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Carles Breto
Carles Breto
Universitat de Valencia (https://ror.org/043nxc105)
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Año
Inference for nonlinear dynamical systems
EL Ionides, C Bretó, AA King
Proceedings of the National Academy of Sciences 103 (49), 18438-18443, 2006
6162006
Time series analysis via mechanistic models
C Bretó, D He, EL Ionides, AA King
The Annals of Applied Statistics, 319-348, 2009
2822009
pomp: Statistical inference for partially observed Markov processes
AA King, EL Ionides, CM Bretó, SP Ellner, MJ Ferrari, BE Kendall, ...
R package, version 1 (1.1), 2015
130*2015
Monte Carlo profile confidence intervals for dynamic systems
EL Ionides, C Breto, J Park, RA Smith, AA King
Journal of The Royal Society Interface 14 (132), 20170126, 2017
612017
Compound Markov counting processes and their applications to modeling infinitesimally over-dispersed systems
C Bretó, EL Ionides
Stochastic Processes and their Applications 121 (11), 2571-2591, 2011
512011
Modeling and inference for infectious disease dynamics: a likelihood-based approach
C Bretó
Statistical Science 33 (1), 57-69, 2018
362018
Panel data analysis via mechanistic models
C Bretó, EL Ionides, AA King
Journal of the American Statistical Association, 1-35, 2019
332019
On idiosyncratic stochasticity of financial leverage effects
C Bretó
Statistics & Probability Letters 91, 20-26, 2014
292014
Modeling disease dynamics: Cholera as a case study
EL Ionides, C Bretó, AA King
Statistical Advances in the Biomedical Sciences: Clinical Trials …, 2007
102007
An entropy-based machine learning algorithm for combining macroeconomic forecasts
C Bretó, P Espinosa, P Hernández, JM Pavía
Entropy 21 (10), 1015, 2019
72019
On the infinitesimal dispersion of multivariate Markov counting systems
C Bretó
Statistics & Probability Letters 82 (4), 720-725, 2012
42012
Time changes that result in multiple points in continuous-time Markov counting processes
C Bretó
Statistics & Probability Letters 82 (12), 2229-2234, 2012
32012
Trajectory composition of Poisson time changes and Markov counting systems
C Bretó
Statistics & Probability Letters 88, 91-98, 2014
22014
Co-jumps and Markov counting systems in random environments
C Bretó
Contemporary Approaches and Methods in Fundamental Mathematics and Mechanics …, 2021
12021
Forecasting volatility: does continuous time do better than discrete time?
C Bretó, H Veiga
12011
Statistical Inference for Nonlinear Dynamical Systems.
C Bretó
2007
El sistema no puede realizar la operación en estos momentos. Inténtalo de nuevo más tarde.
Artículos 1–16