Intrinsically Weighted Means of Marked Point Processes. Malinowski, A., Schlather, M., & Zhang, Z. 2012.
Intrinsically Weighted Means of Marked Point Processes [link]Paper  abstract   bibtex   
For a non-stationary or non-ergodic marked point process (MPP) on $}$\$R{^}d{$, the definition of averages becomes ambiguous as the process might have a different stochastic behavior in different realizations (non-ergodicity) or in different areas of the observation window (non-stationarity). We investigate different definitions for the moments, including a new hierarchical definition for non-ergodic MPPs, and embed them into a family of weighted mean marks. We point out examples of application in which different weighted mean marks all have a sensible meaning. Further, asymptotic properties of the corresponding estimators are investigated as well as optimal weighting procedures.
@misc{Malinowski2012Intrinsically,
 abstract = {For a non-stationary or non-ergodic marked point process (MPP) on {\$}$\backslash$R{\^{}}d{\$}, the definition of averages becomes ambiguous as the process might have a different stochastic behavior in different realizations (non-ergodicity) or in different areas of the observation window (non-stationarity). We investigate different definitions for the moments, including a new hierarchical definition for non-ergodic MPPs, and embed them into a family of weighted mean marks. We point out examples of application in which different weighted mean marks all have a sensible meaning. Further, asymptotic properties of the corresponding estimators are investigated as well as optimal weighting procedures.},
 author = {Malinowski, Alexander and Schlather, Martin and Zhang, Zhengjun},
 date = {2012},
 title = {Intrinsically Weighted Means of Marked Point Processes},
 url = {https://arxiv.org/abs/1210.1335},
 keywords = {phd;stat},
 file = {https://arxiv.org/pdf/1210.1335v1.pdf},
 year = {2012}
}

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