A parameter transformation of the anisotropic Matérn covariance function

IF 0.8 4区 数学 Q3 STATISTICS & PROBABILITY
Kamal Rai, Patrick E. Brown
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引用次数: 0

Abstract

We describe a polar coordinate transformation of the anisotropy parameters of the Matérn covariance function, which provides two benefits over the standard parameterization. First, it identifies a single point (the origin) with the special case of isotropy. Second, the posterior distribution of the transformed anisotropic angle and ratio is approximately bell-shaped and unimodal even in the case of isotropy. This has advantages for parameter inference and density estimation. We also apply a transformation to the standard deviation and range such that they are approximately orthogonal. We demonstrate this parameter transformation through two simulated and two real data sets, and conclude by considering possible extensions, such as implementing this transformation for approximate Bayesian inference methods.

各向异性mat协方差函数的参数变换
我们描述了mat协方差函数的各向异性参数的极坐标变换,它比标准参数化提供了两个好处。首先,它在各向同性的特殊情况下识别单个点(原点)。在各向同性的情况下,变换后的各向异性角和比值的后向分布近似为钟形单峰分布。这在参数推断和密度估计方面具有优势。我们还对标准差和极差进行变换,使它们近似正交。我们通过两个模拟数据集和两个真实数据集演示了这种参数转换,并考虑了可能的扩展,例如在近似贝叶斯推理方法中实现这种转换。
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来源期刊
CiteScore
1.40
自引率
0.00%
发文量
62
审稿时长
>12 weeks
期刊介绍: The Canadian Journal of Statistics is the official journal of the Statistical Society of Canada. It has a reputation internationally as an excellent journal. The editorial board is comprised of statistical scientists with applied, computational, methodological, theoretical and probabilistic interests. Their role is to ensure that the journal continues to provide an international forum for the discipline of Statistics. The journal seeks papers making broad points of interest to many readers, whereas papers making important points of more specific interest are better placed in more specialized journals. The levels of innovation and impact are key in the evaluation of submitted manuscripts.
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