Suchergebnisse - "Inference from stochastic processes and prediction"

Statistical analysis of incomplete long-range dependent data

Autoren: Palma, W Del Pino, G

Schlagwörter: incomplete data, linear predictor, state space, maximum likelihood, mean square prediction error, long-memory, state space system, 08 Decent Work and Economic Growth, 08 Trabajo decente y crecimiento económico, Inference from stochastic processes and prediction, ARFIMA model

Dateibeschreibung: application/xml

Zugangs-URL: https://zbmath.org/1398451

Ridge regularized estimation of VAR models for inference

Autoren: Giovanni Ballarin

Quelle: Journal of Time Series Analysis. 46:235-257

Schlagwörter: Impulse responses, FOS: Computer and information sciences, inference, Ridge regression, shrinkage estimators (Lasso), impulse responses, 05 social sciences, ddc:519, ridge regularization, 01 natural sciences, Inference from stochastic processes and prediction, Methodology (stat.ME), Time series, auto-correlation, regression, etc. in statistics (GARCH), Inference from stochastic processes, Stationary stochastic processes, 0502 economics and business, vector autoregression, Prediction theory (aspects of stochastic processes), 0101 mathematics, Applications of statistics to economics, Asymptotic properties of parametric estimators, Statistics - Methodology

Dateibeschreibung: application/xml

Zugangs-URL: http://arxiv.org/abs/2105.00860
https://zbmath.org/7986231
https://doi.org/10.1111/jtsa.12737
https://hdl.handle.net/10419/319273
https://madoc.bib.uni-mannheim.de/66742/
https://doi.org/10.1111/jtsa.12737

The fractional neural grey system model and its application

Autoren: Wanli Xie Wen-Ze Wu Zhenguo Xu et al.

Quelle: Applied Mathematical Modelling. 121:43-58

Schlagwörter: predictive model, Time series, auto-correlation, regression, etc. in statistics (GARCH), grey neural network, grey system model, fractional-order accumulation, Inference from stochastic processes and prediction, Artificial neural networks and deep learning

Dateibeschreibung: application/xml

Zugangs-URL: https://zbmath.org/7750198
https://doi.org/10.1016/j.apm.2023.04.028

Machine learning-based conditional mean filter: A generalization of the ensemble Kalman filter for nonlinear data assimilation: Machine learning-based conditional mean filter: a generalization of the ensemble Kalman filter for nonlinear data assimilation

Autoren: Hoang, Truong-Vinh Krumscheid, Sebastian Matthies, Hermann G. et al.

Weitere Verfasser: Hoang, Truong-Vinh Krumscheid, Sebastian Matthies, Hermann G. et al.

Quelle: Foundations of Data Science. 5:56-80

Schlagwörter: ddc:004, FOS: Computer and information sciences, Computer Science - Machine Learning, Learning and adaptive systems in artificial intelligence, Machine Learning (stat.ML), 62M45, 62M20, 65C20, 86-08, Statistics - Computation, 01 natural sciences, Inference from stochastic processes and prediction, Machine Learning (cs.LG), Statistics - Machine Learning, conditional expectation, FOS: Mathematics, Mathematics - Numerical Analysis, Computation (stat.CO), 0105 earth and related environmental sciences, DATA processing & computer science, weather forecast, deep learning, Monte Carlo methods, Numerical Analysis (math.NA), Filtering in stochastic control theory, Neural nets and related approaches to inference from stochastic processes, nonlinear filter, inverse problem

Dateibeschreibung: application/xml; application/pdf

Zugangs-URL: http://arxiv.org/abs/2106.07908

Retrieval of initial condition for Burgers' equation using reduced-order EnKF via POD-based sparse observations

Autoren: Li, Jie Wang, Yuepeng Ren, Zhigang

Quelle: Journal of Industrial and Management Optimization. 19:4222-4232

Schlagwörter: Ill-posedness and regularization problems in numerical linear algebra, KdV equations (Korteweg-de Vries equations), Burgers' equation, data assimilation, QD algorithm, sparse observations, ensemble Kalman filter, Inference from stochastic processes and prediction

Dateibeschreibung: application/xml

A New Approach to the Synthesis of Optimal Smoothing and Prediction Systems: A new approach to the synthesis of optimal smoothing and prediction systems

Autoren: Parzen, Emanuel

Quelle: Mathematical Optimization Techniques ISBN: 9780520319875

Schlagwörter: Signal theory (characterization, reconstruction, filtering, etc.), Time series, auto-correlation, regression, etc. in statistics (GARCH), reproducing kernel Hilbert spaces, Detection theory in information and communication theory, Inference from stochastic processes and prediction

Dateibeschreibung: application/xml

Zugangs-URL: https://zbmath.org/3188843

Uncertainty quantification for DeepONets with ensemble Kalman inversion: Uncertainty quantification for DeepONet with ensemble Kalman inversion

Autoren: Andrew Pensoneault Xueyu Zhu

Quelle: Journal of Computational Physics. 523:113670

Schlagwörter: FOS: Computer and information sciences, Computer Science - Machine Learning, uncertainty quantification, Computer Science - Artificial Intelligence, Numerical solution to inverse problems in abstract spaces, Machine Learning (stat.ML), Numerical Analysis (math.NA), Inference from stochastic processes and prediction, ensemble Kalman inversion, Machine Learning (cs.LG), operator learning, Artificial Intelligence (cs.AI), Statistics - Machine Learning, FOS: Mathematics, Mathematics - Numerical Analysis, Artificial neural networks and deep learning

Dateibeschreibung: application/xml

Zugangs-URL: http://arxiv.org/abs/2403.03444
https://zbmath.org/7986892
https://doi.org/10.1016/j.jcp.2024.113670

Optimal call center forecasting and staffing

Autoren: Sihan Ding Ger Koole

Quelle: Probability in the Engineering and Informational Sciences. 36:254-263

Schlagwörter: call centers, staffing, 0211 other engineering and technologies, forecasting, error measurements, 02 engineering and technology, applied probability, 0101 mathematics, Queues and service in operations research, 01 natural sciences, Queueing theory (aspects of probability theory), Inference from stochastic processes and prediction

Dateibeschreibung: application/xml

Zugangs-URL: https://zbmath.org/7621879
https://doi.org/10.1017/s0269964820000595
https://hdl.handle.net/1871.1/5e7e650a-f208-4b3f-81c1-b7fcc6097e5f
https://research.vu.nl/en/publications/5e7e650a-f208-4b3f-81c1-b7fcc6097e5f
https://doi.org/10.1017/S0269964820000595

Forecasting regular and extreme gold price volatility: The roles of asymmetry, extreme event, and jump: Forecasting regular and extreme gold price volatility: the roles of asymmetry, extreme event, and jump

Autoren: Xiafei Li Xuhui Zhang Guiwu Wei et al.

Quelle: Journal of Forecasting. 40:1501-1523

Schlagwörter: Applications of statistics to actuarial sciences and financial mathematics, extreme events, Time series, auto-correlation, regression, etc. in statistics (GARCH), jump, Statistics of extreme values, tail inference, Financial markets, gold volatility forecasting, 0502 economics and business, 05 social sciences, GARCH-MIDAS, asymmetry, Inference from stochastic processes and prediction

Dateibeschreibung: application/xml

Zugangs-URL: https://zbmath.org/7433700
https://doi.org/10.1002/for.2781
https://onlinelibrary.wiley.com/doi/abs/10.1002/for.2781
https://ideas.repec.org/a/wly/jforec/v40y2021i8p1501-1523.html

A forecasting model for time series based on improvements from fuzzy clustering problem

Autoren: Tai Vovan Luan Nguyenhuynh Thuy Lethithu

Quelle: Annals of Operations Research. 312:473-493

Schlagwörter: Time series, auto-correlation, regression, etc. in statistics (GARCH), model, Classification and discrimination, cluster analysis (statistical aspects), forecast, fuzzy cluster analysis, interpolate, 0202 electrical engineering, electronic engineering, information engineering, Multivariate analysis and fuzziness, 02 engineering and technology, time series, Inference from stochastic processes and prediction

Dateibeschreibung: application/xml

Zugangs-URL: https://link.springer.com/article/10.1007/s10479-021-04041-z

Sparse factor model based on trend filtering

Autoren: Jang Ho Kim Woo Chang Kim Frank J. Fabozzi

Quelle: Annals of Operations Research. 306:321-342

Schlagwörter: Applications of statistics to actuarial sciences and financial mathematics, regularization, factor model, stock market trend, Financial markets, \( \ell_1\) trend filtering, 0502 economics and business, 05 social sciences, 0211 other engineering and technologies, 02 engineering and technology, Inference from stochastic processes and prediction

Dateibeschreibung: application/xml

Zugangs-URL: https://zbmath.org/7462436
https://doi.org/10.1007/s10479-021-04029-9

A PHD-SLAM Method for Mixed Birth Map Information Based on Amplitude Information: A PHD-SLAM method for mixed birth map information based on amplitude information

Autoren: Xinyu Zhang Zijing Zhang Fei Zhang et al.

Quelle: Mathematical Problems in Engineering. 2021:1-13

Schlagwörter: 0209 industrial biotechnology, 02 engineering and technology, Inference from stochastic processes and prediction

Dateibeschreibung: application/xml; text/xhtml

Zugangs-URL: https://downloads.hindawi.com/journals/mpe/2021/8420814.pdf
https://zbmath.org/7342157
https://doi.org/10.1155/2021/8420814
https://downloads.hindawi.com/journals/mpe/2021/8420814.pdf
https://www.hindawi.com/journals/mpe/2021/8420814/
http://downloads.hindawi.com/journals/mpe/2021/8420814.pdf

Joint state estimation for nonlinear state‐space model with unknown time‐variant noise statistics: Joint state estimation for nonlinear state-space model with unknown time-variant noise statistics

Autoren: Ke Li Shunyi Zhao Fei Liu

Quelle: International Journal of Adaptive Control and Signal Processing. 35:498-512

Schlagwörter: 0209 industrial biotechnology, Estimation and detection in stochastic control theory, Bayesian inference, particle approximation, inverse-gamma distribution, state estimation, 02 engineering and technology, nonlinear systems, variational Bayesian inference, Inference from stochastic processes and prediction

Dateibeschreibung: application/xml

Zugangs-URL: https://zbmath.org/7839308
https://doi.org/10.1002/acs.3208
https://dl.acm.org/doi/10.1002/acs.3208
https://onlinelibrary.wiley.com/doi/10.1002/acs.3208

A novel T-S fuzzy particle filtering algorithm based on fuzzy C-regression clustering

Autoren: Liang-qun Li Wang Xiaoli Weixin Xie

Quelle: International Journal of Approximate Reasoning. 117:81-95

Schlagwörter: Classification and discrimination, cluster analysis (statistical aspects), 0202 electrical engineering, electronic engineering, information engineering, particle filtering, Multivariate analysis and fuzziness, fuzzy C-regression clustering, 02 engineering and technology, T-S fuzzy model, Inference from stochastic processes and prediction

Dateibeschreibung: application/xml

Zugangs-URL: https://zbmath.org/7174790
https://doi.org/10.1016/j.ijar.2019.11.005

Filtering of signals transmitted in multichannel from Chandrasekhar and Riccati recursions

Autoren: Nakamori, S. Hermoso, A. Jiménez, J. et al.

Weitere Verfasser: Nakamori, S. Hermoso, A. Jiménez, J. et al.

Quelle: Dehesa. Repositorio Institucional de la Universidad de Extremadura
Universidad de Extremadura (UEX)

Schlagwörter: Signal theory (characterization, reconstruction, filtering, etc.), 1209.07 Teoría de la Distribución y Probabilidad, 1209 Estadística, Computational problems in statistics, Recursive algorithms, 1209.11 Teoría Estocástica y Análisis de Series Temporales, Chandrasekhar-type equations, Ecuaciones tipo Chandrasekhar, Statistical aspects of information-theoretic topics, Inference from stochastic processes and prediction, Signal detection and filtering (aspects of stochastic processes), Algoritmos recursivos

Dateibeschreibung: application/pdf; application/xml

Zugangs-URL: http://hdl.handle.net/10662/17000
https://zbmath.org/2190173

Filtering and fixed-point smoothing from an innovation approach in systems with uncertainty

Autoren: Caballero, R. Hermoso, A. Jiménez, J. et al.

Weitere Verfasser: Caballero, R. Hermoso, A. Jiménez, J. et al.

Quelle: Dehesa. Repositorio Institucional de la Universidad de Extremadura
Universidad de Extremadura (UEX)

Schlagwörter: innovation process, Innovation in systems with uncertainty, Systems with uncertain observations, Innovación en sistemas de incertidumbre, Sistemas con observación incierta, Inference from stochastic processes and prediction, Signal detection and filtering (aspects of stochastic processes)

Dateibeschreibung: application/pdf; application/xml

Zugangs-URL: http://hdl.handle.net/10662/17945
https://zbmath.org/1975361

Bayesian forecasting of multivariate time series: scalability, structure uncertainty and decisions

Autoren: Mike West

Quelle: Annals of the Institute of Statistical Mathematics. 72:1-31

Schlagwörter: Applications of statistics to actuarial sciences and financial mathematics, Signal Processing (eess.SP), FOS: Computer and information sciences, decouple/recouple, simultaneous graphical dynamic models, Estimation in multivariate analysis, Bayesian inference, Dynamical Systems (math.DS), time series monitoring, Statistics - Applications, Statistics - Computation, 01 natural sciences, Inference from stochastic processes and prediction, Bayesian forecasting, Methodology (stat.ME), network flows, 0502 economics and business, multi-scale models, FOS: Electrical engineering, electronic engineering, information engineering, FOS: Mathematics, Applications (stat.AP), integer count time series, Electrical Engineering and Systems Science - Signal Processing, Mathematics - Dynamical Systems, 0101 mathematics, Statistics - Methodology, Computation (stat.CO), Probabilistic graphical models, Akaike Memorial Lecture, 05 social sciences, decision-guided model assessment, dynamic dependency networks, Time series, auto-correlation, regression, etc. in statistics (GARCH), Bayesian model emulation

Dateibeschreibung: application/xml

Zugangs-URL: http://arxiv.org/pdf/1911.09656
http://arxiv.org/abs/1911.09656
https://ui.adsabs.harvard.edu/abs/2019arXiv191109656W/abstract
https://link.springer.com/article/10.1007/s10463-019-00741-3
https://ideas.repec.org/a/spr/aistmt/v72y2020i1d10.1007_s10463-019-00741-3.html
https://arxiv.org/abs/1911.09656
https://arxiv.org/pdf/1911.09656
http://export.arxiv.org/pdf/1911.09656

A novel multivariate grey model for forecasting the sequence of ternary interval numbers

Autoren: Xiangyan Zeng Shuli Yan Yanchao Shi et al.

Quelle: Applied Mathematical Modelling. 69:273-286

Schlagwörter: 0209 industrial biotechnology, Estimation in multivariate analysis, ternary interval number, 8. Economic growth, 0202 electrical engineering, electronic engineering, information engineering, forecasting, multivariate grey model, 02 engineering and technology, Applications of statistics to economics, Inference from stochastic processes and prediction

Dateibeschreibung: application/xml

Zugangs-URL: https://www.sciencedirect.com/science/article/pii/S0307904X18306309
https://data.mendeley.com/datasets/xzpzs8tcdd

Prediction Analysis for Microbiome Sequencing Data: Prediction analysis for microbiome sequencing data

Autoren: Can Yang Tao Wang Hongyu Zhao

Quelle: Biometrics. 75:875-884

Schlagwörter: multinomial-logit regression, FOS: Computer and information sciences, 0301 basic medicine, Generalized linear models (logistic models), Likelihood Functions, 0303 health sciences, Bacteria, Microbiota, expectation-maximization algorithm, Protein sequences, DNA sequences, Applications of statistics to biology and medical sciences, meta analysis, Inference from stochastic processes and prediction, Methodology (stat.ME), Expectation-maximization algorithm, model-based dimension reduction, 03 medical and health sciences, log ratios, metagenomic data, Humans, Regression Analysis, Monte Carlo Method, Sequence Analysis, Statistics - Methodology, Algorithms

Dateibeschreibung: application/xml

Zugangs-URL: http://arxiv.org/pdf/1710.02616
https://pubmed.ncbi.nlm.nih.gov/30994187
http://arxiv.org/abs/1710.02616
http://repository.ust.hk/ir/Record/1783.1-96656
https://pubmed.ncbi.nlm.nih.gov/30994187/
https://www.ncbi.nlm.nih.gov/pubmed/30994187
https://onlinelibrary.wiley.com/doi/10.1111/biom.13061
http://ui.adsabs.harvard.edu/abs/2017arXiv171002616W/abstract

Distributed Robust Kalman Filtering with Unknown and Noisy Parameters in Sensor Networks: Distributed robust Kalman filtering with unknown and noisy parameters in sensor networks

Autoren: Donghua Chen Ya Zhang Cheng-Lin Liu et al.

Quelle: Discrete Dynamics in Nature and Society, Vol 2018 (2018)

Schlagwörter: 0209 industrial biotechnology, 13. Climate action, QA1-939, 02 engineering and technology, Mathematics, Filtering in stochastic control theory, Inference from stochastic processes and prediction

Dateibeschreibung: application/xml; text/xhtml

Zugangs-URL: https://downloads.hindawi.com/journals/ddns/2018/7954263.pdf
https://zbmath.org/7026689
https://doi.org/10.1155/2018/7954263
https://doaj.org/article/727c6a373a8441a68bfe376b7ce34a86
https://downloads.hindawi.com/journals/ddns/2018/7954263.pdf
https://www.hindawi.com/journals/ddns/2018/7954263/
http://downloads.hindawi.com/journals/ddns/2018/7954263.pdf