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并行计算在统计推断中的应用AI 解读

Recent advances in parallel computation (e.g., Eddy and Schervish 1986; Gardner, Gerard, Mowers, Nemeth, and Schnabel 1986) have made it possible for a network of microcomputers to act together as a parallel processor using data-flow algorithms (see O'Leary and Stewart 1985). A data-flow algorithm is one in which the sequence of computations is not scheduled a priori, but rather is determined by the order in which computations are completed. Many statistical problems can be…

并行计算在统计推断中的应用AI 解读

Recent advances in parallel computation (e.g., Eddy and Schervish 1986; Gardner, Gerard, Mowers, Nemeth, and Schnabel 1986) have made it possible for a network of microcomputers to act together as a parallel processor using data-flow algorithms (see O'Leary and Stewart 1985). A data-flow algorithm is one in which the sequence of computations is not scheduled a priori, but rather is determined by the order in which computations are completed. Many statistical problems can be…

Durbin–Watson 检验的局部最优性质AI 解读

Although originally designed to detect AR(1) disturbances in the linear-regression model, the Durbin-Watson test is known to have good power against other forms of disturbance behavior. In this paper, we identify disturbance processes involving any number of parameters against which the Durbin–Watson test is approximately locally best invariant uniformly in a range of directions from the null hypothesis. Examples include the sum of q independent ARMA(1,1) processes, certain…

特殊协方差结构下生长曲线的预测与估计AI 解读

The model considered here is a generalized multivariate analysis-of-variance model useful especially for many types of growth-curve problems, including biological growth and technology substitutions. It is defined as Yp × N = Xp×mτm×rAr×N + ∈p×N , where τ is unknown and X and A are known design matrices of ranks m < p and r < N, respectively. Further, the columns of ∈ are independent p-variate normal, with mean vector 0 and common covariance matrix Σ. In general, p is the…

连续空间过程的参数估计与模型辨识AI 解读

SUMMARY Formal parameter estimation and model identification procedures for continuous domain spatial processes are introduced. The processes are assumed to be adequately described by a linear model with residuals that follow a second-order stationary Gaussian random field and data are assumed to consist of noisy observations of the process at arbitrary sampling locations. A general class of two-dimensional rational spectral density functions with elliptic contours is used…

对误差方差错设更稳健的标准误AI 解读

SUMMARY For parameter estimators in linear models, variance estimates are proposed which are positive-semidefinite quadratic forms like the conventional ones but are less dependent on assumptions about error variance. Examples are given of their use in spatial analyses of field trials and analyses of series of trials.

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液体化学动力学的统计模型AI 解读

SUMMARY Statistical methods are used increasingly in theoretical chemistry. Applications range from the use of stochastic relaxation techniques in determining minimum energy molecular configurations to dynamical Monte Carlo simulations of molecular motion in liquids. This paper focuses on diffusion-controlled reactions in radiation chemistry. Here the interest is in describing the evolution of isolated clusters, containing a few chemically active particles, resulting from…

误差的空间自相关与线性回归中 OLS 的相对效率AI 解读

The article considers the efficiency of ordinary least squares (OLS) coefficient estimates relative to generalized least squares (GLS) in a linear regression model where the disturbances follow a spatial autocorrelation pattern. The main result is that the limiting relative efficiency of OLS, as correlation among disturbances increases, tends to either zero or unity for most design matrices and correlation patterns encountered in practice. Which of these cases applies…

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有向图的贝叶斯模型AI 解读

Holland and Leinhardt (1981) proposed a simple exponential model called the p 1 model for analyzing digraphs that arise in studies of networks. A digraph consists of a set of g nodes and a g × g adjacency matrix (Xij ), where Xij = 1 if node i relates to node j and Xij = 0 otherwise. The underlying cell probabilities pij = Pr(Xij = 1) are to be estimated from these dichotomous responses. The p 1 model imposes an additive structure on a log-odds version of the pij . It…

离散马尔可夫场推断：最简单的非平凡情形AI 解读

Markov fields provide a general context for describing the strength and structure of spatial interactions. The Gibbs—Markov equivalence theorem (Preston 1974) parameterizes Markov fields via their neighborhood structures, yielding exponential families in canonical form. Likelihood inference is, therefore, apparently straightforward. The requisite normalizing constants, however, are obstreperous. Even when asymptotic characterizations can be obtained, substantial location…

空间中位数与方向数据AI 解读

We introduce the normalized spatial median as an estimator of location for rotationally symmetric distributions on the hypersphere. We investigate some of its asymptotic properties and use them to obtain confidence regions for the modal direction of a distribution on the hypersphere. These results are then applied to the von Mises-Fisher distribution and to a contamination model. It is seen that the normalized spatial median can perform more efficiently than the normalized…

空间高斯过程协方差函数似然估计的问题AI 解读

Maximum likelihood has frequently been suggested as a way to estimate covariance parameters in spatial Gaussian processes. The results of some simple examples based on simulated data are discussed. It is shown by an example with real data that the profile likelihood can be multimodal, and that the global maximum may not correspond to a sensible value of the parameters.

空间中位数与方向数据AI 解读

We introduce the normalized spatial median as an estimator of location for rotationally symmetric distributions on the hypersphere. We investigate some of its asymptotic properties and use them to obtain confidence regions for the modal direction of a distribution on the hypersphere. These results are then applied to the von Mises-Fisher distribution and to a contamination model. It is seen that the normalized spatial median can perform more efficiently than the normalized…

非平稳空间数据的克里金预测AI 解读

Spatial data modeled to have come from a random function with a nonstationary mean are considered. The spatial prediction method known as kriging exploits second-order spatial correlation structure to obtain minimum variance predictions of certain average values of the random function. But to do so, it must be assumed that either the mean function (the drift) is known up to a constant or the second-order structure (the variogram) is known exactly. Knowledge of the drift…

缺失数据下时空 ARMAX 模型的估计与识别AI 解读

A method for modeling and fitting multivariate spatial time series data based on current spatial methodology coupled with the parameterization of the ARMAX model is presented. Because of the physical constraints imposed on multivariate data collection in both space and time, the estimation and identification procedures tolerate general patterns of missing or incomplete data.

缺失数据下时空 ARMAX 模型的估计与识别AI 解读

A method for modeling and fitting multivariate spatial time series data based on current spatial methodology coupled with the parameterization of the ARMAX model is presented. Because of the physical constraints imposed on multivariate data collection in both space and time, the estimation and identification procedures tolerate general patterns of missing or incomplete data.

管理决策的定量方法AI 解读

ciation of the exchange rate. Then Lopez-Claros argues that this was not practical, since interest rate data were inaccurate for Latin American countries, in part because of the numerous government regulations. The final modeling paper is written by Adcock. He develops a model to forecast the percentage of network terminating points on a given network service as a function of time and data transmission speed. Also described is a model for the take-up of a new service.

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多个 2×2 列联表共同优势比精确置信区间的计算AI 解读

A quadratic time network algorithm is provided for computing an exact confidence interval for the common odds ratio in several 2×2 independent contingency tables. The algorithm is shown to be a considerable improvement on an existing algorithm developed by Thomas (1975), which relies on exhaustive enumeration. Problems that would formerly have consumed several CPU hours can now be solved in a few CPU seconds. The algorithm can easily handle sparse data sets where asymptotic…

田间试验的线性模型、平滑与交叉验证AI 解读

Spatial methods for the analysis of agricultural field experiments are represented here as smoothing methods applied simultaneously with the estimation of treatment effects. Selection of both the form of the smoother and the degree of smoothing required may be based on cross-validation. Particular emphasis is placed in this paper on generalized least squares estimation in linear models, but the principle applies quite generally.

用于评估依赖关系的 χ 图AI 解读

This paper presents a graphical method to be used, in conjunction with a scatterplot, to investigate possible association of two variates as manifested in a sample of bivariate measurements. The method is designed so that the plot is approximately horizontal under independence, and under various forms of association it produces corresponding characteristic patterns. Examples given include application to study of regression residuals, dependence of two spatial point…