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The Journal of the Royal Statistical Society, Series B (Statistical Methodology) aims to publish high quality papers on the methodological aspects of statistics and data science more broadly. Papers should contribute to the understanding of statistical methodology and/or develop and improve statistical methods; any mathematical theory should be directed towards these aims. Many papers published in Series B present new methods of collecting or analysing data, with associated theory, an indication of the scope of application, and a real example. Also considered are comparisons, critical evaluations and new applications of existing methods, contributions to probability theory which have a clear practical bearing, statistical computation or simulation where original methodology is involved, and original contributions to the foundations of statistical science. A paper, even if correct and well presented, is likely to be rejected if it only presents straightforward special cases of previously published work, if it is of mathematical interest only, if it is too long in relation to the importance of the new material that it contains, or if it is dominated by computations or simulations of a routine nature.
Markov Chain Monte Carlo MethodsVariable SelectionCausal InferenceStatistical InferenceNonparametric RegressionModel SelectionConfidence IntervalsFalse Discovery RateTime SeriesMarkov Chain Monte CarloBayesian InferenceGeneralized Linear ModelsRandom VariablesMaximum Likelihood EstimationFunctional Data AnalysisMaximum LikelihoodAsymptotic NormalityLongitudinal DataMultiple TestingDimension Reduction
The Journal of the Royal Statistical Society, Series B (Statistical Methodology) aims to publish high quality papers on the methodological aspects of statistics and data science more broadly. Papers should contribute to the understanding of statistical methodology and/or develop and improve statistical methods; any mathematical theory should be directed towards these aims. Many papers published in Series B present new methods of collecting or analysing data, with associated theory, an indication of the scope of application, and a real example. Also considered are comparisons, critical evaluations and new applications of existing methods, contributions to probability theory which have a clear practical bearing, statistical computation or simulation where original methodology is involved, and original contributions to the foundations of statistical science. A paper, even if correct and well presented, is likely to be rejected if it only presents straightforward special cases of previously published work, if it is of mathematical interest only, if it is too long in relation to the importance of the new material that it contains, or if it is dominated by computations or simulations of a routine nature.