Estimating the intensity of point processes on linear networks
Başlık çevirisi mevcut değil.
- Tez No: 719631
- Danışmanlar: DR. Fred W. Huffer
- Tez Türü: Doktora
- Konular: İstatistik, Statistics
- Anahtar Kelimeler: spatial point pattern, linear network, classification method, intensity estimation, complete spatial randomness
- Yıl: 2020
- Dil: İngilizce
- Üniversite: Florıda State Unıversıty
- Enstitü: Yurtdışı Enstitü
- Ana Bilim Dalı: Belirtilmemiş.
- Bilim Dalı: Belirtilmemiş.
- Sayfa Sayısı: Belirtilmemiş.
Özet
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Özet (Çeviri)
The study of point processes and the analysis of data which involves spatial point patterns are important topics in spatial statistics with a long history and a large literature. A relatively new sub-area within this is the statistical analysis of point processes on linear networks, that is, processes of events occurring randomly in space (or space-time) but with locations constrained to lie on a linear network. For example, traffic accidents occur at random locations constrained to lie on a network of streets. Other examples involve events occurring on networks of rivers or networks of neurons. In all these cases the networks are idealized as (or approximated by) a network of line segments or curves in the plane or in three-dimensional space. The development of statistical techniques for the analysis of point processes on linear networks is still in its infancy. Many standard statistical techniques for analyzing point processes cannot be directly applied to data arising from linear networks and require suitable modification. This dissertation contributes to the development of statistical techniques for analyzing point processes on linear networks. We shall investigate two topics. The first is testing the hypothesis of complete spatial randomness for point processes on linear networks. The second topic is the estimation of the intensity for such processes. In particular, we will estimate the intensity by applying techniques for classification from machine learning.
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