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 "Bayesian Forecasting of Multinomial Time Series through Conditionally Gaussian Dynamic Models"):
  Abstract: Claudia Cargnoni is with the Dipartimento Statistico, Universita di Firenze, 50100 Firenze, Italy. Peter Muller is Assistant Professor, and Mike West is Professor, in the Institute of Statistics and Decision Sciences at Duke University, Durham NC 27708-0251. Research of Cargnoni was performed while visiting ISDS during 1995. Muller and West were partially supported by NSF under grant DMS-9305699.

Includes members:
  Member "BAYESIAN STATISTICS 6, pp. 000--000  Exact sampling for Bayesian inference: towards general purpose algorithms":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "An Approach to Diagnosing Total Variation Convergence of MCMC Algorithms")
  Member "Change Point and Change Curve Modeling in Stochastic Processes and Spatial Statistics":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "Approximate Bayes Factors and Accounting for Model Uncertainty in Generalized Linear Models")
  Member "On Sequential Simulation-Based Methods for Bayesian Filtering":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "FILTERING VIA SIMULATION: AUXILIARY PARTICLE FILTERS")
  Member "Analysis of hospital quality monitors using hierarchical time series models":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "STUDIES OF QUALITY MONITOR TIME SERIES: THE V.A. HOSPITAL SYSTEM build on foundational contributions in")
  Member "Priors and Component Structures in Autoregressive Time Series Models":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "Studies of Neurological Transmission Analysis using Hierarchical Bayesian Mixture Models")
  Member "FILTERING VIA SIMULATION: AUXILIARY PARTICLE FILTERS":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "On Sequential Simulation-Based Methods for Bayesian Filtering")
  Member "Exploratory Modelling of Multiple Non-Stationary Time Series: Latent Process Structure and Decompositions":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "Modelling and robustness issues in Bayesian time series analysis")
  Member "BAYESIAN TIME SERIES: Models and Computations for the Analysis of Time Series in the Physical Sciences":
    also connected through other hyperedges:
      - Hyperedge HE-8 (induced by source paper "Modelling and robustness issues in Bayesian time series analysis")

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