Publication

Metropolis-Hastings sampling of alternatives for route choice models

Michel Bierlaire
2010
Talks

Abstract

Sampling of alternatives has been shown to be an operational technique for the estimation of route choice models. In order to apply it, the sampling protocol generating paths must be such that the sampling probability is known, in order to correct for the sampling bias. Few path generation algorithms proposed in the literature allow to compute the associated probability. We present a new path generation method that we are currently investigating. It is based on the Metropolis-Hastings algorithm, so that the sampling probability is actually an input to the method, and not an output. Also, it allows for a great deal of flexibility in terms of the exploration of the set of paths.

Official source

https://infoscience.epfl.ch/entities/publication/b2b46108-e119-48b1-8010-e6c67d690e5b

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Michel Bierlaire
2010
Talks

Abstract

Official source

https://infoscience.epfl.ch/entities/publication/b2b46108-e119-48b1-8010-e6c67d690e5b

About this result

Related concepts (32)

Sampling (statistics)

In statistics, quality assurance, and survey methodology, sampling is the selection of a subset or a statistical sample (termed sample for short) of individuals from within a statistical population to estimate characteristics of the whole population. Statisticians attempt to collect samples that are representative of the population. Sampling has lower costs and faster data collection compared to recording data from the entire population, and thus, it can provide insights in cases where it is infeasible to measure an entire population.

Survey sampling

In statistics, survey sampling describes the process of selecting a sample of elements from a target population to conduct a survey. The term "survey" may refer to many different types or techniques of observation. In survey sampling it most often involves a questionnaire used to measure the characteristics and/or attitudes of people. Different ways of contacting members of a sample once they have been selected is the subject of survey data collection.

Convenience sampling

Convenience sampling (also known as grab sampling, accidental sampling, or opportunity sampling) is a type of non-probability sampling that involves the sample being drawn from that part of the population that is close to hand. This type of sampling is most useful for pilot testing. Convenience sampling is not often recommended for research due to the possibility of sampling error and lack of representation of the population. But it can be handy depending on the situation. In some situations, convenience sampling is the only possible option.

Related publications (32)

Metropolis-Hastings sampling of alternatives for route choice models

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