Engineering Commons^™

Markov Chain Monte Carlo Multiple Imputation For Incomplete Its Data Using Bayesian Networks, Daiheng Ni, John D. Leonard

Daiheng Ni

The rich ITS data is a precious resource for transportatio n researchers and practitioners. However, the usability of such resource is greatly limited by the issue of data missing. A lot of imputation methods have been proposed in the past decade. However, some issues ar e still not or not sufficiently addresse d. For example, the missing of entire records, temporal correlation in observations, natural char acteristics in raw data, and unbiased estimates for missing values. With these in mind, this paper proposes an advanced imputation method which is based on the recent development in other disciplines, especially applied statistics …