| Titolo |
Pubblicato in |
Anno |
| A Two-Part Beta Regression Model with Measurement Error |
Pollice, A., Mariani, P. (eds) Methodological and Applied Statistics and Demography III. SIS 2024. Italian Statistical Society Series on Advances in Statistics |
2025 |
| A two-part beta regression with mismeasured dependent variable for modeling quasi-formal employment in Europe |
ASTA ADVANCES IN STATISTICAL ANALYSIS |
2025 |
| Estimating the size of undeclared work from partially misclassified survey data via the Expectation–Maximization algorithm |
JOURNAL OF THE ROYAL STATISTICAL SOCIETY. SERIES C, APPLIED STATISTICS |
2024 |
| A pre-whitening with block-bootstrap cross-correlation procedure for temporal alignment of data sampled by eddy covariance systems |
ENVIRONMENTAL AND ECOLOGICAL STATISTICS |
2024 |
| X-BASE: the first terrestrial carbon and water flux products from an extended data-driven scaling framework, FLUXCOM-X |
BIOGEOSCIENCES |
2024 |
| A dynamic causal modeling of the second outbreak of COVID-19 in Italy |
ASTA. ADVANCES IN STATISTICAL ANALYSIS |
2023 |
| Time lag detection between raw eddy-covariance data by prewhitening and cross-correlation analysis |
EGU General Assembly 2023GEOPHYSICAL RESEARCH ABSTRACTS |
2023 |
| From raw data to standardized, fully corrected, quality ensured eddy covariance flux data: the ICOS Ecosystem processing pipeline |
EGU General Assembly 2023GEOPHYSICAL RESEARCH ABSTRACTS |
2023 |
| On time lag detection between time series sampled by eddy covariance systems |
Book of short papers - GRASPA 2023 |
2023 |
| Tackling misclassification in surveys about undeclared work via the EM algorithm |
IES 2023 - Statistical Methods for Evaluation and Quality: Techniques, Technologies and Trends (T3) BOOK OF SHORT PAPERS |
2023 |
| The Importance of Prewhitening in Time-Lag Detection between Raw, High-Frequency, Eddy-Covariance Data |
AGU Abstracts |
2022 |
| A performance evaluation of despiking algorithms for eddy-covariance data |
SCIENTIFIC REPORTS |
2021 |
| Gap-filling eddy covariance methane fluxes: Comparison of machine learning model predictions and uncertainties at FLUXNET-CH4 wetlands |
AGRICULTURAL AND FOREST METEOROLOGY |
2021 |
| Author Correction: The FLUXNET2015 dataset and the ONEFlux processing pipeline for eddy covariance data |
SCIENTIFIC DATA |
2021 |
| Comparison of different multivariate calibrations and ensemble methods for estimating selected soil properties with vis-NIR reflectance spectroscopy |
Metodi e analisi statistiche |
2020 |
| Geostatistical analysis of soil reflectance spectra for field-scale digital soil mapping. A case study |
Metodi e Analisi Statistiche 2020 |
2020 |
| Case study: ENVRI science demonstrators with D4Science |
Towards Interoperable Research Infrastructures for Environmental and Earth Sciences |
2020 |
| The FLUXNET2015 dataset and the ONEFlux processing pipeline for eddy covariance data |
SCIENTIFIC DATA |
2020 |
| A robust data cleaning procedure for eddy covariance flux measurements |
BIOGEOSCIENCES |
2020 |
| A Monte Carlo study on learning algorithms for predicting student dropouts in higher education |
|
2019 |
