Markov-Modulated Linear Regression: a Case Study of Coaches’ Delay Time

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TITLE

Markov-Modulated Linear Regression: a Case Study of Coaches’ Delay Time

ABSTRACT

This research presents alternating Markov-modulated linear regression application for analysis of delays of regional buses (coaches). Markov-modulated linear regression suggests that the parameters of regression model vary randomly in accordance with external environment. The latter is described as a continuous-time homogeneous irreducible Markov chain with known parameters. For each state of the environment the regression model parameters are estimated. Data on weather conditions in the Ventspils city provided by the Latvian Environment, Geology and Meteorology Centre database is used for the environment description: two states are assumed: “no precipitation” and “precipitation”. The model of the external environment is tested for the markovian properties. Actual data on coaches’ trip times is provided by the Riga International Coach Terminal. Data is analysed by means of descriptive statistics. Different experiments are carried out and the application of Markov-modulated linear regression model on given sample showed adequate results indicating the validity of the model.

KEYWORDS

External environment, Markov-modulated linear regression, trip time, delay time analysis

REFERENCES

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Cite this paper

Nadezda Spiridovska. (2018) Markov-Modulated Linear Regression: a Case Study of Coaches’ Delay Time. International Journal of Economics and Management Systems, 3, 53-59