Predicting the pavement performance: A comparison on traditional and multivariate time series model

Mapping Intimacies ◽

10.1201/9781003251125-67 ◽

2021 ◽

pp. 426-431

Author(s):

Wanqi Jiang ◽

Qiao Dong ◽

Tianjie Zhang

Keyword(s):

Time Series ◽

Multivariate Time Series ◽

Time Series Model ◽

Pavement Performance

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Multivariate time-series model to estimate the arrival times of S-waves

Computers & Geosciences ◽

10.1016/0098-3004(93)90127-q ◽

1993 ◽

Vol 19 (2) ◽

pp. 295-301 ◽

Author(s):

Tetsuo Takanami ◽

Genshiro Kitagawa

Keyword(s):

Time Series ◽

Multivariate Time Series ◽

Time Series Model ◽

Arrival Times ◽

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Modelling the Common Risk Among Equities: A Multivariate Time Series Model with an Additive GARCH Structure

Advanced Statistical Methods in Data Science - ICSA Book Series in Statistics ◽

10.1007/978-981-10-2594-5_12 ◽

2016 ◽

pp. 205-218 ◽

Author(s):

Jingjia Chu ◽

Reg Kulperger ◽

Hao Yu

Keyword(s):

Time Series ◽

Multivariate Time Series ◽

Time Series Model ◽

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Conditional forecasting with a multivariate time series model

Economics Letters ◽

10.1016/0165-1765(86)90238-7 ◽

1986 ◽

Vol 22 (2-3) ◽

pp. 233-236 ◽

Author(s):

H.S. Van Der Knoop

Keyword(s):

Time Series ◽

Multivariate Time Series ◽

Time Series Model

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A multivariate, time series model to relate alfalfa responses to chronic, ambient sulfur dioxide exposures

Environmental Pollution ◽

10.1016/0269-7491(89)90258-3 ◽

1989 ◽

Vol 61 (1) ◽

pp. 3-10 ◽

Author(s):

Sagar V. Krupa ◽

Miloslav Nosal

Keyword(s):

Time Series ◽

Sulfur Dioxide ◽

Multivariate Time Series ◽

Time Series Model

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Multivariate time series model to estimate arrival times of S waves

Methods and Applications of Signal Processing in Seismic Network Operations - Lecture Notes in Earth Sciences ◽

10.1007/bfb0117695 ◽

2008 ◽

pp. 13-39 ◽

Author(s):

Tetsuo Takanami ◽

Genshiro Kitagawa

Keyword(s):

Time Series ◽

Multivariate Time Series ◽

Time Series Model ◽

Arrival Times ◽

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Application of spatial EOF and multivariate time series model for evaluating agricultural drought vulnerability in Korea

Advances in Water Resources ◽

10.1016/j.advwatres.2010.12.010 ◽

2011 ◽

Vol 34 (3) ◽

pp. 340-350 ◽

Author(s):

Dae Ha Kim ◽

Chulsang Yoo ◽

Tae-Woong Kim

Keyword(s):

Time Series ◽

Multivariate Time Series ◽

Time Series Model ◽

Agricultural Drought ◽

Drought Vulnerability

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Multivariate Time Series Model for Pollutant Transport Using Environmental Monitoring Data

American Journal of Mathematical and Management Sciences ◽

10.1080/01966324.2008.10737737 ◽

2008 ◽

Vol 28 (3-4) ◽

pp. 433-456

Author(s):

Sung Eun Kim

Keyword(s):

Time Series ◽

Environmental Monitoring ◽

Multivariate Time Series ◽

Pollutant Transport ◽

Time Series Model ◽

Monitoring Data ◽

Environmental Monitoring Data

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Multivariate time-series model for suspended sediment concentration

Continental Shelf Research ◽

10.1016/s0278-4343(97)00066-6 ◽

1998 ◽

Vol 18 (2-4) ◽

pp. 123-150 ◽

Author(s):

Huixin Chen ◽

P.P.G. Dyke

Keyword(s):

Time Series ◽

Suspended Sediment ◽

Suspended Sediment Concentration ◽

Multivariate Time Series ◽

Sediment Concentration ◽

Time Series Model

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Analysis of heterogeneous dengue transmission in Guangdong in 2014 with multivariate time series model

Scientific Reports ◽

10.1038/srep33755 ◽

2016 ◽

Vol 6 (1) ◽

Author(s):

Qing Cheng ◽

Xin Lu ◽

Joseph T. Wu ◽

Zhong Liu ◽

Jincai Huang

Keyword(s):

Time Series ◽

Multivariate Time Series ◽

Time Series Model ◽

Dengue Transmission

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The Velocity of M1 in the 1980s: Evidence from a Multivariate Time Series Model

Southern Economic Journal ◽

10.2307/1059778 ◽

1991 ◽

Vol 57 (3) ◽

pp. 634 ◽

Author(s):

W. Douglas McMillin

Keyword(s):

Time Series ◽

Multivariate Time Series ◽

Time Series Model

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