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Statistical challenges of big brain network data

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  • Chung, Moo K.

Abstract

We explore the main characteristics of big brain network data that offer unique statistical challenges. The brain networks are biologically expected to be both sparse and hierarchical. Such unique characterizations put specific topological constraints onto statistical approaches and models we can use effectively. We explore the limitations of the current models used in the field and offer alternative approaches and explain new challenges.

Suggested Citation

  • Chung, Moo K., 2018. "Statistical challenges of big brain network data," Statistics & Probability Letters, Elsevier, vol. 136(C), pages 78-82.
    • Handle: RePEc:eee:stapro:v:136:y:2018:i:c:p:78-82
    DOI: 10.1016/j.spl.2018.02.020
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    Cited by:

    1. Bowman, Adrian W., 2018. "Big questions, informative data, excellent science," Statistics & Probability Letters, Elsevier, vol. 136(C), pages 34-36.
    2. Reid, Nancy, 2018. "Statistical science in the world of big data," Statistics & Probability Letters, Elsevier, vol. 136(C), pages 42-45.

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