Bayesian hierarchical models for the prediction of volleyball results

Andrea Gabrio

doi:10.1080/02664763.2020.1723506

Bayesian hierarchical models for the prediction of volleyball results

Andrea Gabrio^*

^*Corresponding author for this work

Research output: Contribution to journal › Article › Academic › peer-review

2 Citations (Web of Science)

Original language	English
Pages (from-to)	301-321
Number of pages	21
Journal	Journal of Applied Statistics
Volume	48
Issue number	2
DOIs	https://doi.org/10.1080/02664763.2020.1723506
Publication status	Published - 25 Jan 2021
Externally published	Yes

Keywords

Bayesian statistics
volleyball
poisson distribution
hierarchical models
CROSS-VALIDATION
ASYMPTOTIC EQUIVALENCE

Access to Document

10.1080/02664763.2020.1723506

Cite this

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title = "Bayesian hierarchical models for the prediction of volleyball results",

keywords = "Bayesian statistics, volleyball, poisson distribution, hierarchical models, CROSS-VALIDATION, ASYMPTOTIC EQUIVALENCE",

author = "Andrea Gabrio",

year = "2021",

month = jan,

day = "25",

doi = "10.1080/02664763.2020.1723506",

language = "English",

volume = "48",

pages = "301--321",

journal = "Journal of Applied Statistics",

issn = "0266-4763",

publisher = "Routledge/Taylor & Francis Group",

number = "2",

}

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T1 - Bayesian hierarchical models for the prediction of volleyball results

AU - Gabrio, Andrea

PY - 2021/1/25

Y1 - 2021/1/25

KW - Bayesian statistics

KW - volleyball

KW - poisson distribution

KW - hierarchical models

KW - CROSS-VALIDATION

KW - ASYMPTOTIC EQUIVALENCE

U2 - 10.1080/02664763.2020.1723506

DO - 10.1080/02664763.2020.1723506

M3 - Article

VL - 48

SP - 301

EP - 321

JO - Journal of Applied Statistics

JF - Journal of Applied Statistics

SN - 0266-4763

IS - 2

ER -