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SPATIAL AUTOREGRESSIVE ERROR-COMPONENTS IN TRAVEL FLOW MODELS
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AI
DOI：10.1016/0166-0462(92)90035-Y.png)
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In this study, we propose a generalization of the error components formulation to model the correlation among the errors of a regression based on travel flow data. The error term is broken down into a sum of one component related to the origin zones, one component related to the destination zones and a remainder. The inter-dependencies among the errors are assumed to result from applying a first-order spatial autoregressive generating process to each component. An efficient estimation approach based on maximum likelihood is suggested to address the practical implementation of such a model with a large sample size.
Keyword:
MAXIMUM-LIKELIHOOD ESTIMATION
SPECIFICATION
REGRESSION
期刊
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2.9
论文数:
2.3K
被引数:
4.8K
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