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Alfonso Iodice D'Enza
Title
Cited by
Cited by
Year
Principal component analysis
M Greenacre, PJF Groenen, T Hastie, AI d’Enza, A Markos, E Tuzhilina
Nature Reviews Methods Primers 2 (1), 100, 2022
18312022
The endoscopic endonasal approach for the management of craniopharyngiomas: a series of 103 patients
LM Cavallo, G Frank, P Cappabianca, D Solari, D Mazzatenta, A Villa, ...
Journal of neurosurgery 121 (1), 100-113, 2014
2972014
Distance‐based clustering of mixed data
M Van de Velden, A Iodice D'Enza, A Markos
Wiley Interdisciplinary Reviews: Computational Statistics 11 (3), e1456, 2019
139*2019
Sellar repair with fibrin sealant and collagen fleece after endoscopic endonasal transsphenoidal surgery
P Cappabianca, LM Cavallo, V Valente, I Romano, AI D'Enza, F Esposito, ...
Surgical neurology 62 (3), 227-233, 2004
1282004
Cluster correspondence analysis
M Van de Velden, AI D’Enza, F Palumbo
Psychometrika 82 (1), 158-185, 2017
1182017
Beyond tandem analysis: Joint dimension reduction and clustering in R
A Markos, AI D'Enza, M van de Velden
Journal of Statistical Software 91, 1-24, 2019
952019
Endoscopic endonasal transsphenoidal removal of recurrent and regrowing pituitary adenomas: experience on a 59-patient series
LM Cavallo, D Solari, A Tasiou, F Esposito, M de Angelis, AI D'Enza, ...
World neurosurgery 80 (3-4), 342-350, 2013
862013
The “suprasellar notch,” or the tuberculum sellae as seen from below: definition, features, and clinical implications from an endoscopic endonasal perspective
M de Notaris, D Solari, LM Cavallo, AI D'Enza, J Enseñat, J Berenguer, ...
Journal of neurosurgery 116 (3), 622-629, 2012
682012
Iterative factor clustering of binary data
A Iodice D’Enza, F Palumbo
Computational Statistics 28 (2), 789-807, 2013
412013
Multiple correspondence analysis for the quantification and visualization of large categorical data sets
AI D’Enza, M Greenacre
Advanced statistical methods for the analysis of large data-sets, 453-463, 2011
382011
Publisher Correction: Principal component analysis (Nature Reviews Methods Primers,(2022), 2, 1,(100), 10.1038/s43586-022-00184-w)
M Greenacre, PJF Groenen, T Hastie, AI D’Enza, A Markos, E Tuzhilina
Nature Reviews Methods Primers 3 (1), 22, 2023
252023
Special feature: dimension reduction and cluster analysis
M van de Velden, AI D’Enza, M Yamamoto
Behaviormetrika 46 (2), 239-241, 2019
162019
’Enza, A., Markos, A., & Tuzhilina, E.(2022). Principal component analysis
M Greenacre, P Groenen, T Hastie, D Iodice
Nature Reviews Methods Primers 2 (1), 100, 0
15
’Enza A, Markos A
M Van de Velden, D Iodice
Distance-based clustering of mixed data. WIRE Comput Stat 11 (3), e1456, 2019
132019
’Enza A, Van de Velden M (2019). clustrd: Methods for Joint Dimension Reduction and Clustering
A Markos, D Iodice
R package version 1 (0), 0
13
Predicting the early visual outcomes in sellar-suprasellar lesions compressing the chiasm: the role of SD-OCT series of 20 patients operated via endoscopic endonasal approach
D Solari, G Cennamo, F Amoroso, F Frio, P Donna, AI D'Enza, ...
Journal of neurosurgical sciences 66 (4), 362-370, 2022
112022
Exploratory data analysis leading towards the most interesting simple association rules
AI D’enza, F Palumbo, M Greenacre
Computational Statistics & Data Analysis 52 (6), 3269-3281, 2008
112008
A general framework for implementing distances for categorical variables
M Van De Velden, AI D’Enza, A Markos, C Cavicchia
Pattern Recognition 153, 110547, 2024
102024
On joint dimension reduction and clustering of categorical data
A Iodice D’Enza, M Van de Velden, F Palumbo
Analysis and modeling of complex data in behavioral and social sciences, 161-169, 2014
102014
The idm package: incremental decomposition methods in R
AI D'Enza, A Markos, D Buttarazzi
Journal of Statistical Software 86, 1-24, 2018
72018
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Articles 1–20