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Journal of Computational and Graphical Statistics Volume 21, 2012 - Issue 2
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Dimension Reduction

Symbolic Covariance Principal Component Analysis and Visualization for Interval-Valued Data

Jennifer Le-Rademacher
&
Lynne Billard
Pages 413-432 | Received 01 Jul 2010, Published online: 14 Jun 2012

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Austin Workman & Joon Jin Song. (2023) Spatial analysis for interval-valued data. Journal of Applied Statistics 0:0, pages 1-15.
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Tarek Ait-Izem, M.-Faouzi Harkat, Messaoud Djeghaba & Frédéric Kratz. (2018) Sensor fault detection based on principal component analysis for interval-valued data. Quality Engineering 30:4, pages 635-647.
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Cheolwoo Park, Yongho Jeon & Kee-Hoon Kang. (2016) An exploratory data analysis in scale-space for interval-valued data. Journal of Applied Statistics 43:14, pages 2643-2660.
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Aleix Alcacer, Marina Martinez-Garcia & Irene Epifanio. (2024) Ordinal classification for interval-valued data and interval-valued functional data. Expert Systems with Applications 238, pages 122277.
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Emily Chia-Yu Su & Han-Ming Wu. (2023) Dimension reduction and visualization of multiple time series data: a symbolic data analysis approach. Computational Statistics.
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Liang-Ching Lin, Meihui Guo & Sangyeol Lee. (2022) Monitoring photochemical pollutants based on symbolic interval-valued data analysis. Advances in Data Analysis and Classification 17:4, pages 897-926.
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S. Yaser Samadi, L. Billard, Jiin-Huarng Guo & Wei Xu. (2023) MLE for the parameters of bivariate interval-valued model. Advances in Data Analysis and Classification.
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Rodrigo Girão Serrão, M. Rosário Oliveira & Lina Oliveira. (2023) Theoretical derivation of interval principal component analysis. Information Sciences 621, pages 227-247.
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Nour Basha, Costas Kravaris, Hazem Nounou & Mohamed Nounou. (2023) Bayesian-optimized Gaussian process-based fault classification in industrial processes. Computers & Chemical Engineering 170, pages 108126.
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Imen Hamrouni, Hajer Lahdhiri, Khaoula Ben Abdellafou, Ahamed Aljuhani & Okba Taouali. (2022) Anomaly detection for process monitoring based on machine learning technique. Neural Computing and Applications 35:5, pages 4073-4097.
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M. Rosário Oliveira, Margarida Azeitona, António Pacheco & Rui Valadas. (2021) Association measures for interval variables. Advances in Data Analysis and Classification 16:3, pages 491-520.
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Imen Hamrouni, Hajer Lahdhiri, Khaoula Ben Abdellafou, Ahamed Aljuhani, Okba Taouali & Kais Bouzrara. (2022) Anomaly Detection and Localization for Process Security Based on the Multivariate Statistical Method. Mathematical Problems in Engineering 2022, pages 1-11.
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Miguel Carvalho & Gabriel Martos. (2021) Modeling interval trendlines: Symbolic singular spectrum analysis for interval time series. Journal of Forecasting 41:1, pages 167-180.
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Hajer Lahdhiri & Okba Taouali. (2021) Interval valued data driven approach for sensor fault detection of nonlinear uncertain process. Measurement 171, pages 108776.
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Carlos Maté. (2021) Combining Interval Time Series Forecasts. A First Step in a Long Way (Research Agenda). Revista Colombiana de Estadística 44:1, pages 123-157.
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Chouaib Chakour. 2021. Proceedings of the 4th International Conference on Electrical Engineering and Control Applications. Proceedings of the 4th International Conference on Electrical Engineering and Control Applications 803 813 .
Khaled Dhibi, Radhia Fezai, Majdi Mansouri, Abdelmalek Kouadri, Mohamed-Faouzi Harkat, Kais Bouzara, Hazem Nounou & Mohamed Nounou. (2020) A Hybrid Approach for Process Monitoring: Improving Data-Driven Methodologies With Dataset Size Reduction and Interval-Valued Representation. IEEE Sensors Journal 20:17, pages 10228-10239.
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Mohammed Albassam, Nasrullah Khan & Muhammad Aslam. (2020) The W/S Test for Data Having Neutrosophic Numbers: An Application to USA Village Population. Complexity 2020, pages 1-8.
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Mohamed Faouzi Harkat, Majdi Mansouri, Kamaleldin Abodayeh, Mohamed Nounou & Hazem Nounou. (2020) New sensor fault detection and isolation strategy–based interval‐valued data. Journal of Chemometrics 34:5.
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Kadri Umbleja, Manabu Ichino & Hiroyuki Yaguchi. (2020) Improving symbolic data visualization for pattern recognition and knowledge discovery. Visual Informatics 4:1, pages 23-31.
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Mohammed Ziyan Sheriff, Nour Basha, Muhammad Nazmul Karim, Hazem Nounou & Mohamed Nounou. 2020. Fault Detection, Diagnosis and Prognosis. Fault Detection, Diagnosis and Prognosis.
Imen Hamrouni, Hajer Lahdhiri, Khaoula ben Abdellafou & Okba Taouali. (2020) Fault detection of uncertain nonlinear process using reduced interval kernel principal component analysis (RIKPCA). The International Journal of Advanced Manufacturing Technology 106:9-10, pages 4567-4576.
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Han‐Ming Wu, Chiun‐How Kao & Chun‐houh Chen. 2020. Advances in Data Science. Advances in Data Science 49 77 .
Sondes Gharsellaoui, Majdi Mansouri, Mohamed Abdallah Trabelsi, Mohamed-Faouzi Harkat, Shady S. Refaat & Hassani Messaoud. (2020) Interval-Valued Features Based Machine Learning Technique for Fault Detection and Diagnosis of Uncertain HVAC Systems. IEEE Access 8, pages 171892-171902.
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Radhia Fezai, Kamaleldin Abodayeh, Majdi Mansouri, Abdelmalek Kouadri, Mohamed-Faouzi Harkat, Hazem Nounou, Mohamed Nounou & Hassani Messaoud. (2020) Reliable Fault Detection and Diagnosis of Large-Scale Nonlinear Uncertain Systems Using Interval Reduced Kernel PLS. IEEE Access 8, pages 78343-78353.
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Majdi Mansouri, Mohamed-Faouzi Harkat, Hazem N. Nounou & Mohamed N. Nounou. 2020. Data-Driven and Model-Based Methods for Fault Detection and Diagnosis. Data-Driven and Model-Based Methods for Fault Detection and Diagnosis 135 219 .
Jorge Arce Garro & Oldemar Rodríguez Rojas. (2019) Optimized Dimensionality Reduction Methods for Interval-Valued Variables and Their Application to Facial Recognition. Entropy 21:10, pages 1016.
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Amir Massoud Malekfar & Farzad Eskandari. (2019) Assessment and Estimation of a Covariate’s Coefficient in a Particular Interval Model. Iranian Journal of Science and Technology, Transactions A: Science 43:5, pages 2285-2298.
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M.-F. Harkat, M. Mansouri, M. Nounou & H. Nounou. (2019) Fault detection of uncertain nonlinear process using interval-valued data-driven approach. Chemical Engineering Science 205, pages 36-45.
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Elizabeth Ann Maharaj, Paulo Teles & Paula Brito. (2019) Clustering of interval time series. Statistics and Computing 29:5, pages 1011-1034.
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Przemyslaw Grzegorzewski & Martyna Śpiewak. (2019) The sign test and the signed‐rank test for interval‐valued data. International Journal of Intelligent Systems 34:9, pages 2122-2150.
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Harkat M.-F.Mansouri M.Nounou M.N.Nounou H.N.. (2019) Fault detection of uncertain chemical processes using interval partial least squares-based generalized likelihood ratio test. Information Sciences 490, pages 265-284.
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Amir Massoud Malekfar & Farzad Eskandari. (2019) Assessment and Estimation of the Coefficients of a Linear Model for Interval Data. Journal of Statistical Research of Iran 15:2, pages 237-274.
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Chouaib Chakour, Abdelhafid Benyounes & Mahmoud Boudiaf. (2018) Diagnosis of uncertain nonlinear systems using interval kernel principal components analysis: Application to a weather station. ISA Transactions 83, pages 126-141.
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A. Pedro Duarte Silva, Peter Filzmoser & Paula Brito. (2017) Outlier detection in interval data. Advances in Data Analysis and Classification 12:3, pages 785-822.
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Nour Basha, Mohamed Nounou & Hazem Nounou. (2018) Multivariate fault detection and classification using interval principal component analysis. Journal of Computational Science 27, pages 1-9.
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Tarek Ait-Izem, M-Faouzi Harkat, Messaoud Djeghaba & Frédéric Kratz. (2018) On the application of interval PCA to process monitoring: A robust strategy for sensor FDI with new efficient control statistics. Journal of Process Control 63, pages 29-46.
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Pierpaolo D’Urso. (2017) Exploratory multivariate analysis for empirical information affected by uncertainty and modeled in a fuzzy manner: a review. Granular Computing 2:4, pages 225-247.
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J. Le-Rademacher & L. Billard. (2016) Principal component analysis for histogram-valued data. Advances in Data Analysis and Classification 11:2, pages 327-351.
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Nitis Mukhopadhyay. (2017) A Conversation with Lynne Billard. Statistical Science 32:1.
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Pierpaolo D׳Urso & Jacek M. Leski. (2016) Fuzzy c -ordered medoids clustering for interval-valued data. Pattern Recognition 58, pages 49-67.
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Sun Makosso‐Kallyth. (2015) Principal axes analysis of symbolic histogram variables. Statistical Analysis and Data Mining: The ASA Data Science Journal 9:3, pages 188-200.
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A. Calcagnì, L. Lombardi & E. Pascali. (2014) A dimension reduction technique for two-mode non-convex fuzzy data. Soft Computing 20:2, pages 749-762.
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Chengcheng Hao, Yuli Liang & Anuradha Roy. (2015) Equivalency between vertices and centers-coupled-with-radii principal component analyses for interval data. Statistics & Probability Letters 106, pages 113-120.
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Carmela Cappelli, Pierpaolo D'Urso & Francesca Di Iorio. (2015) Regime change analysis of interval-valued time series with an application to PM10. Chemometrics and Intelligent Laboratory Systems 146, pages 337-346.
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Meiling Chen, Huiwen Wang & Zhongfeng Qin. (2014) Principal component analysis for probabilistic symbolic data: a more generic and accurate algorithm. Advances in Data Analysis and Classification 9:1, pages 59-79.
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Tarek AIT IZEM, Wafa BOUGHELOUM, Mohamed Faouzi HARKAT & Messaoud DJEGHABA. (2015) Fault Detection and Isolation Using Interval Principal Component Analysis Methods. IFAC-PapersOnLine 48:21, pages 1402-1407.
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Lynne Billard. 2014. Past, Present, and Future of Statistical Science. Past, Present, and Future of Statistical Science 323 334 .
Asanao Shimokawa, Yohei Kawasaki & Etsuo Miyaoka. (2014) <b>CONSTRUCTION OF REGRESSION TREES ON INTERVAL-VALUED SYMBOLIC VARIABLES </b>. Journal of the Japanese Society of Computational Statistics 27:1, pages 61-79.
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J. Le-Rademacher & L. Billard. (2013) Principal component histograms from interval-valued observations. Computational Statistics 28:5, pages 2117-2138.
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L. Billard & J. Le-Rademacher. (2012) Principal component analysis for interval data. Wiley Interdisciplinary Reviews: Computational Statistics 4:6, pages 535-540.
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