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student:oppgavekatalog:martino:start [2020-01-16] martino [Prosjekt- og masteroppgaver tilbudt av Sara Martino] |
student:oppgavekatalog:martino:start [2023-11-20] (nåværende versjon) martino [Prosjekt- og masteroppgaver tilbudt av Sara Martino] |
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====== Prosjekt- og masteroppgaver tilbudt av Sara Martino ====== | ====== Prosjekt- og masteroppgaver tilbudt av Sara Martino ====== | ||
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+ | **[[https:// | ||
My field of research is Computational statistics, and I have long experience in developing and working with the INLA software, see the [[http:// | My field of research is Computational statistics, and I have long experience in developing and working with the INLA software, see the [[http:// | ||
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+ | The projects I offer are linked or motivated by an application. The goal can either be answer a concrete question from a dataset using some statistical model, or develop a new statistical method with an application as motivation. In this last case one could use simulated data instead of observed ones. | ||
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+ | Below is a list of suggestions. Some are just ideas from collaborators so not yet very concrete. Get in touch if you find something interesting or if you have you own idea, so we can discuss possible projects together. | ||
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+ | **Analysing bycicle accidents on road networks: ReCyCLIST** | ||
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+ | ---- | ||
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+ | In the research project ReCyCLIST (https:// | ||
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+ | It is of interest to investigate the spatial distribution of the accidents in order to understand more about critical points and imporant street characteristics which might increase or decrease the risk of accidents. The interesting thing is that the road networks is not continuous in space but lives on a metric graph. | ||
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+ | **Interpolation of climate variables** | ||
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+ | ---- | ||
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+ | The global climate is undergoing significant changes, particularly noticeable in monthly mean temperatures. The Norwegian meteorological observational network has been monitoring near-surface atmospheric conditions for several decades, and in some instances, since as early as 1900. Among the various parameters tracked, monthly aggregated temperatures exhibit the most pronounced variations over time. However, these variations differ across different regions, making it crucial to advance research aimed at characterizing climate conditions and temporal trends through a variety of methodologies. | ||
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+ | This research project intends to employ the integrated nested Laplace approximation (INLA) methodology and stochastic partial differential equations (SPDE) to analyze monthly temperature data across Norway. The resulting climatological findings will be compared with existing data to enhance our understanding of climate patterns. The primary focus of this work is to apply statistical methods in the field of climate services, with a particular emphasis on techniques used to characterize climate change. | ||
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+ | This is a project in collaboration with met.no | ||
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+ | ** ** | ||
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- | If you want to work with computational statistics you write " | ||
- | **[[https:// | ||
===== Supporting courses ===== | ===== Supporting courses ===== | ||
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* [[https:// | * [[https:// | ||
* [[https:// | * [[https:// | ||
- | * [[https:// | + | * [[https:// |
+ | ===== Previous Master students ===== | ||
+ | * Sara Elise Wøllo (2022), " | ||
+ | * Julie Berg (2022), " | ||
+ | * Helene Behrens (2021) " | ||
+ | * Marion Helen Røed (2021), " | ||
+ | * August Sørli Mathisen (2020), " Inference on extreme hourly precipitation in Norway using INLA" | ||
+ | * Martin Outzen Berild (2020), " | ||
+ | * Sigrid Leithe (2019) “Statistical Methods for the Analysis of Data with a Lower Limit of Detection” | ||
+ | * Anne Siri Fardal (2019), "A Bayesian Model for Prediction of Heat Consumption" | ||
+ | * Johan Øvstebø Birketvedt (2019), " | ||
+ | Modelling of Precipitation and Temperature" | ||