Hypothetical Models.

Irina Burlacu; Cathal O'Donoghue; Denisa Sologon

doi:https://doi.org/10.1108/S0573-855520140000293000

Hypothetical Models.

Irina Burlacu, Cathal O'Donoghue, Denisa Sologon

Living Conditions

Research output: Chapter in Book/Report/Conference proceeding › Chapter › peer-review

Abstract

Microsimulation models can be used with various types of datasets, including the synthetic data constructed based on a number of simple assumptions. Models based on hypothetical data offer useful insights despite their simplicity. In fact, their usefulness stems largely from the simplicity of the approach as it avoids the population complexity. In this chapter we review the development of microsimulation models using hypothetical data.

Original language	English
Title of host publication	Handbook of Microsimulation Modelling
Publisher	Emerald Publishing Limited
Pages	23-46
Number of pages	0
Volume	293
ISBN (Print)	978-1-78350-569-2
DOIs	https://doi.org/10.1108/S0573-855520140000293000
Publication status	Published - 2014

Keywords

hypothetical data
hypothetical models
microsimulation

Access to Document

https://doi.org/10.1108/S0573-855520140000293000

5 Article

A hybrid learning algorithm for generating multi-agent daily activity plans
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Ma, T-Y., 5 Feb 2014, In: Procedia Social and Behavioral Sciences. 111, p. 330-339 10 p.
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Open Access
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Research output: Contribution to journal › Article › peer-review

Open Access

Cite this

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title = "Hypothetical Models.",

abstract = "Microsimulation models can be used with various types of datasets, including the synthetic data constructed based on a number of simple assumptions. Models based on hypothetical data offer useful insights despite their simplicity. In fact, their usefulness stems largely from the simplicity of the approach as it avoids the population complexity. In this chapter we review the development of microsimulation models using hypothetical data.",

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AU - O'Donoghue, Cathal

AU - Sologon, Denisa

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AB - Microsimulation models can be used with various types of datasets, including the synthetic data constructed based on a number of simple assumptions. Models based on hypothetical data offer useful insights despite their simplicity. In fact, their usefulness stems largely from the simplicity of the approach as it avoids the population complexity. In this chapter we review the development of microsimulation models using hypothetical data.

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KW - microsimulation

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VL - 293

SP - 23

EP - 46

BT - Handbook of Microsimulation Modelling

PB - Emerald Publishing Limited

ER -

Hypothetical Models.

Abstract

Keywords

Access to Document

Research output

A hybrid learning algorithm for generating multi-agent daily activity plans

Mode choice with latent preference heterogeneity: a case study for employees of the EU Institutions in Luxembourg.

Social trajectory and socio-spatial representation of urban space: The relation between social and cognitive structures.

An A* label-setting algorithm for multimodal resource constrained shortest path problem.

Geographic, Social-cultural and Modal Usage Determinants of Activity Space: A Case Study of EU Institutions in Luxembourg and Strasbourg

Cite this