derived using methods of statistical inference. However, this does not make "causal inference" impossible. Formal logic is concerned with such issues as validity, truth, inference, argumentation and proof. Isotonic regression has applications in statistical inference. This leads Hume to the third branch of causal inference, Belief. This can be enough for basic statistical inference (e.g., hypothesis testing, confidence intervals). Efficient algorithms exist that perform inference and learning. Gibbs sampling is commonly used as a means of statistical inference, especially Bayesian inference. Such methods are used in Solomonoff's theory of inductive inference. See material implication (rule of inference).