Sally (Wood) Cripps

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Martin A. TannerNorthwestern UniversityVerified email at northwestern.edu
robert kohnProfessor of Economics University of New South WalesVerified email at unsw.edu.au
John P.A. IoannidisProfessor of Medicine/Health Research & Policy/Biomedical Data Science/Statistics, Stanford UnivVerified email at stanford.edu
Rohitash ChandraUNSWVerified email at unsw.edu.au
Edward CrippsAssociate Professor Statistics, University of Western AustraliaVerified email at uwa.edu.au
Roman MarchantThe University of SydneyVerified email at sydney.edu.au
Richard ScalzoCSIROVerified email at data61.csiro.au
Tom ShivelyProfessor of Statistics, McCombs School of Business, University of Texas at AustinVerified email at mccombs.utexas.edu
Tristan SallesSchool of Geosciences, The University of SydneyVerified email at sydney.edu.au
Nick GlozierProfessor of Psychological Medicine, University of SydneyVerified email at sydney.edu.au
Danial AzamUniversity of SydneyVerified email at sydney.edu.au
Dietmar MüllerProf. of Geophysics, EarthByte Group, Univ. of SydneyVerified email at sydney.edu.au
Victor SojoSenior Lecturer in Leadership, The University of MelbourneVerified email at unimelb.edu.au
Nathan KettlewellResearch Fellow, University of Technology SydneyVerified email at uts.edu.au
Deborah Cobb-ClarkSchool of Economics University fo SydneyVerified email at sydney.edu.au
Richard MorrisTranslational datascientist, University of SydneyVerified email at sydney.edu.au
Gregory A. HousemanProfessor of Geophysics, University of LeedsVerified email at leeds.ac.uk
Mark GirolamiUniversity of CambridgeVerified email at cam.ac.uk
Jens F. BeckmannDurham UniversityVerified email at durham.ac.uk
Nadin BeckmannAssociate Professor, Durham UniversityVerified email at durham.ac.uk

Sally (Wood) Cripps

University of Sydney

Verified email at sydney.edu.au


Title Sort by citations Sort by year Sort by title	Cited by Cited by	Year
Forecasting for COVID-19 has failed JPA Ioannidis, S Cripps, MA Tanner International journal of forecasting, 2020	230	2020
Reporting requirements, targets, and quotas for women in leadership VE Sojo, RE Wood, SA Wood, MA Wheeler The Leadership Quarterly 27 (3), 519-536, 2016	131	2016
Variable selection and function estimation in additive nonparametric regression using a data-based prior TS Shively, R Kohn, S Wood Journal of the American Statistical Association 94 (447), 777-794, 1999	110	1999
Bayesian mixture of splines for spatially adaptive nonparametric regression SA Wood, W Jiang, M Tanner Biometrika 89 (3), 513-528, 2002	106	2002
Bayesian variable selection and model averaging in high-dimensional multinomial nonparametric regression P Yau, R Kohn, S Wood Journal of Computational and Graphical Statistics 12 (1), 23-54, 2003	80	2003
A Bayesian approach to robust binary nonparametric regression S Wood, R Kohn Journal of the American Statistical Association 93 (441), 203-213, 1998	73	1998
AdaptSPEC: Adaptive spectral estimation for nonstationary time series O Rosen, S Wood, DS Stoffer Journal of the American Statistical Association 107 (500), 1575-1589, 2012	63	2012
Model selection in spline nonparametric regression S Wood, R Kohn, T Shively, W Jiang Journal of the Royal Statistical Society: Series B (Statistical Methodology …, 2002	55	2002
Local spectral analysis via a Bayesian mixture of smoothing splines O Rosen, DS Stoffer, S Wood Journal of the American Statistical Association 104 (485), 249-262, 2009	52	2009
A case study in model failure? COVID-19 daily deaths and ICU bed utilisation predictions in New York state V Chin, NI Samia, R Marchant, O Rosen, J Ioannidis, MA Tanner, S Cripps European Journal of Epidemiology 35 (8), 733-742, 2020	45	2020
Learning as we go: An examination of the statistical accuracy of COVID19 daily death count predictions R Marchant, NI Samia, O Rosen, MA Tanner, S Cripps arXiv preprint arXiv:2004.04734, 2020	42	2020
The differential impact of major life events on cognitive and affective wellbeing N Kettlewell, RW Morris, N Ho, DA Cobb-Clark, S Cripps, N Glozier SSM-population health 10, 100533, 2020	33	2020
Bayesian mixtures of autoregressive models S Wood, O Rosen, R Kohn Journal of Computational and Graphical Statistics 20 (1), 174-195, 2011	33	2011
Effect estimates of COVID-19 non-pharmaceutical interventions are non-robust and highly model-dependent V Chin, JPA Ioannidis, MA Tanner, S Cripps Journal of Clinical Epidemiology 136, 96-132, 2021	32*	2021
Langevin-gradient parallel tempering for Bayesian neural learning R Chandra, K Jain, RV Deo, S Cripps Neurocomputing 359, 315-326, 2019	28	2019
Efficiency and robustness in Monte Carlo sampling for 3-D geophysical inversions with Obsidian v0. 1.2: Setting up for success R Scalzo, D Kohn, H Olierook, G Houseman, R Chandra, M Girolami, ... Geoscientific Model Development 12 (7), 2941-2960, 2019	26	2019
Applying machine learning to criminology: semi-parametric spatial-demographic Bayesian regression R Marchant, S Haan, G Clancey, S Cripps Security Informatics 7 (1), 1-19, 2018	17	2018
Multicore parallel tempering Bayeslands for basin and landscape evolution R Chandra, RD Müller, D Azam, R Deo, N Butterworth, T Salles, S Cripps Geochemistry, Geophysics, Geosystems 20 (11), 5082-5104, 2019	14	2019
BayesLands: A Bayesian inference approach for parameter uncertainty quantification in Badlands R Chandra, D Azam, RD Müller, T Salles, S Cripps Computers & Geosciences 131, 89-101, 2019	14	2019
Locally adaptive nonparametric binary regression SA Wood, R Kohn, R Cottet, W Jiang, M Tanner Journal of Computational and Graphical Statistics 17 (2), 352-372, 2008	13	2008

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