Matteo Fasiolo
Matteo Fasiolo
Lecturer in Statistical Science, University of Bristol
Verified email at - Homepage
Cited by
Cited by
Fast calibrated additive quantile regression
M Fasiolo, SN Wood, M Zaffran, R Nedellec, Y Goude
Journal of the American Statistical Association, 1-11, 2020
A comparison of inferential methods for highly non-linear state space models in ecology and epidemiology
M Fasiolo, N Pya, S Wood
Statistical Science 31 (1), 96-118, 2016
Scalable visualisation methods for modern Generalized Additive Models
SN Fasiolo, M., Nedellec, R., Goude, Y. and Wood
arXiv preprint arXiv:1809.10632, 2018
Practice makes perfect: The consequences of lexical proficiency for articulation
F Tomaschek, BV Tucker, M Fasiolo, RH Baayen
Linguistics Vanguard 4 (s2), 20170018, 2018
A generalized Fellner‐Schall method for smoothing parameter optimization with application to Tweedie location, scale and shape models
SN Wood, M Fasiolo
Biometrics 73 (4), 1071-1081, 2017
Rfast: Fast r functions
M Papadakis, M Tsagris, M Dimitriadis, I Tsamardinos, M Fasiolo, ...
R package version 1 (5), 2017
An extended empirical saddlepoint approximation for intractable likelihoods
M Fasiolo, SN Wood, F Hartig, MV Bravington
Electronic Journal of Statistics 12 (1), 1544-1578, 2018
Stochastic particle flow for nonlinear high-dimensional filtering problems
FE De Melo, S Maskell, M Fasiolo, F Daum
arXiv preprint arXiv:1511.01448, 2015
Clinical predictors of pacemaker implantation in patients with syncope receiving implantable loop recorder with or without ECG conduction abnormalities
N Ahmed, A Frontera, A Carpenter, S Cataldo, GM Connolly, M Fasiolo, ...
Pacing and Clinical Electrophysiology 38 (8), 934-941, 2015
An introduction to synlik (2014)
M Fasiolo, S Wood
R package version 0.1 1, 2014
ABC in ecological modelling
M Fasiolo, SN Wood
Handbook of approximate Bayesian computation, 597-622, 2018
An introduction to mvnfast
M Fasiolo
R package version 0.1 6, 2016
Approximate methods for dynamic ecological models
M Fasiolo, SN Wood, To appear in the Handbook of Approximate …, 2015
Statistical inference for highly non-linear dynamical models in ecology and epidemiology
M Fasiolo, N Pya, S Wood
arXiv preprint arXiv:1411.4564, 2014
Fast calibrated additive quantile regression, 2017
M Fasiolo, Y Goude, R Nedellec, SN Wood
URL https://github. com/mfasiolo/qgam/blob/master/draft_qgam. pdf.[Online, 0
Langevin incremental mixture importance sampling
M Fasiolo, FE de Melo, S Maskell
Statistics and Computing 28 (3), 549-561, 2018
Drivers of interannual and intra‐annual variability of dissolved organic carbon concentration in the River Thames between 1884 and 2013
V Noacco, CJ Duffy, T Wagener, F Worrall, M Fasiolo, NJK Howden
Hydrological Processes 33 (6), 994-1012, 2019
A generalized Fellner-Schall method for smoothing parameter estimation with application to Tweedie location, scale and shape models
SN Wood, M Fasiolo
arXiv preprint arXiv:1606.04802, 2016
Statistical Methods for Complex Population Dynamics
M Fasiolo
University of Bath, 2016
Demographic and clinical characteristics to predict paroxysmal atrial fibrillation: insights from an implantable loop recorder population
A Frontera, A Carpenter, N Ahmed, M Fasiolo, M Nelson, I Diab, T Cripps, ...
Pacing and Clinical Electrophysiology 38 (10), 1217-1222, 2015
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