MIRA, ANTONIETTA

MIRA, ANTONIETTA  

DIPARTIMENTO DI SCIENZA E ALTA TECNOLOGIA  

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Risultati 1 - 20 di 119 (tempo di esecuzione: 0.031 secondi).
Titolo Data di pubblicazione Autore(i) File
A Bayesian high-frequency estimator of the multivariate covariance of noisy and asynchronous returns 1-gen-2015 Peluso, Stefano; Corsi, Fulvio; Mira, Antonietta
A Bayesian Semiparametric Multiplicative Error Model with an Application to Realized Volatility 1-gen-2013 R., Solgi; Mira, Antonietta
A Bayesian semiparametric vector Multiplicative Error Model 1-gen-2021 Donelli, N.; Peluso, S.; Mira, A.
A Bayesian spatio-temporal statistical analysis of Out-of-Hospital Cardiac Arrests 1-gen-2020 Peluso, Stefano; Mira, Antonietta; Rue, Havard; Tierney, Nicholas; Benvenuti, Claudio; Cianella, Roberto; Luce Caputo, Maria; Auricchio, Angelo
A Common Atoms Model for the Bayesian Nonparametric Analysis of Nested Data 1-gen-2023 Denti, Francesco; Camerlenghi, Federico; Guindani, Michele; Mira, Antonietta
A global perspective on the intrinsic dimensionality of COVID-19 data 1-gen-2023 Varghese, Abhishek; Santos-Fernandez, Edgar; Denti, Francesco; Mira, Antonietta; Mengersen, Kerrie
A multivariate statistical approach to predict COVID-19 count data with epidemiological interpretation and uncertainty quantification 1-gen-2021 Bartolucci, F.; Pennoni, F.; Mira, A.
A new strategy for speeding Markov chain Monte Carlo algorithms 1-gen-2003 Mira, Antonietta; Sargent, D.
A predictive model for planning emergency events rescue during COVID-19 in Lombardy, Italy 1-gen-2023 Andreella, A.; Mira, A.; Balafas, S.; Wit, E. -J. C.; Ruggeri, F.; Nattino, G.; Ghilardi, G.; Bertolini, G.
A probabilistic spatio-temporal neural network to forecast COVID-19 counts 1-gen-2024 Ravenda, Federico; Cesarini, Mirko; Peluso, Stefano; Mira, Antonietta
A self-supervised seed-driven approach to topic modelling and clustering 1-gen-2024 Ravenda, Federico; Bahrainian, Seyed Ali; Raballo, Andrea; Mira, Antonietta; Crestani, Fabio
ABCpy: A High-Performance Computing Perspective to Approximate Bayesian Computation 1-gen-2021 Dutta, Ritabrata; Schoengens, Marcel; Pacchiardi, Lorenzo; Ummadisingu, Avinash; Widmer, Nicole; Künzli, Pierre; Onnela, Jukka-Pekka; Mira, Antonietta
ABCpy: A user-friendly, extensible, and parallel library for approximate Bayesian computation 1-gen-2017 Dutta, Ritabrata; Schoengens, Marcel; Onnela, Jukka-Pekka; Mira, Antonietta
Adaptive Incremental Mixture Markov Chain Monte Carlo 1-gen-2019 Maire, Florian; Friel, Nial; Mira, Antonietta; E Raftery, Adrian
Adaptive Multiple Importance Sampling 1-gen-2012 Jean Marie, Cornuet; Jean Michel, Marin; Mira, Antonietta; Christian, Robert
An extension of Peskun and Tierney orderings to continuous time Markov chains 1-gen-2008 Leisen, Fabrizio; Mira, Antonietta
An investigation on the delayed rejection strategy in the capture-recapture context 1-gen-2003 F., Bartolucci; Mira, Antonietta; L., Scaccia
Analisi dei Dati, raccolta di esercizi tratti da esami con soluzioni ragionate 1-gen-2002 Mira, Antonietta
Answering two biological questions with a latent class model via MCMC applied to capture-recapture data 1-gen-2003 Bartolucci, F.; Mira, Antonietta; Scaccia, L.
Approximating Max-Sum-Product Problems using Multiplicative Error Bounds 1-gen-2012 Meek, C.; Wexler, Y.; Mira, A.