This book is the result of a collaboration between researchers from occupant behaviour and statistical modelling. It presents a range of statistical methods and models used for modelling occupancy behaviour.
1. Introduction. 2. Likelihood. 3. General linear models. 4. Generalized linear models. 5. Linear mixed effects. Models. 6. Hierarchical models. 7. Survival Analysis. 8. Linear Time Series Models. 9. Markov chain models. 10. State Space Models. 11. Hidden Markov Models.
Do you have data on occupant behaviour, indoor environment or energy use in buildings? Are you interested in statistical analysis and modelling? Do you have a specific (research) question and dataset and would like to know how to answer the question with the data available?
Statistical Modelling of Occupant Behaviour covers a range of statistical methods and models used for modelling energy- and comfort-related occupant behaviour in buildings. It is a classical textbook on statistics, including many practical examples related to occupant behaviour that are either taken from real research problems or adapted from such.
The main focus is traditional statistical techniques based on the likelihood principle that can be applied to occupant behaviour modelling, including:
- General, generalised linear and survival models
- Mixed effect and hierarchical models
- Linear time series and Markov models
- Linear state space and hidden Markov models
- Illustration of all methods using occupant behaviour examples implemented in R
The built environment affects occupants who live and work in it, and occupants affect the built environment by adapting it to their needs for example, by adapting their indoor environments by interacting with building components and systems. These adaptivel³!
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