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Detecting and estimating changes in dependent functional data

John A.D. Aston, Claudia Kirch
2012 Journal of Multivariate Analysis  
Change point detection in sequences of functional data is examined where the functional observations are dependent.  ...  Estimators of the change point location are derived from the test statistics and theoretical properties are investigated.  ...  Aston was also supported by the Engineering and Physical Sciences Research Council (UK) through the CRiSM programme grant and the project grant EP/H016856/1, and thanks SAMSI for hosting the author during  ... 
doi:10.1016/j.jmva.2012.03.006 fatcat:re4gou4rufgnpnqonkgoe35srq

Editorial for the special issue: Change point detection

Georgy Sofronov, Martin Wendler, Volkmar Liebscher
2020 Statistical Papers  
It is of particular interest to be able to detect systematic changes, so-called change points, in the underlying structure despite the random fluctuations and to estimate the locations of these changes  ...  For example, change points in DNA sequences can indicate the location of genes and other functional elements.  ...  Article (Maciak et al. 2020) introduces detection procedures for a change in means of panel data are proposed, where the considered model allows for mutually dependent and generally nonstationary panels  ... 
doi:10.1007/s00362-020-01199-9 fatcat:ugvuzmrdqnav7lzwwrjxwiqr6u

A Multivariate Local Rational Modeling Approach for Detection of Structural Changes in Test Vehicles

T. McKelvey, D. McKelvey, P. Nordberg
2021 IFAC-PapersOnLine  
A data driven structural change detection method is described and evaluated where the data are acceleration and force measurements from a mechanical structure in the form of a vehicle.  ...  When new data is available, the monitoring algorithm re-estimates the non-parametric frequency function and uses a test statistic based on the statistical distance to detect possible change.  ...  When new data is available, the monitoring algorithm re-estimates the non-parametric frequency function and uses a test statistic based on the statistical distance to detect possible change.  ... 
doi:10.1016/j.ifacol.2021.08.338 fatcat:ifukluufbncvzdmw6snov4wkm4

Dynamic Functional Connectivity Change-Point Detection With Random Matrix Theory Inference

Jaehee Kim, Woorim Jeong, Chun Kee Chung
2021 Frontiers in Neuroscience  
To study the dynamic nature of brain activity, functional magnetic resonance imaging (fMRI) data is useful including some temporal dependencies between the corresponding neural activity estimates.  ...  Our study shows the possibility of RMT based approach in DFC change-point problem and in studying the complex dynamic pattern of functional brain interactions.  ...  ACKNOWLEDGMENTS We thank Hyeongrae Lee for helping with preprocessing of resting-state functional data.  ... 
doi:10.3389/fnins.2021.565029 pmid:34017233 pmcid:PMC8129561 fatcat:kklq5sooqvdxzitefu6aeilzp4

Covariate-dependent control limits for the detection of abnormal price changes in scanner data [article]

Youngrae Kim, Sangkyun Kim, Johan Lim, Sungim Lee, Won Son, Heejin Hwang
2020 arXiv   pre-print
We assume that the variance of the log of the price change is a smooth function of the sales volume and estimate the function from previously observed data.  ...  In this paper, we propose a new method to detect abnormal price changes that takes into account an additional covariate, namely, sales volume.  ...  In Section 3, we introduce a procedure to estimate the variance function of the log of the price change and propose a new outlier detection method for use on scanner data.  ... 
arXiv:1912.01832v2 fatcat:6zlxbwan25buphfbur44b7vkja

On the detection of change-points in structural deformation analysis

Hans Neuner, Hansjörg Kutterer
2007 Journal of Applied Geodesy  
This paper deals with an approach for the detection of the change-points in the statistical properties of the data. The method is based on the likelihood function.  ...  In this approach the change-points are estimated by minimising a penalised contrast function.  ...  Detection of Change-Points in Time Series of Observations The scope of the change-point problem is to detect locations where the statistical properties of the system change and to estimate the magnitude  ... 
doi:10.1515/jag.2007.009 fatcat:w5jgelf3a5h4ngxtq7jkdrxv24

Sensor-driven Learning of Time-Dependent Parameters for Prescriptive Analytics

Alexandros Bousdekis, Nikos Papageorgiou, Babis Magoutas, Dimitris Apostolou, Gregoris Mentzas
2020 IEEE Access  
The proposed approach overcomes challenges related to uncertainty derived from user's input, non-stationary data and sensor noise and provides estimates of time-dependent parameters that lead to more reliable  ...  ; however, their estimation poses significant challenges due to the uncertainty derived from inaccurate user input, noisy data, and non-stationarity of real-world data streams.  ...  Non-stationary and noisy data pose significant challenges in accurate and efficient (near) real-time change detection and parameter estimations [23] - [26] .  ... 
doi:10.1109/access.2020.2994933 fatcat:qxggkp4fpnbcdc4w4whcjrvai4

Precise onset detection of human motor responses using a whitening filter and the log-likelihood-ratio test

G.H. Staude
2001 IEEE Transactions on Biomedical Engineering  
The response onset is identified as an abrupt change in the (time-varying) parameters of a statistical process model adapted to the measured signal.  ...  ., in reaction time experiments). This paper presents a new model-based algorithm for computerized response onset detection in kinematic signals (e.g., joint angle).  ...  Wolf for his continuous support and critical comments. He would also like to thank the anonymous reviewers for their valuable suggestions.  ... 
doi:10.1109/10.959325 pmid:11686628 fatcat:hjelcgwsbbcnrnoio7l4wpsrri

Efficient Estimation of Dynamic Density Functions with Applications in Data Streams [chapter]

Abdulhakim Qahtan, Suojin Wang, Xiangliang Zhang
2018 Studies in Big Data  
We demonstrate the usefulness of KDE-Track in visualizing the dynamic density of data streams and change detection.  ...  KDE-Track summarizes the distribution of a data stream by estimating the Probability Density Function (PDF) of the stream at a set of resampling points.  ...  Second, The change detection framework depends mainly on the PCA, which can reflect the changes in linearly dependent data streams.  ... 
doi:10.1007/978-3-319-89803-2_11 fatcat:nfuip3y55nb7hdsilr47c6pbki

Onset Detection in Surface Electromyographic Signals: A Systematic Comparison of Methods

Gerhard Staude, Claus Flachenecker, Martin Daumer, Werner Wolf
2001 EURASIP Journal on Advances in Signal Processing  
But a systematic comparison between methods, which reveals the benefits and the drawbacks of each method compared to the other ones and shows the specific dependence of the detection accuracy on signal  ...  In addition, performance was evaluated on real SEMG data obtained in a reaction time experiment.  ...  In particular, dependence on SNR and ramp duration were studied.  ... 
doi:10.1155/s1110865701000191 fatcat:7vgqg6rv4zgqzoheagb4u42uiy

Detection of the changes in dynamical structures in synchronous neural oscillations from a viewpoint of probabilistic inference [article]

Hiroshi Yokoyama, Keiichi Kitajo
2020 bioRxiv   pre-print
Our proposed method successfully estimated both network couplings and change points of dynamic structures in the numerical and EEG data.  ...  Therefore, the technique that detects changes in dynamical brain structures, which is called "dynamic functional connectivity (DFC) analysis", has become important for the clarification of the crucial  ...  Acknowledgments This research was supported in part by the JSPS KAKENHI (20K19867) and by the Encouraging Grants for Young Researchers at National Institute for Physiological Sciences.  ... 
doi:10.1101/2020.10.13.335356 fatcat:dqbte6o4qfhkjotp5wntedarie

Modeling clustered non-stationary Poisson processes for stochastic simulation inputs

Issac Shams, Saeede Ajorlou, Kai Yang
2013 Computers & industrial engineering  
In many practical cases, probability distributions of the random inputs vary over time in such a way that the functional forms of the distributions and/or their parameters depend on time.  ...  We propose two different methods based on likelihood ratio test and cluster analysis to detect multiple change points when observations follow non-stationary Poisson process with diverse occurrence rates  ...  The cluster analysis can be generalized to detect the presence of one or more changes in the functional form of the data where the first and higher moments of observations vary over time.  ... 
doi:10.1016/j.cie.2013.02.002 fatcat:tyulgxiyj5byjnrllua3q3coly

Constructing a Control Chart Using Functional Data

Miguel Flores, Salvador Naya, Rubén Fernández-Casal, Sonia Zaragoza, Paula Raña, Javier Tarrío-Saavedra
2020 Mathematics  
This study proposes a control chart based on functional data to detect anomalies and estimate the normal output of industrial processes and services such as those related to the energy efficiency domain  ...  Companies providing statistical consultancy services in the fields of energy efficiency; heating, ventilation and air conditioning (HVAC); installation and control; and big data for buildings, have been  ...  The founding sponsors had no role in the design of the study; in the collection, analyses, or interpretation of data; in the writing of the manuscript, or in the decision to publish the results.  ... 
doi:10.3390/math8010058 fatcat:ubcwzq63efbpze7f5q47hovz5m

Discovering Common Change-Point Patterns in Functional Connectivity Across Subjects [article]

Mengyu Dai, Zhengwu Zhang, Anuj Srivastava
2019 arXiv   pre-print
It also provides a graphical representation of estimated FC for stationary subintervals in between the detected change-points.  ...  This paper studies change-points in human brain functional connectivity (FC) and seeks patterns that are common across multiple subjects under identical external stimulus.  ...  HCP is funded in part by WU-Minnesota consortium (PIs: Van Essen and Ugurbil) 1U54MH091657.  ... 
arXiv:1904.12023v1 fatcat:gf6cdcejeja3rokxb2lizk52xu

Inferring spike-timing-dependent plasticity from spike train data

Ian H. Stevenson, Konrad P. Körding
2011 Neural Information Processing Systems  
However, it is often difficult to detect changes in synaptic strength in vivo, since intracellular recordings are experimentally challenging.  ...  First, using a generalized bilinear model with Poisson output we estimate time-varying coupling assuming that all changes are spike-timing-dependent.  ...  An important question for the practical application of these methods is how much data is necessary to detect and accurately estimate modification functions for various effect sizes.  ... 
dblp:conf/nips/StevensonK11 fatcat:zvh6gndxlbgzhm2jhk2jvs3vty
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