Yavuz Selim BALCIOĞLU & Kültigin AKÇİN. (2023) Assessing the Surge in COVID-19-Related Cyberbullying on Twitter: A Generalized Additive Model Approach. OPUS Journal of Society Research.
Crossref
Karim Atashgar & Mahnaz Boush. (2023) A convolutional neural network to identify the change point of a multistage process profile with cascade property. International Journal of Quality & Reliability Management.
Crossref
Ryo Nezaki & Hideki Nagatsuka. (2023) New Anomaly Detection Method based on the Multivariate Generalized Pareto Distributions. Total Quality Science 8:2, pages 89-99.
Crossref
Aysegul Erem & Tahir Mahmood. (2023) A bivariate CUSUM control chart based on exceedance statistics. Quality and Reliability Engineering International 39:4, pages 1172-1191.
Crossref
Ali Salmasnia, Mohammadreza Mohabbati, Mohammad Reza Maleki & Maryam Kiani Anbohi. (2023) A two-stage model for change point detection in large-scale weighted directed social networks using a MEWMA chart. Social Network Analysis and Mining 13:1.
Crossref
Krunal Sachdev, Hadeer S. Saad, Issa Traore, Karim Ganame & Oussama Boudar. 2023. Artificial Intelligence for Cyber-Physical Systems Hardening. Artificial Intelligence for Cyber-Physical Systems Hardening
101
121
.
Yicheng Kang. (2022) Statistical quality control using image intelligence: A sparse learning approach. Naval Research Logistics (NRL) 69:7, pages 996-1008.
Crossref
Luca Frittoli, Diego Carrera & Giacomo Boracchi. (2022) Nonparametric and Online Change Detection in Multivariate Datastreams Using QuantTree. IEEE Transactions on Knowledge and Data Engineering, pages 1-14.
Crossref
Dongdong Xiang, Wendong Li, Fugee Tsung, Xiaolong Pu & Yicheng Kang. (2021) Fault classification for high‐dimensional data streams: A directional diagnostic framework based on multiple hypothesis testing. Naval Research Logistics (NRL) 68:7, pages 973-987.
Crossref
Luca Frittoli, Diego Carrera & Giacomo Boracchi. 2021. Machine Learning and Knowledge Discovery in Databases. Research Track. Machine Learning and Knowledge Discovery in Databases. Research Track
421
436
.
Chiwoo Park & Yu DingChiwoo Park & Yu Ding. 2021. Data Science for Nano Image Analysis. Data Science for Nano Image Analysis
241
275
.
Anne R. Driscoll, William H. Woodall & Changliang Zou. 2021. Frontiers in Statistical Quality Control 13. Frontiers in Statistical Quality Control 13
3
12
.
Ali Salmasnia, Mohammadreza Mohabbati & Mohammadreza Namdar. (2019) Change point detection in social networks using a multivariate exponentially weighted moving average chart. Journal of Information Science 46:6, pages 790-809.
Crossref
Sayantan Banerjee & Kousik Guhathakurta. (2020) Change‐point analysis in financial networks. Stat 9:1.
Crossref
Daniele Zambon, Cesare Alippi & Lorenzo Livi. (2019) Change-Point Methods on a Sequence of Graphs. IEEE Transactions on Signal Processing 67:24, pages 6327-6341.
Crossref
Longcheen Huwang, Li‐Wei Lin & Cheng‐Ting Yu. (2019) A spatial rank–based multivariate EWMA chart for monitoring process shape matrices. Quality and Reliability Engineering International 35:6, pages 1716-1734.
Crossref
Muhammad Aslam, G. Rao, Ali AL-Marshadi & Chi-Hyuck Jun. (2019) A Nonparametric HEWMA-p Control Chart for Variance in Monitoring Processes. Symmetry 11:3, pages 356.
Crossref
Peihua Qiu. 2019. Statistical Quality Technologies. Statistical Quality Technologies
3
19
.
Daniele Zambon, Cesare Alippi & Lorenzo Livi. (2018) Concept Drift and Anomaly Detection in Graph Streams. IEEE Transactions on Neural Networks and Learning Systems 29:11, pages 5592-5605.
Crossref
Shuguang He, Wei Jiang & Houtao Deng. (2016) A distance-based control chart for monitoring multivariate processes using support vector machines. Annals of Operations Research 263:1-2, pages 191-207.
Crossref
Li Bu, Cesare Alippi & Dongbin Zhao. (2018) A pdf-Free Change Detection Test Based on Density Difference Estimation. IEEE Transactions on Neural Networks and Learning Systems 29:2, pages 324-334.
Crossref
Yuma Ueno & Yasushi Nagata. Proposal of multivariate control chart using exponentially log-likelihood for detection of change in mean and variability. Proposal of multivariate control chart using exponentially log-likelihood for detection of change in mean and variability.
Longcheen Huwang, Po-Chun Lin, Chih-Hsiang Chang, Li-Wei Lin & Yeu-Shiang Tee. (2017) An EWMA chart for monitoring the covariance matrix of a multivariate process based on dissimilarity index. Quality and Reliability Engineering International 33:8, pages 2089-2104.
Crossref
Juan Du, Xi Zhang & Qingpei Hu. (2017) An Automatic Condition Detection Approach for Quality Assurance in Solar Cell Manufacturing Processes. IEEE Robotics and Automation Letters 2:3, pages 1825-1831.
Crossref
Wendong Li, Xiaolong Pu, Fugee Tsung & Dongdong Xiang. (2017) A robust self-starting spatial rank multivariate EWMA chart based on forward variable selection. Computers & Industrial Engineering 103, pages 116-130.
Crossref
Giada Tacconelli & Manuel Roveri. 2017. Advances in Big Data. Advances in Big Data
100
110
.
Kang-Ping Lu & Shao-Tung Chang. (2016) Detecting change-points for shifts in mean and variance using fuzzy classification maximum likelihood change-point algorithms. Journal of Computational and Applied Mathematics 308, pages 447-463.
Crossref
Shao-Tung Chang & Kang-Ping Lu. (2016) Change-Point Detection for Shifts in Control Charts Using EM Change-Point Algorithms. Quality and Reliability Engineering International 32:3, pages 889-900.
Crossref
Ian Barnett & Jukka-Pekka Onnela. (2016) Change Point Detection in Correlation Networks. Scientific Reports 6:1.
Crossref
Yuan Wang & Yajun Mei. (2015) Large-Scale Multi-Stream Quickest Change Detection via Shrinkage Post-Change Estimation. IEEE Transactions on Information Theory 61:12, pages 6926-6938.
Crossref
Mohammad Reza Maleki, Amirhossein Amiri & Seyed Meysam Mousavi. (2015) Step change point estimation in the multivariate-attribute process variability using artificial neural networks and maximum likelihood estimation. Journal of Industrial Engineering International 11:4, pages 505-515.
Crossref
Kazuya Nishimura, Shun Matsuura & Hideo Suzuki. (2015) Multivariate EWMA control chart based on a variable selection using AIC for multivariate statistical process monitoring. Statistics & Probability Letters 104, pages 7-13.
Crossref
Peihua QiuDongdong Xiang. (2015) Surveillance of cardiovascular diseases using a multivariate dynamic screening system. Statistics in Medicine 34:14, pages 2204-2221.
Crossref
Amirhossein Amiri, Saeed Allahyari & Fatemeh Sogandi. (2014) Identifying the time of a step change in bivariate binomial processes. The International Journal of Advanced Manufacturing Technology 77:1-4, pages 225-233.
Crossref
Ching‐Ren Cheng & Jyh‐Jen Horng Shiau. (2014) A Distribution‐Free Multivariate Control Chart for Phase I Applications. Quality and Reliability Engineering International 31:1, pages 97-111.
Crossref
Pedro A. Marques, Carlos B. Cardeira, Paula Paranhos, Sousa Ribeiro & Helena Gouveia. (2015) Selection of the Most Suitable Statistical Process Control Approach for Short Production Runs: A Decision-Model. International Journal of Information and Education Technology 5:4, pages 303-310.
Crossref
Marziyeh Keshavarz & Biao Huang. (2014) Expectation Maximization method for multivariate change point detection in presence of unknown and changing covariance. Computers & Chemical Engineering 69, pages 128-146.
Crossref
Sylvia R. Esterby. 2014. Wiley StatsRef: Statistics Reference Online. Wiley StatsRef: Statistics Reference Online.
Douglas M. Hawkins, Peihua Qiu & Kokou D. Zamba. 2014. Wiley StatsRef: Statistics Reference Online. Wiley StatsRef: Statistics Reference Online.
M. B. Nigro, S. N. Pakzad & S. Dorvash. (2014) Localized Structural Damage Detection: A Change Point Analysis. Computer-Aided Civil and Infrastructure Engineering 29:6, pages 416-432.
Crossref
Mei Hua Duan & Xue Min Zi. (2014) Distribution-Free Multivariate Control Chart Based on Change-Point Model. Advanced Materials Research 971-973, pages 1435-1439.
Crossref
Víctor G. Tercero-Gómez, Alvaro Cordero-Franco, Angel Pérez-Blanco & Alberto Hernández-Luna. (2014) A Self-Starting CUSUM Chart Combined with a Maximum Likelihood Estimator for the Time of a Detected Shift in the Process Mean. Quality and Reliability Engineering International 30:4, pages 591-599.
Crossref
Robert Garthoff, Vasyl Golosnoy & Wolfgang Schmid. (2014) Monitoring the mean of multivariate financial time series. Applied Stochastic Models in Business and Industry 30:3, pages 328-340.
Crossref
Marziyeh Keshavarz & Biao Huang. (2014) Bayesian and Expectation Maximization methods for multivariate change point detection. Computers & Chemical Engineering 60, pages 339-353.
Crossref
William J. Faithfull & Ludmila I. Kuncheva. 2014. Structural, Syntactic, and Statistical Pattern Recognition. Structural, Syntactic, and Statistical Pattern Recognition
364
373
.
Farzaneh Ahmadzadeh, Jan Lundberg & Thomas Strömberg. (2013) Multivariate process parameter change identification by neural network. The International Journal of Advanced Manufacturing Technology 69:9-12, pages 2261-2268.
Crossref
Ali Movaffagh & Amirhossein Amiri. (2013) Monotonic change point estimation in the mean vector of a multivariate normal process. The International Journal of Advanced Manufacturing Technology 69:5-8, pages 1895-1906.
Crossref
Marziyeh Keshavarz & Biao Huang. (2013) Expectation maximization approach to gross error and change point detection. Expectation maximization approach to gross error and change point detection.
Karim Atashgar. (2012) Identification of the change point: an overview. The International Journal of Advanced Manufacturing Technology 64:9-12, pages 1663-1683.
Crossref
Víctor G Tercero-Gómez, María del Carmen Temblador-Pérez, Mario Beruvides & Alberto Hernández-Luna. (2013) Nonparametric Estimator for the Time of a Step Change in the Trend of Random Walk Models with Drift. Quality and Reliability Engineering International 29:1, pages 43-51.
Crossref
Giacomo Boracchi, Vicenç Puig & Manuel Roveri. 2013. Artificial Intelligence Applications and Innovations. Artificial Intelligence Applications and Innovations
615
624
.
Amirhossein Amiri & Saeed Allahyari. (2011) Change Point Estimation Methods for Control Chart Postsignal Diagnostics: A Literature Review. Quality and Reliability Engineering International 28:7, pages 673-685.
Crossref
Sylvia R. Esterby. 2001. Encyclopedia of Environmetrics. Encyclopedia of Environmetrics.
Changliang Zou, Zhaojun Wang & Fugee Tsung. (2012) A spatial rank‐based multivariate EWMA control chart. Naval Research Logistics (NRL) 59:2, pages 91-110.
Crossref
Karim Atashgar & R. Noorossana. (2010) An integrating approach to root cause analysis of a bivariate mean vector with a linear trend disturbance. The International Journal of Advanced Manufacturing Technology 52:1-4, pages 407-420.
Crossref
Mohammad Hossein Fazel Zarandi & Adel Alaeddini. (2010) A general fuzzy-statistical clustering approach for estimating the time of change in variable sampling control charts. Information Sciences 180:16, pages 3033-3044.
Crossref
Zengrong WangK. C. G. Ong. (2010) Multivariate Statistical Approach to Structural Damage Detection. Journal of Engineering Mechanics 136:1, pages 12-22.
Crossref
István Berkes, Robertas Gabrys, Lajos Horváth & Piotr Kokoszka. (2009) Detecting changes in the mean of functional observations. Journal of the Royal Statistical Society: Series B (Statistical Methodology) 71:5, pages 927-946.
Crossref
Zengrong Wang & K.C.G. Ong. (2009) Structural damage detection using autoregressive-model-incorporating multivariate exponentially weighted moving average control chart. Engineering Structures 31:5, pages 1265-1275.
Crossref
Mehdi Ghazanfari, Adel Alaeddini, Seyed Taghi Akhavan Niaki & Mir‐Bahador Aryanezhad. (2008) A clustering approach to identify the time of a step change in Shewhart control charts. Quality and Reliability Engineering International 24:7, pages 765-778.
Crossref
Maroš Tunák & Aleš Linka. (2008) Directional Defects in Fabrics. Research Journal of Textile and Apparel 12:2, pages 13-22.
Crossref
Douglas M. Hawkins, Peihua Qiu & Kokou D. Zamba. 2007. Encyclopedia of Statistics in Quality and Reliability. Encyclopedia of Statistics in Quality and Reliability.