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文献信息
The aim of the Japanese Journal of Statistics and Data Science (JJSD) is to publish original articles concerning statistical theories and novel applications in diverse research fields related to statistics and data science. It also sometimes publishes review and expository articles on specific topics, which are expected to bring valuable information for researchers interested in the fields selected. The journal also contributes to broadening the coverage of statistics and data analysis in publishing articles based on innovative ideas. All articles are refereed by experts.
Data ScienceVariable SelectionMaximum LikelihoodAsymptotic NormalityMaximum Likelihood EstimationFrequency DataLikelihood FunctionMarkov Chain Monte CarloMean VectorNormal DistributionParameter EstimationData AnalysisEstimatorMaximum Likelihood EstimatorSurvival AnalysisSmall Area EstimationCovariance MatrixRobust EstimationMonte Carlo SimulationModel Selection
vol.8 (2025)
vol.7 (2024)
vol.6 (2023)
vol.5 (2022)
vol.4 (2021)
vol.3 (2020)
vol.2 (2019)
vol.1 (2018)