155 citations · 360 across the 13 of their papers we have counts for
9 papers · 1 filter
A note on the modeling of the effects of experimental time in psycholinguistic experiments
R. Harald Baayen, Matteo Fasiolo, Simon Wood +1
Thul et al. (2020) called attention to problems that arise when chronometric experiments implementing specific factorial designs are analysed with the generalized additive mixed mo…
qgam: Bayesian non-parametric quantile regression modelling in R
Matteo Fasiolo, Simon N. Wood, Margaux Zaffran +2
Generalized additive models (GAMs) are flexible non-linear regression models, which can be fitted efficiently using the approximate Bayesian methods provided by the mgcv R package.…
Scalable visualisation methods for modern Generalized Additive Models
Matteo Fasiolo, Raphaël Nedellec, Yannig Goude +1
In the last two decades the growth of computational resources has made it possible to handle Generalized Additive Models (GAMs) that formerly were too costly for serious applicatio…
Fast calibrated additive quantile regression
M. Fasiolo, S. N. Wood, M. Zaffran +2
We propose a novel framework for fitting additive quantile regression models, which provides well calibrated inference about the conditional quantiles and fast automatic estimation…
A generalized Fellner-Schall method for smoothing parameter estimation with application to Tweedie location, scale and shape models
Simon N. Wood, Matteo Fasiolo
We consider the estimation of smoothing parameters and variance components in models with a regular log likelihood subject to quadratic penalization of the model coefficients, via…
An Extended Empirical Saddlepoint Approximation for Intractable Likelihoods
Matteo Fasiolo, Simon N. Wood, Florian Hartig +1
The challenges posed by complex stochastic models used in computational ecology, biology and genetics have stimulated the development of approximate approaches to statistical infer…
Approximate methods for dynamic ecological models
Matteo Fasiolo, Simon N. Wood
This document is due to appear as a chapter of the forthcoming Handbook of Approximate Bayesian Computation (ABC) by S. Sisson, L. Fan, and M. Beaumont. Here we describe some of th…
Stochastic Particle Flow for Nonlinear High-Dimensional Filtering Problems
Flávio Eler De Melo, Simon Maskell, Matteo Fasiolo +1
A series of novel filters for probabilistic inference that propose an alternative way of performing Bayesian updates, called particle flow filters, have been attracting recent inte…
A comparison of inferential methods for highly non-linear state space models in ecology and epidemiology
Matteo Fasiolo, Natalya Pya, Simon N. Wood
Highly non-linear, chaotic or near chaotic, dynamic models are important in fields such as ecology and epidemiology: for example, pest species and diseases often display highly non…