Detecting British Columbia Coastal Rainfall Patterns by Clustering Gaussian Processes

@article{Paton2018DetectingBC,
  title={Detecting British Columbia Coastal Rainfall Patterns by Clustering Gaussian Processes},
  author={Forrest Paton and P. McNicholas},
  journal={arXiv: Applications},
  year={2018}
}
  • Forrest Paton, P. McNicholas
  • Published 2018
  • Mathematics
  • arXiv: Applications
  • Functional data analysis is a statistical framework where data are assumed to follow some functional form. This method of analysis is commonly applied to time series data, where time, measured continuously or in discrete intervals, serves as the location for a function's value. Gaussian processes are a generalization of the multivariate normal distribution to function space and, in this paper, they are used to shed light on coastal rainfall patterns in British Columbia (BC). Specifically, this… CONTINUE READING

    Figures and Tables from this paper.

    References

    Publications referenced by this paper.
    SHOWING 1-10 OF 24 REFERENCES
    Adapting K-means clustering to identify spatial patterns in storms
    2
    Model-Based Clustering
    134
    Model-based clustering of high-dimensional data: A review
    248
    El Niño : overview and bibliography
    4
    Gaussian processes for time-series modelling
    249
    Finite mixtures of skewed matrix variate distributions
    24