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Department of Pure Mathematics and Mathematical Statistics

University Lecturer

Research Interests: Bayesian methods and Bayesian nonparametrics, analysis of Markov models, and applications to biology and biophysics

Publications

Bayesian mixed effects model for zero-inflated compositions in microbiome data analysis
B Ren, S Bacallado de Lara, S Favaro, T Vatanen, C Huttenhower, L Trippa
– Annals of Applied Statistics
(2020)
Bayesian Uncertainty Directed Trial Designs
S Ventz, M Cellamare, S Bacallado, L Trippa
– Journal of the American Statistical Association
(2019)
114,
1
Sufficientness postulates for Gibbs-type priors and hierarchical generalizations
SA Bacallado de Lara, M Battiston, S Favaro, L Trippa
– Statistical Science
(2017)
32,
487
Bayesian Nonparametric Ordination for the Analysis of Microbial Communities
B Ren, S Bacallado, S Favaro, S Holmes, L Trippa
– J Am Stat Assoc
(2017)
112,
1430
Bayesian nonparametric inference for shared species richness in multiple populations
S Bacallado, S Favaro, L Trippa
– Journal of Statistical Planning and Inference
(2015)
166,
14
Bayesian regularization of the length of memory in reversible sequences
S Bacallado, V Pande, S Favaro, L Trippa
– Journal of the Royal Statistical Society Series B (Statistical Methodology)
(2015)
78,
933
de Finetti Priors using Markov chain Monte Carlo computations.
S Bacallado, P Diaconis, S Holmes
– Statistics and computing
(2015)
25,
797
BETS: The dangers of selection bias in early analyses of the coronavirus disease (COVID-19) pandemic
Q Zhao, N Ju, S Bacallado, RD Shah
BETS: The dangers of selection bias in early analyses of the coronavirus disease (COVID-19) pandemic
Q Zhao, N Ju, S Bacallado, RD Shah
– Annals of Applied Statistics

Room

D1.10

Telephone

01223 337960