High dimensional regression for regenerative time-series: An application to road traffic modeling

Computational Statistics & Data Analysis ◽

10.1016/j.csda.2021.107191 ◽

2021 ◽

Vol 158 ◽

pp. 107191

Author(s):

Mohammed Bouchouia ◽

François Portier

Keyword(s):

Time Series ◽

Road Traffic ◽

High Dimensional ◽

Traffic Modeling ◽

High Dimensional Regression

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Variable selection for high-dimensional regression models with time series and heteroscedastic errors

Journal of Econometrics ◽

10.1016/j.jeconom.2020.01.009 ◽

2020 ◽

Vol 216 (1) ◽

pp. 118-136

Author(s):

Hai-Tang Chiou ◽

Meihui Guo ◽

Ching-Kang Ing

Keyword(s):

Time Series ◽

Variable Selection ◽

Regression Models ◽

High Dimensional ◽

High Dimensional Regression ◽

Heteroscedastic Errors ◽

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Road Traffic Modeling: The Interest of Warm-Up Detection in Dynamic Simulations

Engineering and Technology Journal ◽

10.31142/etj/v3i5.01 ◽

2018 ◽

Vol 3 (5) ◽

Author(s):

Najia BOUHA ◽

Keyword(s):

Road Traffic ◽

Traffic Modeling ◽

Dynamic Simulations ◽

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Testing Covariates in High Dimensional Regression

SSRN Electronic Journal ◽

10.2139/ssrn.2260820 ◽

2013 ◽

Author(s):

Wei Lan ◽

Hansheng Wang ◽

Chih-Ling Tsai

Keyword(s):

High Dimensional ◽

High Dimensional Regression

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Introducing Software Components to Road Traffic Modeling and Simulation

SNE Simulation Notes Europe ◽

10.11128/sne.21.tn.10041 ◽

2011 ◽

Vol 21 (1) ◽

pp. 21-26

Author(s):

Petr Zelenka

Keyword(s):

Modeling And Simulation ◽

Road Traffic ◽

Traffic Modeling ◽

Software Components

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Hierarchical selection of variables in sparse high-dimensional regression

Institute of Mathematical Statistics Collections - Borrowing Strength: Theory Powering Applications – A Festschrift for Lawrence D. Brown ◽

10.1214/10-imscoll605 ◽

2010 ◽

pp. 56-69 ◽

Author(s):

Peter J. Bickel ◽

Ya’acov Ritov ◽

Alexandre B. Tsybakov

Keyword(s):

High Dimensional ◽

Selection Of Variables ◽

High Dimensional Regression ◽

Hierarchical Selection ◽

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Large‐sample approximations and change testing for high‐dimensional covariance matrices of multivariate linear time series and factor models

Scandinavian Journal of Statistics ◽

10.1111/sjos.12508 ◽

2020 ◽

Author(s):

Monika Bours ◽

Ansgar Steland

Keyword(s):

Time Series ◽

Linear Time ◽

Factor Models ◽

Covariance Matrices ◽

High Dimensional ◽

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Differentiable Neural Architecture Search for High-Dimensional Time Series Forecasting

IEEE Access ◽

10.1109/access.2021.3055555 ◽

2021 ◽

Vol 9 ◽

pp. 20922-20932

Author(s):

Renlong Jie ◽

Junbin Gao

Keyword(s):

Time Series ◽

Time Series Forecasting ◽

High Dimensional ◽

Neural Architecture

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Inference of breakpoints in high-dimensional time series

Journal of the American Statistical Association ◽

10.1080/01621459.2021.1893178 ◽

2021 ◽

pp. 1-33

Author(s):

Likai Chen ◽

Weining Wang ◽

Wei Biao Wu

Keyword(s):

Time Series ◽

High Dimensional

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Time Series-Analysis Based Engineering of High-Dimensional Wide-Area Stability Indices for Machine Learning

IEEE Access ◽

10.1109/access.2021.3099459 ◽

2021 ◽

pp. 1-1

Author(s):

Raoult Teukam Dabou ◽

Innocent Kamwa ◽

C. Y. Chung ◽

C. F. Mugombozi

Keyword(s):

Machine Learning ◽

Time Series ◽

Time Series Analysis ◽

Wide Area ◽

High Dimensional ◽

Series Analysis ◽

Stability Indices

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Grey Systems Theory Time Series Prediction applied to Road Traffic Safety in Germany

IFAC-PapersOnLine ◽

10.1016/j.ifacol.2016.07.039 ◽

2016 ◽

Vol 49 (3) ◽

pp. 231-236 ◽

Author(s):

Hosse René S. ◽

U. Becker ◽

H. Manz

Keyword(s):

Time Series ◽

Systems Theory ◽

Traffic Safety ◽

Road Traffic ◽

Time Series Prediction ◽

Road Traffic Safety ◽

Grey Systems Theory

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