Approximation of Gaussian spatial autoregressive models for massive regular square tessellation data

Most of the literature to date proposes approximations to the determinant of a positive definite n × n spatial covariance matrix (the Jacobian term) for Gaussian spatial autoregressive models that fail to support the analysis of massive georeferenced data sets. This paper briefly surveys this literature, recalls and refines much simpler Jacobian approximations, presents selected eigenvalue estimation techniques, summarizes validation results (for estimated eigenvalues, Jacobian approximations, and estimation of a spatial autocorrelation parameter), and illustrates the estimation of the spatial autocorrelation parameter in a spatial autoregressive model specification for cases as large as n = 37,214,101. The principal contribution of this paper is to the implementation of spatial autoregressive model specifications for any size of georeferenced data set. Its specific additions to the literature include (1) new, more efficient estimation algorithms; (2) an approximation of the Jacobian term for remotely sensed data forming incomplete rectangular regions; (3) issues of inference; and (4) timing results.     

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前兆定点形变观测数据噪声分析

地球物理研究表明,可以构造或选择合适的统计模型模拟观测噪声,从而了解噪声特性,获得噪声谱及其含量.对吉林省5个台站的倾斜观测共18个测项产出的时间序列进行噪声分析,结果表明,长期观测噪声可用带通噪声和随机游走噪声的组合模型模拟,短时间观测噪声可用谱指数介于-1至-2的幂律噪声模型模拟.该结论对定点形变观测噪声的认识、噪声源的研究以及地壳构造信息的提取具有参考意义.     

Identification of uncertainty in low flow frequency analysis using Bayesian MCMC method

This study employs the Bayesian Markov Chain Monte Carlo (MCMC) method with the Metropolis–Hastings algorithm and maximum likelihood estimation (MLE) using a quadratic approximation of the likelihood function for the evaluation of uncertainties in low flow frequency analysis using a two‐parameter Weibull distribution. The two types of prior distributions, a non‐data‐based distribution and a data‐based distribution using regional information collected from neighbouring stations, are used to establish a posterior distribution. Eight case studies using the synthetic data with a sample size of 100, generated from two‐parameter Weibull distribution, are performed to compare with results of analysis using MLE and Bayesian MCMC. Also, Bayesian MCMC and MLE are applied to 36 years of gauged data to validate the efficiency of the developed scheme. These examples illustrate the advantages of Bayesian MCMC and the limitations of MLE based on a quadratic approximation. From the point of view of uncertainty analysis, Bayesian MCMC is more effective than MLE using a quadratic approximation when the sample size is small. In particular, Bayesian MCMC method is more attractive than MLE based on a quadratic approximation because the sample size of low flow at the site of interest is mostly not enough to perform the low flow frequency analysis. Copyright © 2007 John Wiley & Sons, Ltd.     

A MORE GENERAL FORM OF ERROR DISTRIBUTION

This paper deduced a more general error distribution,the p-th pow-er norm distribution,based on the foundational properties of random errors.     

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汶川地震前后四川区域GPS时序特征演变及统计分析

为探索地震事件对GPS坐标时间序列的长周期影响,对汶川地震前后四川GPS观测网络长约10年的解算成果进行了多参数模型噪声特征分析.基于最大似然估计方法和频谱特性分析,提取了地震前后各测站坐标序列中的噪声分量,使用Λ-统计检验,得出"白噪声+闪烁噪声"模型可以作为四川GPS区域观测网络的最优噪声组合模型,同时,地震事件使得地震前后GPS噪声分量中的白噪声、闪烁噪声、随机游走噪声等发生显著改变,说明传统谱噪声分析中简单地将地震数据拼接在一起并进行统一处理的模式并不可取;使用共模误差分析方法、区域速度场变化趋势等信息对地震前后噪声模型的改变成因进行了初步的物理解析.