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大型空间数据集似然估计中的协方差截尾AI 解读

Maximum likelihood is an attractive method of estimating covariance parameters in spatial models based on Gaussian processes. But calculating the likelihood can be computationally infeasible for large data sets, requiring O(n3) calculations for a data set with n observations. This article proposes the method of covariance tapering to approximate the likelihood in this setting. In this approach, covariance matrixes are “tapered,” or multiplied element wise by a sparse…

多元随机场协方差结构的检验AI 解读

There is an increasing wealth of multivariate spatial and multivariate spatio-temporal data appearing. For such data, an important part of model building is an assessment of the properties of the underlying covariance function describing variable, spatial and temporal correlations. In this paper, we propose a methodology to evaluate the appropriateness of several types of common assumptions on multivariate covariance functions in the spatio-temporal context. The methodology…

非齐次空间泊松过程的拟合优度检验AI 解读

We introduce a formal testing procedure to assess the fit of an inhomogeneous spatial Poisson process model, based on a discrepancy measure function that is constructed from residuals obtained from the fitted model. We derive the asymptotic distributional properties of and develop a test statistic based on them. Our test statistic has a limiting standard normal distribution, so that the test can be performed by simply comparing the test statistic with readily available…

多维空间中空间相关数据的估计方程AI 解读

We use the quasilikelihood concept to propose an estimating equation for spatial data with correlation across the study region in a multi-dimensional space. With appropriate mixing conditions, we develop a central limit theorem for a random field under various Lp metrics. The consistency and asymptotic normality of quasilikelihood estimators can then be derived. We also conduct simulations to evaluate the performance of the proposed estimating equation, and a dataset from…

时间序列、空间与截面数据的相关性检验AI 解读

We provide a general class of tests for correlation in time series, spatial, spatio-temporal and cross-sectional data. We motivate our focus by reviewing how computational and theoretical difficulties of point estimation mount, as one moves from regularly-spaced time series data, through forms of irregular spacing, and to spatial data of various kinds. A broad class of computationally simple tests is justified. These specialize to Lagrange multiplier tests against parametric…

个体数与时期数均较大时固定效应空间动态面板的准极大似然估计AI 解读

This paper investigates the asymptotic properties of quasi-maximum likelihood estimators for spatial dynamic panel data with fixed effects, when both the number of individuals n and the number of time periods T are large. We consider the case where T is asymptotically large relative to n, the case where T is asymptotically proportional to n, and the case where n is asymptotically large relative to T. In the case where T is asymptotically large relative to n, the estimators…

非齐次空间点过程的一致非参数强度估计AI 解读

A common nonparametric approach to estimate the intensity function of an inhomogeneous spatial point process is through kernel smoothing. When conducting the smoothing, one typically uses events only in a local set around the point of interest. But the resulting estimator often is inconsistent, because the number of events in a fixed set is of order 1 for spatial point processes. In this article we propose a new covariate-based kernel smoothing method to estimate the…

在迷宫中搜寻证据路径AI 解读

Consider a graph with a set of vertices and oriented edges connecting pairs of vertices. Each vertex is associated with a random variable and these are assumed to be independent. In this setting, suppose we wish to solve the following hypothesis testing problem: under the null, the random variables have common distribution N(0, 1) while under the alternative, there is an unknown path along which random variables have distribution N(μ, 1), μ> 0, and distribution N(0, 1) away…

强度函数成比例的非齐次空间点过程二阶分析AI 解读

We consider pairs of spatial point processes with intensity functions sharing a common multiplicative term. We introduce two novel approaches to estimating the pair correlation function for one of the point processes by treating the other as a baseline so as to account for the unspecified part of the intensity functions. The first approach is based on nonparametric kernel-smoothing, whereas the second approach uses a conditional likelihood estimation approach to fit a…

纵向曲线的基于小波的非参数功能定位AI 解读

Functional mapping based on parametric and nonparametric modeling of functional data can estimate the developmental pattern of genetic effects on a complex dynamic or longitudinal process triggered by quantitative trait loci (QTLs). But existing functional mapping models have a limitation for mapping dynamic QTLs with irregular functional data characterized by many local features, such as peaks. We derive a statistical model for QTL mapping of longitudinal curves of any form…

从实验数据学习因果贝叶斯网络结构AI 解读

We propose a method for the computational inference of directed acyclic graphical structures given data from experimental interventions. Order-space Markov chain Monte Carlo, equi-energy sampling, importance weighting, and stream-based computation are combined to create a fast algorithm for learning causal Bayesian network structures.

存在个体间干扰时的因果推断AI 解读

A fundamental assumption usually made in causal inference is that of no interference between individuals (or units); that is, the potential outcomes of one individual are assumed to be unaffected by the treatment assignment of other individuals. However, in many settings, this assumption obviously does not hold. For example, in the dependent happenings of infectious diseases, whether one person becomes infected depends on who else in the population is vaccinated. In this…

通过条件方差限制识别社会互动AI 解读

The copyright to this Article is held by the Econometric Society. It may be downloaded, printed and reproduced only for educational or research purposes, including use in course packs. No downloading or copying may be done for any commercial purpose without the explicit permission of the Econometric Society. For such commercial purposes contact the Office of the Econometric Society (contact information may be found at the website

热带非洲罗阿丝虫患病率的二元二项空间建模AI 解读

We present a state-of-the-art application of smoothing for dependent bivariate binomial spatial data to Loa loa prevalence mapping in West Africa. This application starts with the nonspatial calibration of survey instruments, continues with the spatial model building and assessment, and ends with robust, tested software intended for use by field workers for online prevalence map updating. From a statistical perspective, we address several important methodological issues:…

利用空间经验似然进行变差函数模型的点估计与区间估计AI 解读

We present a spatial blockwise empirical likelihood method for estimating variogram model parameters in the analysis of spatial data on a grid. The method produces point estimators that require no spatial variance estimates to compute, unlike least squares methods for variogram fitting, but are as efficient as the best least squares estimator in large samples. Our approach also produces confidence regions for the variogram, without requiring knowledge of the full joint…

贝叶斯层级曲线配准AI 解读

Functional data often exhibit a common shape, but with variations in amplitude and phase across curves. The analysis often proceeds by synchronization of the data through curve registration. In this article we propose a Bayesian hierarchical model for curve registration. Our hierarchical model provides a formal account of amplitude and phase variability while borrowing strength from the data across curves in the estimation of the model parameters. We discuss extensions of…

地下与地上树皮甲虫定殖引致林隙的时空建模AI 解读

Studies of forest declines are important, because they both reduce timber production and affect successional trajectories of landscapes and ecosystems. Of particular interest is the decline of red pines, which is characterized by expanding areas of dead and chlorotic trees in plantations throughout the Great Lakes region. Here we examine the impact of two bark beetle groups, red turpentine beetles and pine engraver bark beetles, on tree mortality and the subsequent gap…

利用暴露模拟器研究环境颗粒物浓度与死亡率的关系AI 解读

Since the U.S. Environmental Protection Agency began widespread monitoring of PM2.5 (particulate matter <2.5 μ in diameter) concentration levels in the late 1990s, the epidemiological community has performed several observational studies directly relating PM2.5 concentration to various health endpoints including mortality and morbidity. However, recent research suggests that human exposure to the constituents of PM2.5 may differ significantly from ambient (or outdoor) PM2.5…

确定性动态模型中时变系数的高效局部估计及 HIV-1 应用AI 解读

Recently deterministic dynamic models have become very popular in biomedical research and other scientific areas; examples include modeling human immunodeficiency virus (HIV) dynamics, pharmacokinetic/pharmacodynamic analysis, tumor cell kinetics, and genetic network modeling. In this article we propose estimation methods for the time-varying coefficients in deterministic dynamic systems that are usually described by a set of differential equations. Three two-stage local…

社会网络模型的拟合优度AI 解读

We present a systematic examination of a real network data set using maximum likelihood estimation for exponential random graph models as well as new procedures to evaluate how well the models fit the observed networks. These procedures compare structural statistics of the observed network with the corresponding statistics on networks simulated from the fitted model. We apply this approach to the study of friendship relations among high school students from the National…

银行分支设立放松管制的实际效应：美国跨州相邻县比较AI 解读

This paper proposes a new methodology to evaluate the economic effect of state-specific policy changes, using bank-branching deregulations in the US as an example. The new method compares economic performance of pairs of contiguous counties separated by state borders, where on one side restrictions on statewide branching were removed relatively earlier, to create a natural "regression discontinuity" setup. The study uses a total of 285 pairs of contiguous counties along 38…

利用条件自回归空间模型的方差结构刻画知识溢出AI 解读

Abstract This study investigates the pattern of knowledge spillovers arising from patent activity between European regions. A Bayesian hierarchical model is developed that specifies region‐specific latent effects parameters modeled using a connectivity structure between regions that can reflect geographical proximity in conjunction with technological and other types of proximity. This approach exploits the fact that interregional relationships may exhibit industry‐specific…

协变量信息不完整时非齐次空间点过程的估计函数AI 解读

The R package spatstat provides a very flexible and useful framework for analysing spatial point patterns. A fundamental feature is a procedure for fitting spatial point process models depending on covariates. However, in practice one often faces incomplete observation of the covariates and this leads to parameter estimation error which is difficult to quantify. In this paper, we introduce a Monte Carlo version of the estimating function used in spatstat for fitting…

多参数自模型及其应用AI 解读

Motivated by the modelling of non-Gaussian data or positively correlated data on a lattice, extensions of Besag's automodels to exponential families with multi-dimensional parameters have been proposed recently. We provide a multiple-parameter analogue of Besag's one-dimensional result that gives the necessary form of the exponential families for the Markov random field's conditional distributions. We propose estimation of parameters by maximum pseudolikelihood and give a…