Analysis of traffic data based on ARMA-TS-GARCH finite mixture model

Wei Qiang Wang; Zhen Dong Niu; Yu Juan Cao; Yu Min Zhao; Kun Zhao

Analysis of traffic data based on ARMA-TS-GARCH finite mixture model

Wei Qiang Wang^*, Zhen Dong Niu, Yu Juan Cao, Yu Min Zhao, Kun Zhao

^*Corresponding author for this work

School of Computer Science and Technology

Beijing Institute of Technology

Research output: Contribution to journal › Article › peer-review

2 Citations (Scopus)

Abstract

Based on the fact that in order to study time-series data, their auto-regression and periodic and the variance of the sequence and long-term random fluctuations must be analyzed, ARMA -TS-GARCH model based on ARMA model and APARCH model was proposed, and the construction of the model and the parameter estimation with the Los Angeles Long Beach area traffic data and diagnostic tests were analyzed. The results of this model were compared with those of the GARCH and ARMA-GARCH model. The results show that the ARMA-TS-GARCH model fits the data better than ARMA model and APARCH model. Using ARMA-TS-GARCH model to predict the traffic data set, the results are well.

Original language	English
Pages (from-to)	1860-1864
Number of pages	5
Journal	Zhongnan Daxue Xuebao (Ziran Kexue Ban)/Journal of Central South University (Science and Technology)
Volume	41
Issue number	5
Publication status	Published - Oct 2010

Keywords

ARMA-TS-GARCH
Prediction
Time series
Traffic

Cite this

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title = "Analysis of traffic data based on ARMA-TS-GARCH finite mixture model",

abstract = "Based on the fact that in order to study time-series data, their auto-regression and periodic and the variance of the sequence and long-term random fluctuations must be analyzed, ARMA -TS-GARCH model based on ARMA model and APARCH model was proposed, and the construction of the model and the parameter estimation with the Los Angeles Long Beach area traffic data and diagnostic tests were analyzed. The results of this model were compared with those of the GARCH and ARMA-GARCH model. The results show that the ARMA-TS-GARCH model fits the data better than ARMA model and APARCH model. Using ARMA-TS-GARCH model to predict the traffic data set, the results are well.",

keywords = "ARMA-TS-GARCH, Prediction, Time series, Traffic",

author = "Wang, {Wei Qiang} and Niu, {Zhen Dong} and Cao, {Yu Juan} and Zhao, {Yu Min} and Kun Zhao",

year = "2010",

month = oct,

language = "English",

volume = "41",

pages = "1860--1864",

journal = "Zhongnan Daxue Xuebao (Ziran Kexue Ban)/Journal of Central South University (Science and Technology)",

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TY - JOUR

T1 - Analysis of traffic data based on ARMA-TS-GARCH finite mixture model

AU - Wang, Wei Qiang

AU - Niu, Zhen Dong

AU - Cao, Yu Juan

AU - Zhao, Yu Min

AU - Zhao, Kun

PY - 2010/10

Y1 - 2010/10

N2 - Based on the fact that in order to study time-series data, their auto-regression and periodic and the variance of the sequence and long-term random fluctuations must be analyzed, ARMA -TS-GARCH model based on ARMA model and APARCH model was proposed, and the construction of the model and the parameter estimation with the Los Angeles Long Beach area traffic data and diagnostic tests were analyzed. The results of this model were compared with those of the GARCH and ARMA-GARCH model. The results show that the ARMA-TS-GARCH model fits the data better than ARMA model and APARCH model. Using ARMA-TS-GARCH model to predict the traffic data set, the results are well.

AB - Based on the fact that in order to study time-series data, their auto-regression and periodic and the variance of the sequence and long-term random fluctuations must be analyzed, ARMA -TS-GARCH model based on ARMA model and APARCH model was proposed, and the construction of the model and the parameter estimation with the Los Angeles Long Beach area traffic data and diagnostic tests were analyzed. The results of this model were compared with those of the GARCH and ARMA-GARCH model. The results show that the ARMA-TS-GARCH model fits the data better than ARMA model and APARCH model. Using ARMA-TS-GARCH model to predict the traffic data set, the results are well.

KW - ARMA-TS-GARCH

KW - Prediction

KW - Time series

KW - Traffic

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JO - Zhongnan Daxue Xuebao (Ziran Kexue Ban)/Journal of Central South University (Science and Technology)

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Analysis of traffic data based on ARMA-TS-GARCH finite mixture model

Abstract

Keywords

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