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
Roman MarchantAssociate Professor, Human Technology Institute, University of Technology SydneyVerified email at uts.edu.au
Rohitash ChandraUNSWVerified email at unsw.edu.au
Edward CrippsAssociate Professor Statistics, University of Western AustraliaVerified email at uwa.edu.au
Nick GlozierProfessor of Psychological Medicine, University of SydneyVerified email at sydney.edu.au
Richard ScalzoCSIROVerified email at data61.csiro.au
Vincent ChinUniversity of SydneyVerified email at sydney.edu.au
Tristan SallesSchool of Geosciences, The University of SydneyVerified email at sydney.edu.au
Tom ShivelyProfessor of Statistics, McCombs School of Business, University of Texas at AustinVerified email at mccombs.utexas.edu
Danial AzamUniversity of SydneyVerified email at sydney.edu.au
Richard W MorrisTranslational datascientist, University of SydneyVerified email at sydney.edu.au
Dietmar MüllerProfessor of Geophysics, EarthByte Group, Univ. of SydneyVerified email at sydney.edu.au
Nathan KettlewellSenior lecturer, University of Technology SydneyVerified email at uts.edu.au
Victor SojoAssociate Professor in Leadership, The University of MelbourneVerified email at unimelb.edu.au
Michael BertolacciSenior Lecturer, The University of Western AustraliaVerified email at uwa.edu.au
Rafael OliveiraData61 (CSIRO), AustraliaVerified email at data61.csiro.au
Deborah Cobb-Clark AOSchool of Economics University fo SydneyVerified email at sydney.edu.au
Konark JainPhD Student, University College LondonVerified email at ucl.ac.uk

Sally (Wood) Cripps

University of Technology Sydney

Verified email at uts.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 38 (2), 423-438, 2022	447	2022
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	196	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	122	1999
Bayesian mixture of splines for spatially adaptive nonparametric regression SA Wood, W Jiang, M Tanner Biometrika 89 (3), 513-528, 2002	113	2002
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	102	2020
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	87	2003
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, JPA Ioannidis, MA Tanner, ... European Journal of Epidemiology 35, 733-742, 2020	81	2020
A Bayesian approach to robust binary nonparametric regression S Wood, R Kohn Journal of the American Statistical Association 93 (441), 203-213, 1998	79	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	75	2012
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	68*	2021
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	64	2009
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
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	48	2020
Langevin-gradient parallel tempering for Bayesian neural learning R Chandra, K Jain, RV Deo, S Cripps Neurocomputing 359, 315-326, 2019	43	2019
Bayesian mixtures of autoregressive models S Wood, O Rosen, R Kohn Journal of Computational and Graphical Statistics 20 (1), 174-195, 2011	38	2011
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	33	2019
Bayesreef: A Bayesian inference framework for modelling reef growth in response to environmental change and biological dynamics J Pall, R Chandra, D Azam, T Salles, JM Webster, R Scalzo, S Cripps Environmental Modelling & Software 125, 104610, 2020	25	2020
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	25	2019
Applying machine learning to criminology: semi-parametric spatial-demographic Bayesian regression R Marchant, S Haan, G Clancey, S Cripps Security Informatics 7, 1-19, 2018	25	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	20	2019

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