Matteo Fasiolo
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View article: High measured GFR as a predictor of all-cause mortality and cardiovascular disease in a prospective non-diabetic population cohort
High measured GFR as a predictor of all-cause mortality and cardiovascular disease in a prospective non-diabetic population cohort Open
Background High glomerular filtration rate (GFR) is generally regarded as beneficial but has been associated with cardiovascular disease (CVD) and all-cause mortality in epidemiological studies. However, these investigations may have been …
View article: Scalable Fitting Methods for Multivariate Gaussian Additive Models with Covariate-dependent Covariance Matrices
Scalable Fitting Methods for Multivariate Gaussian Additive Models with Covariate-dependent Covariance Matrices Open
We propose efficient computational methods to fit multivariate Gaussian additive models, where the mean vector and the covariance matrix are allowed to vary with covariates, in an empirical Bayes framework. To guarantee the positive-defini…
View article: SoftCVI: Contrastive variational inference with self-generated soft labels
SoftCVI: Contrastive variational inference with self-generated soft labels Open
Estimating a distribution given access to its unnormalized density is pivotal in Bayesian inference, where the posterior is generally known only up to an unknown normalizing constant. Variational inference and Markov chain Monte Carlo meth…
View article: Soil organic carbon stocks in European croplands and grasslands: How much have we lost in the past decade?
Soil organic carbon stocks in European croplands and grasslands: How much have we lost in the past decade? Open
The EU Soil Strategy 2030 aims to increase soil organic carbon (SOC) in agricultural land to enhance soil health and support biodiversity as well as to offset greenhouse gas emissions through soil carbon sequestration. Therefore, the quant…
View article: Adaptive Probabilistic Forecasting of Electricity (Net-)Load
Adaptive Probabilistic Forecasting of Electricity (Net-)Load Open
Electricity load forecasting is a necessary capability for power system operators and electricity market participants. The proliferation of local generation, demand response, and electrification of heat and transport are changing the funda…
View article: A flexible copula regression model with Bernoulli and Tweedie margins for estimating the effect of spending on mental health
A flexible copula regression model with Bernoulli and Tweedie margins for estimating the effect of spending on mental health Open
We develop a flexible two‐equation copula model to address endogeneity of medical expenditures in a distribution regression for health. The expenditure margin uses the compound gamma distribution, a special case of the Tweedie family of di…
View article: Supplementary materials for "Adaptive Probabilistic Forecasting of Electricity (Net-)Load"
Supplementary materials for "Adaptive Probabilistic Forecasting of Electricity (Net-)Load" Open
Supplementary materials for “Adaptive Probabilistic Forecasting of Electricity (Net-)Load”, presently under review. Only underlying data is included for now. Code will be included in a future update of this deposit.
View article: Supplementary materials for "Adaptive Probabilistic Forecasting of Electricity (Net-)Load"
Supplementary materials for "Adaptive Probabilistic Forecasting of Electricity (Net-)Load" Open
Supplementary materials for “Adaptive Probabilistic Forecasting of Electricity (Net-)Load”, presently under review. Only underlying data is included for now. Code will be included in a future update of this deposit.
View article: Supplementary materials for "Adaptive Probabilistic Forecasting of Electricity (Net-)Load"
Supplementary materials for "Adaptive Probabilistic Forecasting of Electricity (Net-)Load" Open
Supplementary materials for “Adaptive Probabilistic Forecasting of Electricity (Net-)Load”, presently under review. Only underlying data is included for now. Code will be included in a future update of this deposit.
View article: Robust Neural Posterior Estimation and Statistical Model Criticism
Robust Neural Posterior Estimation and Statistical Model Criticism Open
Computer simulations have proven a valuable tool for understanding complex phenomena across the sciences. However, the utility of simulators for modelling and forecasting purposes is often restricted by low data quality, as well as practic…
View article: Covariance structures for high-dimensional energy forecasting
Covariance structures for high-dimensional energy forecasting Open
Forecasts of various quantities over multiple time periods and/or spatial expanses are required to operate modern power systems. Furthermore, probabilistic forecasts are necessary to facilitate economic decision-making and risk management.…
View article: A note on the modeling of the effects of experimental time in psycholinguistic experiments
A note on the modeling of the effects of experimental time in psycholinguistic experiments Open
Thul et al. (2020) called attention to problems that arise when chronometric experiments implementing specific factorial designs are analysed with the generalized additive mixed model (GAMM), using factor smooths to capture trial-to-trial …
View article: Daily peak electrical load forecasting with a multi-resolution approach
Daily peak electrical load forecasting with a multi-resolution approach Open
In the context of smart grids and load balancing, daily peak load forecasting has become a critical activity for stakeholders of the energy industry. An understanding of peak magnitude and timing is paramount for the implementation of smar…
View article: Probabilistic Forecasting of Regional Net-Load With Conditional Extremes and Gridded NWP
Probabilistic Forecasting of Regional Net-Load With Conditional Extremes and Gridded NWP Open
Supplementary material to accompany pre-print of "Probabilistic Forecasting of Regional Net-load with Conditional Extremes and Gridded NWP" by Jethro Browell and Matteo Fasiolo available on on arXiv. This is version 3. The only changes fro…
View article: Additive stacking for disaggregate electricity demand forecasting
Additive stacking for disaggregate electricity demand forecasting Open
Future grid management systems will coordinate distributed production and storage resources to manage, in a cost effective fashion, the increased load and variability brought by the electrification of transportation and by a higher share o…
View article: A note on the modeling of the effects of experimental time in psycholinguistic experiments
A note on the modeling of the effects of experimental time in psycholinguistic experiments Open
Thul et al. (2020) called attention to problems that arise when chronometric experiments implementing specific factorial designs are analysed with the generalized additive mixed model (GAMM), using factor smooths to capture trial-to-trial …
View article: <b>qgam</b>: Bayesian Nonparametric Quantile Regression Modeling in <i>R</i>
<b>qgam</b>: Bayesian Nonparametric Quantile Regression Modeling in <i>R</i> Open
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. While the GAM methods provided by mgcv are based on the as…
View article: qgam: Bayesian non-parametric quantile regression modelling in R
qgam: Bayesian non-parametric quantile regression modelling in R Open
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. While the GAM methods provided by mgcv are based on the as…
View article: Differential aberrant structural synaptic plasticity in axons and dendrites ahead of their degeneration in tauopathy
Differential aberrant structural synaptic plasticity in axons and dendrites ahead of their degeneration in tauopathy Open
Neurodegeneration driven by aberrant tau is a key feature of many dementias. Pathological stages of tauopathy are characterised by reduced synapse density and altered synapse function. Furthermore, changes in synaptic plasticity have been …
View article: Fast Calibrated Additive Quantile Regression
Fast Calibrated Additive Quantile Regression Open
We propose a novel framework for fitting additive quantile regression models, which provides well-calibrated inference about the conditional quantiles and fast automatic estimation of the smoothing parameters, for model structures as diver…
View article: Peer Review #3 of "Hierarchical generalized additive models in ecology: an introduction with mgcv (v0.2)"
Peer Review #3 of "Hierarchical generalized additive models in ecology: an introduction with mgcv (v0.2)" Open
In this paper, we discuss an extension to two popular approaches to modelling complex structures in ecological data: the generalized additive model (GAM) and the hierarchical model (HGLM).The hierarchical GAM (HGAM), allows modelling of no…
View article: Peer Review #3 of "Hierarchical generalized additive models in ecology: an introduction with mgcv (v0.1)"
Peer Review #3 of "Hierarchical generalized additive models in ecology: an introduction with mgcv (v0.1)" Open
In this paper, we discuss an extension to two popular approaches to modelling complex structures in ecological data: the generalized additive model (GAM) and the hierarchical model (HGLM).The hierarchical GAM (HGAM), allows modelling of no…
View article: Scalable Visualization Methods for Modern Generalized Additive Models
Scalable Visualization Methods for Modern Generalized Additive Models Open
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 applications. However, the growth in model complexity has not been m…
View article: Scalable visualisation methods for modern Generalized Additive Models
Scalable visualisation methods for modern Generalized Additive Models Open
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 applications. However, the growth in model complexity has not been ma…
View article: Drivers of interannual and intra‐annual variability of dissolved organic carbon concentration in the River Thames between 1884 and 2013
Drivers of interannual and intra‐annual variability of dissolved organic carbon concentration in the River Thames between 1884 and 2013 Open
The world's longest record of river water quality (River Thames—130 years) provides a unique opportunity to understand fluvial dissolved organic carbon (DOC) concentrations dynamics. Understanding riverine DOC variability through long‐term…
View article: Scalable visualisation methods for modern Generalized Additive Models
Scalable visualisation methods for modern Generalized Additive Models Open
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 applications. However, the growth in model complexity has not been ma…