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多元分类响应的联合分布与边际分布同步建模AI 解读

We discuss model-fitting methods for analyzing simultaneously the joint and marginal distributions of multivariate categorical responses. The models are members of a broad class of generalized logit and loglinear models. We fit them by improving a maximum likelihood algorithm that uses Lagrange's method of undetermined multipliers and a Newton-Raphson iterative scheme. We also discuss goodness-of-fit tests and adjusted residuals, and give asymptotic distributions of model…

基于惩罚 Whittle 似然的非参数谱密度估计AI 解读

The penalized likelihood approach is not well developed in time series analysis, even though it has been applied successfully in a number of nonparametric function estimation problems. Chow and Grenander proposed a penalized likelihood-type approach to the nonparametric estimation of the spectral density of Gaussian processes. In this article this estimator is extended to more general stationary processes, its practical implementation is developed in some detail, and some…

通过重加权使回归协变量呈椭圆对称分布AI 解读

We investigate a method of constructing weights to induce elliptically contoured covariates in regression analyses. Much recent work in regression has identified various data analytic and model robustness advantages associated with such covariates. In particular, new estimation methods like SIR, SIRII, SAVE, and PHD have been built around the assumption of elliptically contoured covariates. Finite samples of regression covariates may deviate from this ideal in practice, and…

仅少数成分相关时的预测方法比较AI 解读

We consider prediction in a multiple regression model where we also look on the explanatory variables as random. If the number of explanatory variables is large, then the common least squares multiple regression solution may not be the best one. We give a methodology for comparing certain alternative prediction methods by asymptotic calculations and perform such a comparisons for four specific methods. The results indicate that none of these methods dominates the others, and…

相关曲线：回归局部解释方差的度量AI 解读

We call (a model for) an experiment heterocorrelatious if the strength of the relationship between a response variable Y and a covariate X is different in different regions of the covariate space. For such experiments we introduce a correlation curve that measures heter-ocorrelaticity in terms of the variance explained by regression locally at each covariate value. More precisely, the squared correlation curve is obtained by first expressing the usual linear model “variance…

删失回归：局部线性近似及其应用AI 解读

Various statistical tools are available for modeling the relationship between response and covariate if the data are fully observable. In the situation of censored data, however, those tools are no longer directly applicable. This article provides an easily implemented methodology for modeling the association, based on censored data. The form of the regression relationship will be completely determined by the data; no assumptions are made about this form. Basic ideas behind…

基于排序集样本的非参数最大似然估计AI 解读

A ranked set sample consists entirely of independently distributed order statistics and can occur naturally in many experimental settings, including problems in reliability. When each ranked set from which an order statistic is drawn is of the same size, and when the statistic of each fixed order is sampled the same number of times, the ranked set sample is said to be balanced. Stokes and Sager have shown that the edf F n of a balanced ranked set sample from the cdf F is an…

观测值函数的密度估计AI 解读

Density estimates, such as histograms and more sophisticated versions, are important in applied and theoretical statistics. In applied statistics, a density estimate gives the data analyst a graphical overview of the shape of the distribution. This overview allows the data analyst to arrive immediately at a qualitative impression of the location, scale, and various aspects of the extremes of the distribution. In theoretical statistics, the shape of the density allows the…

混沌系统中的估计函数方法AI 解读

Berliner considered Bayesian and likelihood-based approaches for estimation and prediction in a chaotic system with measurement error. This article proposes the use of estimating functions for this problem. Logistic and exponential maps are analyzed. Estimators are shown to be consistent and asymptotically normal. Small-sample behavior is studied with simulations.

半参数模型中的拟似然估计AI 解读

Suppose the expected value of a response variable Y may be written h(Xβ +γ(T)) where X and T are covariates, each of which may be vector-valued, β is an unknown parameter vector, γ is an unknown smooth function, and h is a known function. In this article, we outline a method for estimating the parameter β, γ of this type of semiparametric model using a quasi-likelihood function. Algorithms for computing the estimates are given and the asymptotic distribution theory for the…

空间数据一般统计量矩的非参数估计AI 解读

A statistic s(·) is computed on spatially indexed data {X i : i ∈ D}, where D is a finite subset of the integer lattice Z2. We propose a simple nonparametric method for estimating the moments (e.g., variance, skewness) of s(D), using only the observed data at hand. The method uses “replicates” of s(·) computed on smaller subsets of D. No explicit knowledge of the underlying spatial dependence mechanism is needed, and the marginal distribution of X i may also be unknown. The…

缺失数据、插补与自助法AI 解读

Missing data refers to a class of problems made difficult by the absence of some portions of a familiar data structure. For example, a regression problem might have some missing values in the predictor vectors. This article concerns nonparametric approaches to assessing the accuracy of an estimator in a missing data situation. Three main topics are discussed: bootstrap methods for missing data, these methods' relationship to the theory of multiple imputation, and…

伽马射线暴数据的生存分析AI 解读

Gamma-ray bursts are short but powerful pulses of electromagnetic radiation coming from space. Specially equipped satellites have observed the arrival of several hundred bursts during the past two decades. The origin of these bursts, whether from near the earth, across the galaxy, or out of the deep cosmos, has become a major question for astronomers. At the heart of this question lies a statistical puzzle relating to familiar issues in survival analysis: Kaplan-Meier-type…

频率先验信念的实证检验：方法与先天性心脏病案例AI 解读

We consider the problem of critiquing prior beliefs concerning the distribution of a discrete random variable in the light of a sequentially obtained sample. A topical application concerns a probabilistic expert system for the diagnosis of congenital heart disease, which requires specification of a large number of conditional probabilities that are initially imprecisely estimated by a suitable “expert.” These prior beliefs may be formally updated as data become available,…

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利用卡尔曼滤波估计、预测与插补非平稳序列AI 解读

We show how our definition of the likelihood of an autoregressive integrated moving average (ARIMA) model with missing observations, alternative to that of Kohn and Ansley and based on the usual assumptions made in estimation of and forecasting with ARIMA models, permits a direct and standard state-space representation of the nonstationary (original) data, so that the ordinary Kalman filter and fixed point smoother can be efficiently used for estimation, forecasting, and…

Mallows Cp 的稳健版本AI 解读

We present a robust version of Mallows's C P for regression models. It is defined by RC P = W Pσ2 - (U P - V P), where W P = ω i ω2 i r 2 i is a weighted residual sum of squares computed from a robust fit of model P, σ2 is a robust and consistent estimator of σ2 in the full model, and U P and V P are constants depending on the weight function and the number of parameters in model P. Good subset models are those with RC P close to V P or smaller than V P. When the weights are…

线性模型中影响有界且具有高崩溃点的检验程序AI 解读

Three classes of testing procedures based on one-step high breakdown point bounded influence estimators, for testing subhypotheses in linear models are developed. These are drop-in-dispersion, Wald-type, and score-type tests. The asymptotic distributions of these testing procedures are obtained under the null hypothesis and under contiguous alternatives. Their stability properties are studied in terms of their influence functions and breakdown points. It is shown that the…

具有回降影响函数的正则秩估计AI 解读

A study is made of some unusual location estimates first proposed in 1977 by J. S. Maritz, M. Wu, and R. G. Staudte, Jr., who established some strong robustness properties of these estimates, such as redescending influence functions and, in some cases, full efficiency at the Cauchy model. It is further shown here that the estimates, called M-W-S estimates, are derivable from a rank-based scheme founded on convex functions and hence are regular, are unique, and have…

定号二次型联合分布的近似AI 解读

Multidimensional Wilson-Hilferty transformations support Gaussian approximations to certain joint distributions of quadratic forms in jointly Gaussian variates. Central and noncentral joint distributions are studied and applications are noted. Parameters of the approximating distributions are given up to terms of order o(v −2) in the degrees of freedom v. Numerical studies validate using these approximations over a range of parameters for an essential subclass of the…

内陆水体限制性营养关系的统计模型AI 解读

The ecological theory of limiting factors holds that the observed level of response in a biological process will be governed by the input factor in least supply—the limiting factor. This theory has formed the basis for numerous attempts by aquatic ecologists to describe the relation between the biological productivity of inland waters and the availability of plant nutrients required for algal growth. Regression analysis has been the primary statistical tool used in the…

气象场的统计时空建模方法AI 解读

In this article we develop a random field model for the mean temperature over the region in the northern United States covering eastern Montana through the Dakotas and northern Nebraska up to the Canadian border. The readings are temperatures at the stations in the U.S. historical climatological network. The stochastic structure is modeled by a stationary spatial-temporal Gaussian random field. For this region, we find little evidence of temporal dependence while the spatial…

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