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文献信息
Journal of Applied Statistics is a world-leading journal which provides a forum for communication among statisticians and practitioners for judicious application of statistical principles and innovations of statistical methodology motivated by current and important real-world examples across a wide range of disciplines, including, but not limited to:
Maximum LikelihoodVariable SelectionMonte Carlo SimulationMaximum Likelihood EstimationLongitudinal DataMarkov Chain Monte CarloData SetConfidence IntervalsEM AlgorithmNormal DistributionTime SeriesSample SizeTest StatisticBayesian InferenceRegression ModelRandom EffectsCount DataLinear RegressionWEIBULL DistributionModel Selection
vol.53 (2026)
vol.52 (2025)
vol.51 (2024)
vol.50 (2023)
vol.49 (2022)
vol.48 (2021)
vol.47 (2020)
vol.46 (2019)
vol.45 (2018)
vol.44 (2017)
vol.43 (2016)
vol.42 (2015)
vol.41 (2014)
vol.40 (2013)
vol.39 (2012)
vol.38 (2011)
vol.37 (2010)
vol.36 (2009)
vol.35 (2008)
vol.34 (2007)
vol.33 (2006)
vol.32 (2005)
vol.31 (2004)
vol.30 (2003)
vol.29 (2002)
vol.28 (2001)
vol.27 (2000)
vol.26 (1999)
vol.25 (1998)
vol.24 (1997)
vol.23 (1996)
vol.22 (1995)
vol.20 (1993)