A Bayesian graphical framework with static, autoregressive, and hidden-Markov variants is applied to 76ers player-game data; the autoregressive variant wins on WAIC and supports player-level predictive inference.
Wiley Interdisciplinary Reviews: Computational Statistics , volume=
1 Pith paper cite this work. Polarity classification is still indexing.
1
Pith paper citing it
fields
stat.AP 1years
2026 1verdicts
CONDITIONAL 1representative citing papers
citing papers explorer
-
Longitudinal Bayesian networks for assessing team performance in the National Basketball Association
A Bayesian graphical framework with static, autoregressive, and hidden-Markov variants is applied to 76ers player-game data; the autoregressive variant wins on WAIC and supports player-level predictive inference.