human: Given a hyperedge-centered hypergraph: <hypergraph>, where the center hyperedge is induced by one source paper and its member nodes are the cited papers.

Details of the hypergraph:
Center hyperedge (induced by source paper "arguing practical significance in software engineering using bayesian data analysis"):
  Abstract: This paper provides a case for using Bayesian data analysis (BDA) to make more grounded claims regarding practical significance of software engineering research. #R##N#We show that using BDA, here combined with cumulative prospect theory (CPT), is appropriate when a researcher or practitioner wants to make clearer connections between statistical findings and practical significance in empirical software engineering research. To illustrate our point we provide an example case using previously published data. We build a multilevel Bayesian model for this data, for which we compare the out of sample predictive power. Finally, we use our model to make out of sample predictions while, ultimately, connecting this to practical significance using CPT. #R##N#Throughout the case that we present, we argue that a Bayesian approach is a natural, theoretically well-grounded, practical work-flow for data analysis in empirical software engineering. By including prior beliefs, assuming parameters are drawn from a probability distribution, assuming the true value is a random variable for uncertainty intervals, using counter-factual plots for sanity checks, conducting predictive posterior checks, and out of sample predictions, we will better understand the phenomenon being studied, while at the same time avoid the obsession with p-values.

Includes members:
  Member "bayesian hierarchical modelling for tailoring metric thresholds":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "bayesian data analysis in empirical software engineering research")
  Member "evolution of statistical analysis in empirical software engineering research current state and steps forward":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "cross dataset design discussion mining")
  Member "bayesian statistics in software engineering practical guide and case studies":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "bayesian data analysis in empirical software engineering research")

Question: Please tell me which class the source paper belongs to. The 40 classes are: cs.NA(Numerical Analysis), cs.MM(Multimedia), cs.LO(Logic in Computer Science), cs.CY(Computers and Society), cs.CR(Cryptography and Security), cs.DC(Distributed, Parallel, and Cluster Computing), cs.HC(Human-Computer Interaction), cs.CE(Computational Engineering, Finance, and Science), cs.NI(Networking and Internet Architecture), cs.CC(Computational Complexity), cs.AI(Artificial Intelligence), cs.MA(Multiagent Systems), cs.GL(General Literature), cs.NE(Neural and Evolutionary Computing), cs.SC(Symbolic Computation), cs.AR(Hardware Architecture), cs.CV(Computer Vision and Pattern Recognition), cs.GR(Graphics), cs.ET(Emerging Technologies), cs.SY(Systems and Control), cs.CG(Computational Geometry), cs.OH(Other Computer Science), cs.PL(Programming Languages), cs.SE(Software Engineering), cs.LG(Machine Learning), cs.SD(Sound), cs.SI(Social and Information Networks), cs.RO(Robotics), cs.IT(Information Theory), cs.PF(Performance), cs.CL(Computation and Language), cs.IR(Information Retrieval), cs.MS(Mathematical Software), cs.FL(Formal Languages and Automata Theory), cs.DS(Data Structures and Algorithms), cs.OS(Operating Systems), cs.GT(Computer Science and Game Theory), cs.DB(Databases), cs.DL(Digital Libraries), cs.DM(Discrete Mathematics). Directly output the class name.

gpt: cs.SE(Software Engineering)