Antonio D'Ambrosio
Antonio D'Ambrosio
Associate Professor, Department of Economics and Statistics University of Naples Federico II
Verified email at - Homepage
Cited by
Cited by
Analysis of powered two-wheeler crashes in Italy by classification trees and rules discovery
A Montella, M Aria, A D’Ambrosio, F Mauriello
Accident Analysis & Prevention 49, 58-72, 2012
Simulator evaluation of drivers’ speed, deceleration and lateral position at rural intersections in relation to different perceptual cues
A Montella, M Aria, A D’Ambrosio, F Galante, F Mauriello, M Pernetti
Accident Analysis & Prevention 43 (6), 2072-2084, 2011
Traffic calming along rural highways crossing small urban communities: Driving simulator experiment
F Galante, F Mauriello, A Montella, M Pernetti, M Aria, A D’Ambrosio
Accident Analysis & Prevention 42 (6), 1585-1594, 2010
Data-mining techniques for exploratory analysis of pedestrian crashes
A Montella, M Aria, A D'Ambrosio, F Mauriello
Transportation research record 2237 (1), 107-116, 2011
Accurate algorithms for identifying the median ranking when dealing with weak and partial rankings under the Kemeny axiomatic approach
R Amodio, S., D'Ambrosio A., Siciliano
European Journal of Operational Research, 2015
A recursive partitioning method for the prediction of preference rankings based upon kemeny distances
A D’Ambrosio, WJ Heiser
psychometrika 81 (3), 774-794, 2016
Perceptual measures to influence operating speeds and reduce crashes at rural intersections: driving simulator experiment
A Montella, M Aria, A D'Ambrosio, F Galante, F Mauriello, M Pernetti
Transportation Research Record 2149 (1), 11-20, 2010
Clustering and prediction of rankings within a Kemeny distance framework
WJ Heiser, A D’Ambrosio
Algorithms from and for Nature and Life, 19-31, 2013
A P-spline based clustering approach for portfolio selection
C Iorio, G Frasso, A D’Ambrosio, R Siciliano
Expert Systems with Applications 95, 88-103, 2018
Two algorithms for finding optimal solutions of the Kemeny rank aggregation problem for full rankings
A D'Ambrosio, S Amodio, C , Iorio
Electronic Journal of Applied Statistical Analysis 8 (2), 198-212, 2015
Accurate tree-based missing data imputation and data fusion within the statistical learning paradigm
A D’Ambrosio, M Aria, R Siciliano
Journal of classification 29 (2), 227-258, 2012
Parsimonious time series clustering using p-splines
C Iorio, G Frasso, A D’Ambrosio, R Siciliano
Expert Systems with Applications 52, 26-38, 2016
Robust tree-based incremental imputation method for data fusion
A D’Ambrosio, M Aria, R Siciliano
International Symposium on Intelligent Data Analysis, 174-183, 2007
A differential evolution algorithm for finding the median ranking under the Kemeny axiomatic approach
A D’Ambrosio, G Mazzeo, C Iorio, R Siciliano
Computers & Operations Research 82, 126-138, 2017
ConsRank, compute the median ranking (s) according to the Kemeny’s axiomatic approach. R package version 2.0. 0
A D’Ambrosio, S Amodio, G Mazzeo
On concurvity in nonlinear and nonparametric regression models
S Amodio, M Aria, A D’Ambrosio
Statistica 74 (1), 85-98, 2014
Regression trees for multivalued numerical response variables
A D’Ambrosio, M Aria, C Iorio, R Siciliano
Expert Systems with Applications 69, 21-28, 2017
Conditional classification trees by weighting the Gini impurity measure
A D’Ambrosio, VA Tutore
New perspectives in statistical modeling and data analysis, 273-280, 2011
Posterior prediction modelling of optimal trees
R Siciliano, M Aria, A D’Ambrosio
COMPSTAT 2008, 323-334, 2008
Tree-based methods for data editing and preference rankings
A D’ambrosio
PhD thesis, Department of Mathematics and Statistics, University of Naplesá…, 2008
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