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March 14, 2026Journal of Statistical Theory and Practice0 citationsOpen Access

A Note on Asymptotics of Estimators for Axially Symmetric Processes on the Sphere

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HZHaimeng ZhangCHChunfeng HuangXXXiaohuan Xue

Key Points

  • To investigate the asymptotic properties of method-of-moments estimators for axially symmetric Gaussian processes.
  • Analyzed MOM estimators of covariances and cross-variograms on latitude-longitude grids.
  • Examined the asymptotic bias of MOM covariance estimators.
  • Established the inconsistency of MOM cross-variogram estimators using covariance matrix diagonalization.
  • MOM covariance estimators are shown to be asymptotically biased.
  • MOM cross-variogram estimators proved to be unbiased.
  • Intrinsic limitations of MOM estimators on compact manifolds were illustrated.

Abstract

Abstract Axially symmetric processes, those stationary in longitude but nonstationary across latitude, provide a flexible and physically meaningful class of models for global environmental data. Despite their wide use, the asymptotic properties of classical method-of-moments (MOM) estimators for these processes remain largely unexamined. In this work, we investigate MOM estimators of covariances and cross-variograms for axially symmetric Gaussian processes observed on regular latitude-longitude grids. First, we show that MOM covariance estimators are asymptotically biased. We then examine MOM estimators of cross-variograms, and prove that they are unbiased. However, using the block circulant structure of the covariance matrix and its Fourier diagonalization, we establish MOM cross-variogram estimators are not consistent. These findings illustrate intrinsic limitations of MOM-type estimators on compact manifolds and emphasize that Euclidean intuition does not carry over to spherical settings.

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Cite This Study

Zhang et al. (2026) studied this question.

synapsesocial.com/papers/69b4ada918185d8a39801525https://doi.org/10.1007/s42519-026-00556-5
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