A Bayesian vector autoregression-based data analytics approach to enable irregularly-spaced mixed-frequency traffic collision data imputation with missing values
- 6 November 2019
- journal article
- research article
- Published by Elsevier BV in Transportation Research Part C: Emerging Technologies
- Vol. 108, 302-319
- https://doi.org/10.1016/j.trc.2019.09.013
Abstract
No abstract availableKeywords
Funding Information
- National Natural Science Foundation of China (61803083, 61672236)
- China Postdoctoral Science Foundation (2018M630497)
This publication has 79 references indexed in Scilit:
- Bayesian VARs: Specification Choices and Forecast AccuracyJournal of Applied Econometrics, 2013
- A tensor-based method for missing traffic data completionTransportation Research Part C: Emerging Technologies, 2013
- Bayesian random effect models incorporating real-time weather and traffic data to investigate mountainous freeway hazardous factorsAccident Analysis & Prevention, 2013
- A spatial and temporal analysis of child pedestrian crashes in Santiago, ChileAccident Analysis & Prevention, 2012
- VAR FORECASTING USING BAYESIAN VARIABLE SELECTIONJournal of Applied Econometrics, 2011
- The impact of state level behavioral regulations on traffic fatality ratesJournal of Safety Research, 2009
- Poverty as a determinant of young drivers' fatal crash risksJournal of Safety Research, 2009
- Explaining variation in safety performance of roundaboutsAccident Analysis & Prevention, 2009
- K nearest neighbours with mutual information for simultaneous classification and missing data imputationNeurocomputing, 2009
- Indicator and Stratification Methods for Missing Explanatory Variables in Multiple Linear RegressionJournal of the American Statistical Association, 1996