Amanda Lenzi
Amanda Lenzi
Verifierad e-postadress på ed.ac.uk
Citeras av
Citeras av
Advanced spatial modeling with stochastic partial differential equations using R and INLA
E Krainski, V Gómez-Rubio, H Bakka, A Lenzi, D Castro-Camilo, ...
Chapman and Hall/CRC, 2018
Benefits of spatiotemporal modeling for short‐term wind power forecasting at both individual and aggregated levels
A Lenzi, I Steinsland, P Pinson
Environmetrics 29 (3), e2493, 2018
Neural networks for parameter estimation in intractable models
A Lenzi, J Bessac, J Rudi, ML Stein
Computational Statistics & Data Analysis 185, 107762, 2023
Parameter Estimation with Dense and Convolutional Neural Networks Applied to the FitzHugh–Nagumo ODE
J Rudi, J Bessac, A Lenzi
Mathematical and Scientific Machine Learning, 781-808, 2022
Spatial models for probabilistic prediction of wind power with application to annual-average and high temporal resolution data
A Lenzi, P Pinson, LH Clemmensen, G Guillot
Stochastic Environmental Research and Risk Assessment 31, 1615-1631, 2017
Power grid frequency prediction using spatiotemporal modeling
A Lenzi, J Bessac, M Anitescu
Statistical Analysis and Data Mining: The ASA Data Science Journal 14 (6 …, 2021
Very short-term spatio-temporal wind power prediction using a censored Gaussian field
A Baxevani, A Lenzi
Stochastic environmental research and risk assessment 32, 931-948, 2018
Spatio-temporal cross-covariance functions under the Lagrangian framework with multiple advections
MLO Salvaña, A Lenzi, MG Genton
Journal of the American Statistical Association 118 (544), 2746-2761, 2023
Improving Bayesian local spatial models in large datasets
A Lenzi, S Castruccio, H Rue, MG Genton
Journal of Computational and Graphical Statistics 30 (2), 349-359, 2020
Analysis of aggregated functional data from mixed populations with application to energy consumption
A Lenzi, CPE de Souza, R Dias, NL Garcia, NE Heckman
Environmetrics 28 (2), e2414, 2017
Neural Likelihood Surfaces for Spatial Processes with Computationally Intensive or Intractable Likelihoods
J Walchessen, A Lenzi, M Kuusela
arXiv preprint arXiv:2305.04634, 2023
Spatiotemporal probabilistic wind vector forecasting over Saudi Arabia
A Lenzi, MG Genton
Towards black-box parameter estimation
A Lenzi, H Rue
arXiv preprint arXiv:2303.15041, 2023
Detecting large frequency excursions in the power grid with Bayesian decision theory
A Lenzi, J Bessac, M Anitescu
IEEE Open Access Journal of Power and Energy 9, 66-75, 2022
Spatio-temporal modelling for short term wind power forecasts. Why, when and how.
A Lenzi, I Steinsland, P Pinson
EGU General Assembly Conference Abstracts, 3633, 2017
Automatic cross-validation in structured models: Is it time to leave out leave-one-out?
A Adin, E Krainski, A Lenzi, Z Liu, J Martínez-Minaya, H Rue
arXiv preprint arXiv:2311.17100, 2023
How can statistics help to prevent blackouts?
A Lenzi, M Anitescu
Significance 20 (1), 24-27, 2023
A spatial model for the instantaneous estimation of wind power at a large number of unobserved sites
A Lenzi, G Guillot, P Pinson
Procedia Environmental Sciences 26, 131-134, 2015
A Lenzi, I Steinsland, P Pinson
Benefits of spatio-temporal modelling for short term wind power forecasting …, 0
How statistics keeps the lights on
A Lenzi, M Anitescu
Significance 19 (6), 28-30, 2022
Systemet kan inte utföra åtgärden just nu. Försök igen senare.
Artiklar 1–20