Selected Publications (peer reviewed)

1.     D. De Canditiis and M. Pensky “Estimation of delta-contaminated density of the random intensity   of Poisson data” Electronic Journal of Statistics , (2015)

 

2.     M. C. Basile, V. Bruni, F. Buccolini, D. De Canditiis, S. Tagliaferri, and D. Vitulano,  "Automatic and Noninvasive Indoor Air Quality Control in HVAC Systems," Journal of Industrial Mathematics, vol. 2016, ID 9674387, (2016)

 

3.     C. Angelini, D. De Canditiis and I. De Feis “Computational approaches for isoform detection and estimation: good and bad news” BMC Bioinformatics, 15:135 (2014)

 

4.     D. De Canditiis “A frame based shrinkage procedure for fast oscillating functions”  Computational Statistics & Data Analysis Vol. 75, pag.142-150 (2014)

 

5.     V. Bruni, D. De Canditiis and D. Vitulano Speed-up of Video Enhancement based on Human Perception”  in Signal Image and Video processing  (2012).

 

6.     C. Angelini, D. De Canditiis and M. Pensky Clustering time-course microarray data using functional Bayesian infinite mixture-modelJournal of Applied Statistics 39, pag.129-149 (2012).

 

7.     V. Bruni, D. De Canditiis and D. Vitulano Time-scale energy based analysis of contours of real-world shapesMathematics and Computers in Simulation (2010). 

 

8.     V. Bruni, D. De Canditiis and D. Vitulano Local Sorting for Adaptive Signal RegularizationIEEE Signal Processing Letters (2010) vol. 17 pp 691 - 694

 

9.     V. Bruni, D. De Canditiis and D. Vitulano Phase Information and Space Filling Curves in Noisy Motion Estimation  IEEE Transactions on Image Processing. Vol. 18(7), pag. 1660-1664, (2009).

 

10.  C. Angelini, D. De Canditiis and M. Pensky " Bayesian models for the two-sample time-course microarray experiments" Computational Statistics & Data Analysis Vol. 53:1547-1565 (2009).

 

11.  C.Angelini, L. Cutillo, D. De Canditiis, M. Mutarelli, and M. PenskyBATS: a Bayesian user-friendly software for Analyzing Time Series microarray experimentsBMC Bioinformatics Vol 9:415 (2008). 

 

12.  C. Angelini, D. De Canditiis, M. Mutarelli, and M. Pensky "A bayesian approach to estimation and testing in time-course microarray experiments" Statistical Applications in Genetics and Molecular Biology, Vol 6 n°4 (2007).

 

13.  M.Pensky, B.Vidakovic and D.De Canditiis ,“Bayesian  decision theoretic scale-adaptive estimation of a log-spectral densityStatistica Sinica Vol 17 n.2, pag 653-666, (2007).

 

14.  F.Abramovich, C. Angelini and D. De Canditiis Pointwise optimality of bayesian wavelet estimators dataAnnals of the Institute of Statistical Mathematics Vol.59  (2007).

 

15.  D. De Canditiis and I. De FeisPointwise convergence of fourier regularization for smoothing data. Journal of Computational and Applied Mathematics, pag 540-552, (2006).

 

16.  D. De Canditiis e M. Pensky  Simultaneous wavelet deconvolution in periodic settingScandinavian Journal of Statistics, Vol 33, issue 2,  pag 293-306 (2006).

 

17.  D. De Canditiis “Pointwise bayesian credible intervals for the regularized linear wavelet estimators. Communications in Statistics: Simulation and Computation Vol 35 n°1, pag 61-77  (2006).

 

18.  D. De Canditiis  e M. Pensky contribution to “Discussion  on the meeting on statistical approaches to inverse problem”  Journal of the Royal Statistical Society B, 66 Part 3, pag 627-652  (2004).

 

19.  D. De Canditiis e T. SapatinasTesting for additivity and joint effect in bivariate nonparametric regression models using fourier and wavelet methods. Statistic and Computing 14, pag 235-249, (2004).

 

20.  D. De Canditiis e B. VidakovicWavelet bayesian block shrinkage via mixture of Normal-Inverse-GammaJournal of Computational and Graphical Statistics 13, N. 2,  pag 383-398 (2004).

 

21.  C. Angelini D. De Canditiis e F. Leblanc “Wavelet regression estimation in non parametric mixed effect modelsJournal of Multivariate Analysis 85  issue 2,  pag 267-291, (2003) 

 

22.  G. Katul C. Angelini D. De Canditiis B. Vidakovic T.D. Albertson and U. Amato “Are the effect of large scale flow conditions really lost through the turbolent cascadeGeophisical Research Letters 30 N.4, pag 1164-1168, (2003).

 

23.  C. Angelini e D. De Canditiis “Pointwise convergence of the wavelet regularization estimator  Communication in Statistics: Theory and Method Vol. 31, issue 9, (2002).

 

24.  U. Amato e D. De Canditiis “Convergence in probability of the Mallows and GCV wavelet and Fourier regularization method  Statistics and Probability Letters 54, pag 325-329, (2001).

 

25.  C. Angelini e D. De Canditiis “Fourier frequency adaptive regularization for smoothing data,  Journal of Computational and Applied Mathematics 115, pag.35-50, (2000).

 

26.  U. Amato, D. De Canditiis e C. Serio “Effect of apodization on the retrieval  of geophysical parameters from fourier trasform spectrometersApplied Optics vol.37 No.27, pag.6537-6543, (1998)

 

Papers on proceeding and book’s chapter (peer reviewed)

·       M. Basile, F. Buccolini, V. Bruni, D. De Canditiis, S. Tagliaferri, D. VitulanoNon invasive indoor air quality control through HVAC systems cleaning state” in Proceedings of the International Conference on Sustainable Housing Planning, Management and Usability; eBook ISBN: 978-989-8734-21-1

·       D. De Canditiis “Generalizing Wiener estimator to frame operators” MASCOT2015 IMACS Series in Computational and Applied Mathematics ISSN 1098-870X  

 

·       C.Angelini, D. De Canditiis, M. PenskyBayesian methods for Time-course microarray analysis: from genes detection to clustering. In Studies in Theoretical and Applied Statistics, Springer, pp.47-56. (2012).

 

·       C. Angelini, D. De Canditiis and M. Pensky  “Estimation and testing in time-course microarray experimentsCh. 7 in Bayesian Modeling in Bioinformatics eds. Dipak K. Dey, Samiran Ghosh, Bani K. Mallick, 2010, ISBN: 978-1-4200701-7-0  Chapman & Hall/CRC Biostatistics Series.

 

·       C. Angelini, D. De Canditiis, M. PenskyBayesian models for the analysis of multi-sample time-course microarray experiments. Lecture Notes in Bioinformatics (2012).  In statistical methods for the analysis of large data sets. Book of short paper of the Italian Statistical Society, Invited paper by the Royal Statistical Society, Pescara 23-25 Sept 2009, pp 19-23,  ISBN: 978-88-6129-425-7

 

·       V. Bruni, D. De Canditiis, D. Vitulano, "Human Visual System for Complexity Reduction of Image and Video Restoration," Lecture Notes in Computer Science, 2011, Volume 6855/2011, 261-268.

 

·        V. Bruni, D. De Canditiis, D. Vitulano, "Time scale descriptors of highly oscillating contours”  proc. of MASCOT 2009, IMACS Series in Computational and Applied Mathematics ISSN 1098-870X

 

·        V. Bruni, D. De Canditiis and D. Vitulano  “Phase based motion estimation for noisy sequencesSystem Signal and Image Processing IEEE IWSSIP pag 399-402, Maribor, Slovenia, (2007).

 

·       V. Bruni, D. De Canditiis and D. VitulanoFast motion estimation using spatio temporal filteringLecture Notes in Computer Science (ICIAR 2006)  Vol 4141 pag. 755-766, Póvoa de Varzim, Portogallo(2006).

 

·       U. Amato, D. De Canditiis and C. Serio “New quasi analytical method for evaluating the coefficients of a linearized  RTE modelSatellite Remote Sensing of Clouds and the Atmosphere IISPIE Vol 3220, pag.148-155,London, UK (1998).

 

·       U. Amato, D. De Canditiis, I. De Feis, C. Serio, and H. Kobayashi “The CHIARA inversion algorithm for IMG International Geoscience and Remote Sensing Symposium  (IGARSS) pag. 2538-2540, Seattle, USA, (1998).

 

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