Zobrazeno 1 - 10
of 16
pro vyhledávání: '"Hou‐Cheng Yang"'
Publikováno v:
Geosciences, Vol 9, Iss 4, p 169 (2019)
Generalized linear models are routinely used in many environment statistics problems such as earthquake magnitudes prediction. Hu et al. proposed Pareto regression with spatial random effects for earthquake magnitudes. In this paper, we propose Bayes
Externí odkaz:
https://doaj.org/article/385579769b044c7293ce5fab47642574
Publikováno v:
Journal of Data Science. Jan2023, Vol. 21 Issue 1, p68-86. 19p.
Autor:
Hou-Cheng Yang1 hy15e@my.fsu.edu, Bradley, Jonathan R.1
Publikováno v:
Journal of Data Science. Jul2022, Vol. 20 Issue 3, p325-337. 13p.
Publikováno v:
Journal of Data Science. :68-86
Understanding shooting patterns among different players is a fundamental problem in basketball game analyses. In this paper, we quantify the shooting pattern via the field goal attempts and percentages over twelve non-overlapping regions around the f
Publikováno v:
Canadian Journal of Statistics. 51:157-172
Autor:
Hou-Cheng Yang, Jonathan R. Bradley
Publikováno v:
Journal of Data Science. :325-337
We propose a method of spatial prediction using count data that can be reasonably modeled assuming the Conway-Maxwell Poisson distribution (COM-Poisson). The COM-Poisson model is a two parameter generalization of the Poisson distribution that allows
Publikováno v:
Journal of Data Science. Apr2021, Vol. 19 Issue 2, p203-205. 3p.
Publikováno v:
Journal of Data Science. :203-205
Publikováno v:
Stat. 10
In this paper, we develop a group learning approach to analyze the underlying heterogeneity structure of shot selection among professional basketball players in the NBA. We propose a mixture of finite mixtures (MFM) model to capture the heterogeneity
In this paper, we propose a Susceptible–Infected–Removal (SIR) model with time fused coefficients. In particular, our proposed model discovers the underlying time homogeneity pattern for the SIR model's transmission rate and removal rate via Baye
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::13e73cfadd291c62b60ad8b8ed17baee