Abstract
A variety of statistical techniques are suggested for the analysis of data where the incidence of respiratory cancer is thought to be related to a putative pollution source. Non-parametric kernel regression techniques and more formal point process models are considered. Parameter estimation based on maximum likelihood is discussed. Extensions to an existing model are proposed, and a new hybrid model is also fitted.
| Original language | English |
|---|---|
| Pages (from-to) | 285-298 |
| Number of pages | 14 |
| Journal | Journal of the Royal Statistical Society Series A - Statistics in Society |
| Volume | 157 |
| Issue number | 2 |
| Publication status | Published - 1994 |
UN SDGs
This output contributes to the following UN Sustainable Development Goals (SDGs)
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SDG 3 Good Health and Well-being
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