Flexible regression and smoothing: using GAMLSS in R MD Stasinopoulos, RA Rigby, GZ Heller, V Voudouris, F De Bastiani CRC Press, 2017 | 640 | 2017 |
The economic growth enigma: Capital, labour and useful energy? R Ayres, V Voudouris Energy Policy 64, 16-28, 2014 | 197 | 2014 |
Modelling skewness and kurtosis with the BCPE density in GAMLSS V Voudouris, R Gilchrist, R Rigby, J Sedgwick, D Stasinopoulos Journal of Applied Statistics 39 (6), 1279-1293, 2012 | 80 | 2012 |
Discussion: A comparison of GAMLSS with quantile regression RA Rigby, DM Stasinopoulos, V Voudouris Statistical Modelling 13 (4), 335-348, 2013 | 42 | 2013 |
The ACEGES laboratory for energy policy: Exploring the production of crude oil V Voudouris, D Stasinopoulos, R Rigby, C Di Maio Energy Policy 39 (9), 5480-5489, 2011 | 42 | 2011 |
The economic growth enigma revisited: The EU-15 since the 1970s V Voudouris, R Ayres, AC Serrenho, D Kiose Energy Policy 86, 812-832, 2015 | 38 | 2015 |
Exploring crude oil production and export capacity of the OPEC Middle East countries K Matsumoto, V Voudouris, D Stasinopoulos, R Rigby, C Di Maio Energy policy 48, 820-828, 2012 | 34 | 2012 |
The distribution toolbox of GAMLSS B Rigby, M Stasinopoulos, G Heller, V Voudouris The GAMLSS Team 261, 2014 | 31 | 2014 |
Towards a unifying formalisation of geographic representation: the object–field model with uncertainty and semantics V Voudouris International Journal of Geographical Information Science 24 (12), 1811-1828, 2010 | 29 | 2010 |
Potential impact of unconventional oil resources on major oil-producing countries: scenario analysis with the ACEGES model K Matsumoto, V Voudouris Natural Resources Research 24, 107-119, 2015 | 26 | 2015 |
Flexible regression and smoothing: The GAMLSS packages in R M Stasinopoulos, B Rigby, V Voudouris, G Heller, F De Bastiani GAMLSS for Statistical Modelling. GAMLSS for Statistical Modeling, 2015 | 25 | 2015 |
Exploring the production of natural gas through the lenses of the ACEGES model V Voudouris, K Matsumoto, J Sedgwick, R Rigby, D Stasinopoulos, ... Energy Policy 64, 124-133, 2014 | 25 | 2014 |
Package ‘gamlss’ M Stasinopoulos, B Rigby, V Voudouris, C Akantziliotou, M Enea, D Kiose Dist’2020Available online: http://www. gamlss. org (accessed on 16 July 2021), 2024 | 18 | 2024 |
The ACEWEM framework: An integrated agent-based and statistical modelling laboratory for repeated power auctions D Kiose, V Voudouris Expert Systems with Applications 42 (5), 2731-2748, 2015 | 16 | 2015 |
Global energy policy and security W Leal Filho, V Voudouris Springer, 2013 | 16 | 2013 |
Towards a conceptual synthesis of dynamic and geospatial models: fusing the agent-based and Object–Field models V Voudouris Environment and Planning B: Planning and Design 38 (1), 95-114, 2011 | 15 | 2011 |
Capturing and representing conceptualization uncertainty interactively using object-fields V Voudouris, P Fisher, J Wood Progress in Spatial Data Handling, 755-770, 2006 | 10 | 2006 |
Oil scenarios for long-term business planning: Royal Dutch Shell and generative explanation, 1960-2010 M Jefferson, V Voudouris | 8 | 2011 |
Collaborative geovisualization: object-field representations with semantic and uncertainty information V Voudouris, J Wood, P Fisher On the Move to Meaningful Internet Systems 2005: OTM 2005 Workshops, 1056-1065, 2005 | 7 | 2005 |
gamlss. dist: Distributions to be used for GAMLSS modelling. R package version 4.3-0 M Stasinopoulos, B Rigby, C Akantziliotou, G Heller, R Ospina, N Motpan, ... | 6 | 2014 |