Statistica Sinica

Aims & Scope✦ Inferred from recent articles

Statistica Sinica publishes research on statistical theory and methodology, with a focus on developing and analyzing new statistical models and methods. Recent articles address topics such as latent space models for network analysis, factor modeling for high-dimensional time series, regression analysis for clustered and interval-censored data, hypothesis testing for multiple data streams, covariate-adaptive randomization in clinical trials, compositional regression for microbiome studies, time-dependent covariates in survival analysis, conformal inference for missing data, covariate balance in survey experiments, model selection for clustered regression, bootstrap approximations for high-dimensional data, correlation coefficients for censored data, causal inference in cluster randomized trials, functional regression models, transfer learning for high-dimensional regression, time series of counts, volatility jump detection, treatment effect estimation, space-filling designs for computer experiments, and Bayesian grouped regression.

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Source: OpenAlex · Note: citations accumulate over time so older years appear higher

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