| |
Original Artikel |
Journal |
Datum |
Titel |
Autoren Max. 6 Autoren |
| 1 |
[GO] |
The Annals of Applied Statistics |
2026―Jun―25 |
Measuring public opinion: “The Wasserstein bipolarization index,” with application to cross-national attitudes toward mandatory vaccination for COVID-19 |
Hane Lee, Michael E. Sobel |
| 2 |
[GO] |
The Annals of Applied Statistics |
2025―Dez―05 |
Exploring spatiotemporal variation in Covid-19 waves: Non-Euclidean spatially aware functional registration |
Luke A. Barratt, John A. D. Aston |
| 3 |
[GO] |
The Annals of Applied Statistics |
2025―Aug―28 |
Integrative ecological regression analysis of U.S. county and state level COVID-19 death data for studying health disparity associations |
Daniel Li, Xihong Lin |
| 4 |
[GO] |
The Annals of Applied Statistics |
2025―Mai―28 |
Temporal network influence model with application to the COVID-19 population flow network |
Dongxue Zhang, Long Feng, Yujia Wu, Wei Lan, Jing Zhou |
| 5 |
[GO] |
The Annals of Applied Statistics |
2025―Mrz―18 |
Leveraging cellphone-derived mobility networks to assess Covid-19 travel risk |
Justin J. Slater, Patrick E. Brown, Jeffrey S. Rosenthal, Jorge Mateu |
| 6 |
[GO] |
The Annals of Applied Statistics |
2025―Mrz―18 |
A three-state coupled Markov switching model for COVID-19 outbreaks across Q based on hospital admissions |
Dirk Douwes-Schultz, Alexandra M. Schmidt, Yannan Shen, David L. Buckeridge |
| 7 |
[GO] |
The Annals of Applied Statistics |
2025―Mrz―18 |
Has the Covid-19 outbreak capsized the predictive performance of Bayesian VAR models with cointegration and time-varying volatility? |
Anna Pajor, Łukasz Kwiatkowski, Justyna Wróblewska |
| 8 |
[GO] |
The Annals of Applied Statistics |
2024―Okt―31 |
Predicting COVID-19 hospitalisation using a mixture of Bayesian predictive syntheses |
Genya Kobayashi, Shonosuke Sugasawa, Yuki Kawakubo, Dongu Han, Taeryon Choi |
| 9 |
[GO] |
The Annals of Applied Statistics |
2024―Okt―31 |
Multisite disease analytics with applications to estimating COVID-19 undetected cases in Canada |
Matthew R. P. Parker, Jiguo Cao, Laura L. E. Cowen, Lloyd T. Elliott, Junling Ma |
| 10 |
[GO] |
The Annals of Applied Statistics |
2024―Aug―06 |
A nonparametric mixed-effects mixture model for patterns of clinical measurements associated with COVID-19 |
Xiaoran Ma, Wensheng Guo, Mengyang Gu, Len Usvyat, Peter Kotanko, Yuedong Wang |
| 11 |
[GO] |
The Annals of Applied Statistics |
2024―Aug―06 |
Semiparametric modeling of SARS-CoV-2 transmission using tests, cases, deaths, and seroprevalence data |
Damon Bayer, Isaac H. Goldstein, Jonathan Fintzi, Keith Lumbard, Emily Ricotta, Sarah Warner, Jeffrey R Strich, Daniel S. Chertow, Lindsay M. Busch, Daniel M. Parker, Bernadette Boden-Albala, Richard Chhuon, Matthew Zahn, Nichole Quick, Alissa Dratch, Volodymyr M. Minin |
| 12 |
[GO] |
Brazilian Journal of Probability and Statistics |
2024―Mrz―05 |
Some estimation procedures for Covid-19 suspected persons in a locality using randomized response model |
G. N. Singh, D. Bhattacharyya, A. Bandyopadhyay |
| 13 |
[GO] |
The Annals of Applied Statistics |
2024―Jan―31 |
Nonnegative tensor completion for dynamic counterfactual prediction on COVID-19 pandemic |
Yaoming Zhen, Junhui Wang |
| 14 |
[GO] |
The Annals of Applied Statistics |
2024―Jan―31 |
Change point detection in dynamic Gaussian graphical models: The impact of COVID-19 pandemic on the U.S. stock market |
Beatrice Franzolini, Alexandros Beskos, Maria De Iorio, Warrick Poklewski Koziell, Karolina Grzeszkiewicz |
| 15 |
[GO] |
The Annals of Applied Statistics |
2023―Okt―31 |
Addressing selection bias and measurement error in COVID-19 case count data using auxiliary information |
Walter Dempsey |
| 16 |
[GO] |
The Annals of Applied Statistics |
2023―Okt―31 |
Modeling racial/ethnic differences in COVID-19 incidence with covariates subject to nonrandom missingness |
Rob Trangucci, Yang Chen, Jon Zelner |
| 17 |
[GO] |
The Annals of Applied Statistics |
2023―Okt―31 |
Estimating Covid-19 transmission time using Hawkes point processes |
Frederic Schoenberg |
| 18 |
[GO] |
The Annals of Applied Statistics |
2023―Okt―31 |
Estimating COVID-19 vaccine protection rates via dynamic epidemiological models-a study of 10 countries |
Yuru Zhu, Jia Gu, Yumou Qiu, Song Xi Chen |
| 19 |
[GO] |
The Annals of Applied Statistics |
2023―Okt―31 |
Bayesian learning of Covid-19 vaccine safety while incorporating adverse events ontology |
Bangyao Zhao, Yuan Zhong, Jian Kang, Lili Zhao |
| 20 |
[GO] |
The Annals of Applied Statistics |
2023―Sep―07 |
Real-time mechanistic Bayesian forecasts of COVID-19 mortality |
Graham C. Gibson, Nicholas G. Reich, Daniel Sheldon |
| 21 |
[GO] |
The Annals of Applied Statistics |
2023―Mai―01 |
Estimating global and country-specific excess mortality during the Covid-19 pandemic |
Victoria Knutson, Serge Aleshin-Guendel, Ariel Karlinsky, William Msemburi, Jon Wakefield |
| 22 |
[GO] |
The Annals of Applied Statistics |
2023―Jan―24 |
Bayesian clustering of spatial functional data with application to a human mobility study during COVID-19 |
Bohai Zhang, Huiyan Sang, Zhao Tang Luo, Hui Huang |
| 23 |
[GO] |
The Annals of Applied Statistics |
2023―Jan―24 |
Social distancing and COVID-19: Randomization inference for a structured dose-response relationship |
Bo Zhang, Siyu Heng, Ting Ye, Dylan S. Small |
| 24 |
[GO] |
Bayesian Analysis |
2022―Okt―03 |
Regularised B-splines Projected Gaussian Process Priors to Estimate Time-trends in Age-specific COVID-19 Deaths |
Mélodie Monod, Alexandra Blenkinsop, Andrea Brizzi, Yu Chen, Carlos Cardoso Correia Perello, Vidoushee Jogarah, Yuanrong Wang, Seth Flaxman, Samir Bhatt, Oliver Ratmann |
| 25 |
[GO] |
The Annals of Applied Statistics |
2022―Sep―27 |
Causal inference for the effect of mobility on COVID-19 deaths |
Matteo Bonvini, Edward H. Kennedy, Valerie Ventura, Larry Wasserman |
| 26 |
[GO] |
The Annals of Applied Statistics |
2022―Sep―27 |
Estimating functional parameters for understanding the impact of weather and government interventions on COVID-19 outbreak |
Chih-Li Sung |
| 27 |
[GO] |
Statistical Science |
2022―Mai―17 |
Seven Principles for Rapid-Response Data Science: Lessons Learned from Covid-19 Forecasting |
Bin Yu, Chandan Singh |
| 28 |
[GO] |
Statistical Science |
2022―Mai―17 |
Real-Time Estimation of COVID-19 Infections: Deconvolution and Sensor Fusion |
Maria Jahja, Andrew Chin, Ryan J. Tibshirani |
| 29 |
[GO] |
Statistical Science |
2022―Mai―17 |
Statistical Modeling for Practical Pooled Testing During the COVID-19 Pandemic |
Saskia Comess, Hannah Wang, Susan Holmes, Claire Donnat |
| 30 |
[GO] |
Statistical Science |
2022―Mai―17 |
Lessons Learned from the COVID-19 Pandemic: A Statistician’s Reflection |
Xihong Lin |
| 31 |
[GO] |
Statistical Science |
2022―Mai―17 |
Learning and Predicting from Dynamic Models for COVID-19 Patient Monitoring |
Zitong Wang, Mary Grace Bowring, Antony Rosen, Brian Garibaldi, Scott Zeger, Akihiko Nishimura |
| 32 |
[GO] |
Statistical Science |
2022―Mai―17 |
Statistical Challenges in Tracking the Evolution of SARS-CoV-2 |
Lorenzo Cappello, Jaehee Kim, Sifan Liu, Julia A. Palacios |
| 33 |
[GO] |
Statistical Science |
2022―Mai―17 |
Being a Public Health Statistician During a Global Pandemic |
Bhramar Mukherjee |
| 34 |
[GO] |
Statistical Science |
2022―Mai―17 |
Data Science in a Time of Crisis: Lessons from the Pandemic |
Chiara Sabatti, John M. Chambers |
| 35 |
[GO] |
Statistical Science |
2022―Mai―17 |
Interoperability of Statistical Models in Pandemic Preparedness: Principles and Reality |
George Nicholson, Marta Blangiardo, Mark Briers, Peter J. Diggle, Tor Erlend Fjelde, Hong Ge, Robert J. B. Goudie, Radka Jersakova, Ruairidh E. King, Brieuc C. L. Lehmann, Ann-Marie Mallon, Tullia Padellini, Yee Whye Teh, Chris Holmes, Sylvia Richardson |
| 36 |
[GO] |
The Annals of Applied Statistics |
2022―Mrz―29 |
Bayesian adjustment for preferential testing in estimating infection fatality rates, as motivated by the COVID-19 pandemic |
Harlan Campbell, Perry de Valpine, Lauren Maxwell, Valentijn M. T. de Jong, Thomas P. A. Debray, Thomas Jaenisch, Paul Gustafson |
| 37 |
[GO] |
The Annals of Applied Statistics |
2021―Mrz―19 |
BETS: The dangers of selection bias in early analyses of the coronavirus disease (COVID-19) pandemic |
Qingyuan Zhao, Nianqiao Ju, Sergio Bacallado, Rajen D. Shah |
| 38 |
[GO] |
The Annals of Applied Statistics |
2020―Apr―16 |
Efficient real-time monitoring of an emerging influenza pandemic: How feasible? |
Paul J. Birrell, Lorenz Wernisch, Brian D. M. Tom, Leonhard Held, Gareth O. Roberts, Richard G. Pebody, Daniela De Angelis |
