Proceedings of the GRASPA 2019 Conference, Pescara, 15-16 July 2019 [article]

Cameletti Michela
2019
In the analysis of most spatial and spatio-temporal processes in environmental studies, observations present skewed distributions, with a heavy right or left tail. Usually, a single transformation of the data is used to approximate normality, and stationary Gaussian processes are assumed to model the transformed data. Spatial interpolation and/or temporal prediction are routinely performed by transforming the predictions back to the original scale. The choice of a distribution for the data is
more » ... n for the data is key for spatial interpolation and temporal prediction. In this talk, I will start discussing the advantages and disadvantages of using a single transformation to model such processes. Then I will discuss some recent advances in the modeling of non-Gaussian spatial and spatio-temporal processes. Abstract. With the development of data-monitoring techniques in various fields of science, multivariate functional data are often observed. Consequently, an increasing number of methods have appeared to extend the general summary statistics of multivariate functional data. However, trajectory functional data, as an important sub-type, have not been studied very well. We proposes two informative exploratory tools, the trajectory functional boxplot, and the modified simplicial band depth (MSBD) versus Wiggliness of Directional Outlyingness (WO) plot, to visualize the centrality of trajectory functional data. The newly defined WO index effectively measures the shape variation of curves and hence serves as a detector for shape outliers; additionally, MSBD provides a centeroutward ranking result and works as a detector for magnitude outliers. Using the two measures, the functional boxplot of the trajectory reveals center-outward patterns and potential outliers using the raw curves, whereas the MSBD-WO plot illustrates such patterns and outliers in a space spanned by MSBD and WO. The proposed methods are validated on hurricane path data and migration trace data recorded from two types of birds. Abstract. There are currently about 2000 operational satellites orbiting the earth. The subject of space situational awareness deals with various hazards to these satellites ranging space weather to space debris. There are estimated to be over 30000 pieces of space debris and inactive satellites in orbit bigger than a grapefruit, which can be observed from earth. In this talk I will describe some recent work funded by the US Air Force to develop fast and accurate improved statistical methods to predict the path of the debris so that it can be avoided by active spacecraft. The methodology uses ideas from Kalman filtering, directional statistics and multivariate analysis.
doi:10.6092/graspa19 fatcat:frys2ozttzhlbdy54n4s5yntmq