human: Given a hyperedge-centered hypergraph: <hypergraph>, where the center hyperedge groups papers that share a common citing paper.

Details of the hypergraph:
Center hyperedge (induced by source paper "Estimating Bayes Factors via Posterior Simulation with the Laplace-Metropolis Estimator"):
  Abstract: The key quantity needed for Bayesian hypothesis testing and model selection is the marginal likelihood for a model, also known as the integrated likelihood, or the marginal probability of the data. In this paper we describe a way to use posterior simulation output to estimate marginal likelihoods. We describe the basic Laplace-Metropolis estimator for models without random effects. For models with random effects the compound Laplace-Metropolis estimator is introduced. This estimator is applied to data from the World Fertility Survey and shown to give accurate results. Batching of simulation output is used to assess the uncertainty involved in using the compound Laplace-Metropolis estimator. The method allows us to test for the effects of independent variables in a random effects model, and also to test for the presence of the random effects.

Includes members:
  Member "Approximate Bayes Factors and Accounting for Model Uncertainty in Generalized Linear Models":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "Formal Rules for Selecting Prior Distributions: A Review and Annotated Bibliography")
  Member "Inference in Model-Based Cluster Analysis":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "Detecting Features in Spatial Point Processes with Clutter via Model-Based Clustering")

Question: Please tell me which class the citing paper (i.e., the source paper of the center hyperedge) belongs to. The 7 classes are: Neural_Networks, Reinforcement_Learning, Probabilistic_Methods, Theory, Genetic_Algorithms, Case_Based, Rule_Learning. Directly output the class name.

gpt: Probabilistic_Methods