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文献信息
The primary aim of the journal is to publish original and high-quality articles that recognize statistical modelling as the general framework for the application of statistical ideas. Submissions must reflect important developments, extensions, and applications in statistical modelling. The journal also encourages submissions that describe scientifically interesting, complex or novel statistical modelling aspects from a wide diversity of disciplines, and submissions that embrace the diversity of applied statistical modelling.
Random EffectsLongitudinal DataMarkov Chain Monte CarloVariable SelectionQuantile RegressionEM AlgorithmCount DataGeneralized Linear ModelsModel SelectionMaximum LikelihoodMaximum Likelihood EstimationMixture ModelFinite MixtureMissing DataDirichlet ProcessStatistical ModelsSurvival AnalysisTime SeriesPoisson RegressionMixed Model
vol.25 (2025)
vol.24 (2024)
vol.23 (2023)
vol.22 (2022)
vol.21 (2021)
vol.20 (2020)
vol.19 (2019)
vol.18 (2018)
vol.17 (2017)
vol.16 (2016)
vol.15 (2015)
vol.14 (2014)
vol.13 (2013)
vol.12 (2012)
vol.11 (2011)
vol.10 (2010)
vol.9 (2009)
vol.8 (2008)
vol.7 (2007)
vol.6 (2006)
vol.5 (2005)
vol.4 (2004)
vol.3 (2003)
vol.2 (2002)
vol.1 (2001)