Standard Gaussian process models were introduced in Section 2.2. Such models gained popularity originally in geostatistical applications but have become widely used throughout spatial statistics. In this chapter, we will see how one can represent a Gaussian process via convolutions, which can have great computational advantages as well as providing a rather natural mechanism for moving to a multiscale model. Thus the latter section of this chapter will fully explore how to use the convolution representation to build a multiscale model.
KeywordsGaussian Process Gaussian Kernel Markov Chain Monte Carlo Method Background Process Bottom Plot
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