研飞ivySCI (青藤学术）

Journal of the Royal Statistical Society. Series C: Applied Statistics

短名	J. R. Stat. Soc. C
Journal Impact	1.02
国际分区	STATISTICS & PROBABILITY(Q3)
期刊索引	SCI Q2中科院 4 区

ISSN	0035-9254, 1467-9876
h-index	80
国内分区	数学(4区)数学统计学与概率论(3区)

The Journal of the Royal Statistical Society, Series C (Applied Statistics) is a journal of international repute for statisticians both inside and outside the academic world. The journal is concerned with papers which deal with novel solutions to real life statistical problems by adapting or developing methodology, or by demonstrating the proper application of new or existing statistical methods to them. At their heart therefore the papers in the journal are motivated by examples and statistical data of all kinds. The subject-matter covers the whole range of inter-disciplinary fields, e.g. applications in agriculture, genetics, industry, medicine and the physical sciences, and papers on design issues (e.g. in relation to experiments, surveys or observational studies). A deep understanding of statistical methodology is not necessary to appreciate the content. Although papers describing developments in statistical computing driven by practical examples are within its scope, the journal is not concerned with simply numerical illustrations or simulation studies. The emphasis of Series C is on case-studies of statistical analyses in practice.

期刊主页投稿网址

涉及主题	数学计算机科学统计经济计量经济学机器学习物理医学生物人工智能工程类
出版信息	出版商: Oxford University Press，出版周期: Quarterly，期刊类型: journal
基本数据	创刊年份: 1996，原创研究文献占比: 100.00%，自引率:0.00%， Gold OA占比: 29.52%
平均审稿周期	网友分享经验：>12周，或约稿
平均录用比例	网友分享经验：容易

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Mixtures of Dirichlet processes for joint spatial modelling of transcranial magnetic stimulation mapping data

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Inference for extreme spatial temperature events in a changing climate with application to Ireland

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Measuring the impact of new risk factors within survival models

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A Bayesian valuation framework for catastrophe bonds

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Joint modelling of survival and backwards recurrence outcomes: an analysis of factors associated with fertility treatment in the U.S.

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A state-space perspective on modelling and inference for online skill rating

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An adaptive functional regression framework for locally heterogeneous signals in spectroscopy

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A semi-parametric maximum-likelihood analysis of measurement error in population size estimation

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A noisy-input generalized additive model for relative sea-level change along the Atlantic coast of North America

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Automatic locally stationary time series forecasting with application to predicting UK gross value added time series

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Non-parametric Bayesian approach to multiple treatment comparisons in network meta-analysis with application to comparisons of anti-depressants

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Walking fingerprinting

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Spatio-temporal forecasting for the US Drought Monitor

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Estimating spatially varying health effects of wildland fire smoke using mobile health data

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Variable importance based interaction modelling with an application on initial spread of COVID-19 in China

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A fractional Hawkes process model for earthquake aftershock sequences

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Learning local cascading failure pattern from massive network failure data

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Two-phase biomarker studies for disease progression with multiple registries

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Bats monitoring: a classification procedure of bats behaviours based on Hawkes processes

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Inverse set estimation and inversion of simultaneous confidence intervals

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Exponential tilting for zero-inflated interval regression with applications to cyber security survey data

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Dynamic factor models for binary data in circular spaces: an application to the US Supreme Court

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Semi-parametric Bayesian approach for population size estimation modelling the excess of singletons

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Testing for distributional structural change with unknown breaks: application to pricing crop insurance contracts

2024-5-16

A bi-endpoint expectation-maximisation algorithm for re-estimating sample size for the time-to-event endpoint under the blind condition

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A stochastic gradient relational event additive model for modelling US patent citations from 1976 to 2022

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Estimating disease transmission in a closed population under repeated testing

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Joint analysis of multivariate longitudinal, imaging, and time-to-event data

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Estimating the timing of stillbirths in countries worldwide using a Bayesian hierarchical penalized splines regression model

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Bayesian modelling of effective and functional brain connectivity using hierarchical vector autoregressions

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Generalized functional additive mixed models with (functional) compositional covariates for areal Covid-19 incidence curves

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A two-sample tree-based test for hierarchically organized genomic signals

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Population-level task-evoked functional connectivity via Fourier analysis

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Estimating the size of undeclared work from partially misclassified survey data via the Expectation–Maximization algorithm

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Optimal transport-based machine learning to match specific patterns: application to the detection of molecular regulation patterns in omics data

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Nonlinear network-based quantitative trait prediction from biological data

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Testing unit root non-stationarity in the presence of missing data in univariate time series of mobile health studies

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A doubly self-exciting Poisson model for describing scoring levels in NBA basketball