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1 Contributo su Rivista 11315
- N.D. 0
- 1.1 Articolo in rivista 10630
- 1.2 Recensione in rivista 357
- 1.3 Scheda bibliografica 12
- 1.4 Nota a sentenza 74
- 1.5 Abstract in rivista 214
- 1.6 Traduzione in rivista 28

2 Contributo in Volume 6341
- 2.1 Contributo in volume (Capitolo o Saggio) 5745
- 2.2 Prefazione/Postfazione 86
- 2.3 Breve introduzione 43
- 2.4 Voce (in dizionario o enciclopedia) 291
- 2.5 Traduzione in volume 15
- 2.6 Recensione in volume 3
- 2.7 Schede di catalogo 158

3 Libro 1322
- 3.1 Monografia o trattato scientifico 1223
- 3.2 Concordanza 0
- 3.3 Indice 1
- 3.4 Bibliografia 3
- 3.5 Edizione critica 17
- 3.6 Pubblicazione di fonti inedite 5
- 3.7 Commento scientifico 1
- 3.8 Traduzione di libro 72

4 Contributo in Atti di Convegno (Proceeding) 6197
- 4.1 Contributo in Atti di convegno 5909
- 4.2 Abstract in Atti di convegno 262
- 4.3 Poster 26

5 Altro 995
- 5.01 Composizione 1
- 5.02 Disegno 0
- 5.03 Design 0
- 5.04 Performance 0
- 5.05 Esposizione 0
- 5.06 Mostra 1
- 5.07 Manufatto 0
- 5.08 Prototipo d'arte e relativi progetti 0
- 5.09 Cartografia 0
- 5.10 Banca dati 32
- 5.11 Software 0
- 5.12 Altro 927
- 5.13 Progetto architettonico 1
- 5.14 Rapporto di ricerca 33

6 Brevetti 42
- 6.1 Brevetto 42

7 Curatele 752
- 7.1 Curatela 752

8 Tesi di dottorato 98
- 8.1 Tesi di dottorato 98

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A Stacked Machine Learning Algorithm for Multi-Step Ahead Prediction of Soil Moisture

A trustworthy assessment of soil moisture content plays a significant role in irrigation planning and in controlling various natural disasters such as floods, landslides, and droughts. Various machine learning models (MLMs) have been used to increase the accuracy of soil moisture content prediction. The present investigation aims to apply MLMs with novel structures for the estimation of daily volumetric soil water content, based on the stacking of the multilayer perceptron (MLP), random fores...

Exercise Evaluation and Prescription

Heterogeneity in Risk Aversion and Risk Sharing Regressions

Heterogeneity in risk attitudes, if not properly accounted for, may induce a bias on the income coefficient of standard consumption insurance regressions. We show that, extending the theoretical analysis and empirical findings in Schulofer-Wohl (2011), the sign of the bias is ambiguous, and depends on cycle-related variables and on the covariances of both aggregate and idiosyncratic risk with individual risk aversion.

Individual preferences for public education spending: does personal income matter?

Standard redistributive arguments suggest that the impact of household income on preferences for public education spending should be negative, because wealthier families are likely to oppose the redistributive effect of public funding. However, the empirical evidence does not confirm this prediction. This paper addresses this ‘puzzle’ by focusing on the role of the inclusiveness of the education system and the allocation of public spending between tiers of education in shaping the impact of i...

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UNICLAM: [27062] Home page macrotipologia

Prodotti recenti

A Stacked Machine Learning Algorithm for Multi-Step Ahead Prediction of Soil Moisture

Exercise Evaluation and Prescription

Heterogeneity in Risk Aversion and Risk Sharing Regressions

Individual preferences for public education spending: does personal income matter?

Riducibilità ex officio della penale manifestamente eccessiva

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