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噪声图像上下文分类的方向邻域方法AI 解读

The directional neighborhoods approach (DNA) to classifying pixels and reconstructing images from remotely sensed noisy data is a newly proposed computer-intensive procedure that is partly Bayesian and partly data analytic. It uses the observational data to select an optimal, generally asymmetric, but relatively homogeneous neighborhood for contextually classifying pixels. A criterion for “homogeneity of neighborhood” is developed. DNA involves two stages: a zero-neighbor…

从蒙特卡洛检验构造置信区间AI 解读

It is argued that confidence sets can be derived from Monte Carlo tests by exploiting the equivalence between confidence estimation and hypothesis testing.The approach benefits from the wide applicability of this class of tests and the high level accuracy that is passed on to the confidence sets.The main problem is whether the confidence sets are simple enough to be of practical interest.A conservative general approximation is given, but most of the paper deals with exact…

生成函数计算置换分布及离散数据敏感性分析AI 解读

Generating functions provide a simple and elegant way to describe probability or frequency distributions of discrete statistics and, in particular, permutation distributions. They are also a computational tool. Many efficient algorithms, including those described as fast Fourier transform methods, network methods, and multiple shift methods, are different implementations of the recursions needed to evaluate generating functions efficiently. Our goals here are twofold. First,…

最大似然分析中的带符号根离差剖面与置信区间AI 解读

We investigate a natural extension of the profile t plot of Bates and Watts to a general parametric function g(θ) of the parameters θ in a general maximum likelihood analysis. Although the basic purpose of the extension, called the signed root deviance profile (SRDP), is to construct likelihood ratio (LR) confidence intervals for g(θ), it has various other applications that significantly extend its usefulness. The tangent to the plot of the SRDP at the maximum likelihood…

复访调查方法有效性的评价程序：劳动力数据应用AI 解读

Several types of reinterview surveys have been designed to measure the different kinds of response errors that occur in survey data. This article is based on the reinterview procedures conducted by the U.S. Census Bureau in its monthly Current Population Survey. We present estimates of the misclassification error rates associated with the original survey data collection procedures and the reinterview methods. A new procedure enables us to estimate the dependence between the…

利用前瞻性数据估计HIV母婴传播率与儿童艾滋病潜伏期AI 解读

This article considers the estimation of the rate of vertical human immunodeficiency virus (HIV) transmission and the pediatric acquired immune deficiency syndrome (AIDS) incubation period using data from birth cohort studies. Standard methods of analysis, which ignore children whose infection status is not established, may lead to biased estimates. Methods based on modeling the disappearance of HIV antibody or appearance of virus are inefficient, as they essentially rely on…

二元结局与有序依从性的安慰剂对照临床试验因果推断AI 解读

We propose a likelihood-based method to analyze the causal effect of partial compliance (i.e., unplanned partial exposure to treatment or placebo) in the LRC-CPPT data, a prevention trial with long term follow-up previously analyzed by Efron and Feldman. Initially, we construct ordered compliance categories and dichotomize response. Assuming increased exposure to cholestyramine does not increase cholesterol, we estimate exposure—response curves in different compliance…

摘要暂缺

以ARMA(1,1)为备择的序列相关检验AI 解读

This paper is concerned with tests for serial correlation in time series and in the errors of regression models. In particular, the nonstandard problem of testing for white noise against ARMA(1,1) alternatives is considered. Sup Lagrange multiplier (LM) and exponential average LM tests are introduced and are shown to be asymptotically admissible for ARMA(1,1) alternatives. In addition, they are shown to be consistent against all (weakly stationary strong mixing) non-white…

用 EM 算法拟合纵向数据的一阶条件自回归模型AI 解读

An EM algorithm fits a state-space formulation of the longitudinal regression model in which a continuous response depends on the lagged response and both time-dependent and time-independent covariates. The baseline response depends only on covariates. The model handles both missing data and Gaussian measurement error on both response and continuous covariates. The E step uses the Kalman filter and associated filtering algorithms to update the unknown true response and…

插补调查数据的自助法AI 解读

Most surveys use imputation to compensate for missing data. However, treating the imputed data set as the complete data set and directly applying existing methods (e.g., the linearization, the jackknife, and the bootstrap) for variance estimation and/or statistical inference does not produce valid results, because these methods do not account for the effect of missing data and/or imputation. In this article we show that correct bootstrap estimates can be obtained by…

地震时间演化的贝叶斯分析AI 解读

We adopt a Bayesian approach to analyze the occurrence times of seismic events and their magnitudes. We choose an epidemic model for the process of occurrence times conditional on the observed magnitude values. The locations of, and dependencies between, the model parameters are determined on the basis of historical and physical information. The overall prior variability is deliberately made diffuse. We generate samples from the joint posterior distribution of the model…

右截断数据下的二元估计AI 解读

Bivariate estimation with survival data has received considerable attention recently; however, most of the work has focused on random censoring models. Another common feature of survival data, random truncation, is considered in this study. Truncated data may arise if the time origin of the events under study precedes the observation period. In a random right-truncation model, one observes the lid samples of (Y, T) only if (Y less than or equal to T), where Y is the variable…

随机序约束下生存概率的贝叶斯推断AI 解读

In the statistical analysis of survival data arising from two populations, it often happens that the analyst knows, a priori, that the life lengths in one population are stochastically shorter than those in the other. Nevertheless, survival probability estimates, if determined separately from the corresponding samples, may not be consistent with this prior assumption, because of inherent statistical variability in the observations. This problem has been considered in a…

针对单侧备择的简单多元检验AI 解读

A simple test for multivariate normal data is proposed that has good power for alternatives where the mean vector tends to be positive. The test rejects if the quadratic form of the sample mean vector exceeds its 2α critical value and the sum of the elements of the mean vector exceeds zero. The proposed test is shown to have type I error rate equal to α whether or not the covariance matrix is known. Tight bounds on the power of the proposed test are provided, and the test is…

从多项响应数据恢复信息的最大熵方法AI 解读

The classical maximum entropy (ME) approach to estimating the unknown parameters of a multinomial discrete choice problem, which is equivalent to the maximum likelihood multinomial logit (ML) estimator, is generalized. The generalized maximum entropy (GME) model includes noise terms in the multinomial information constraints. Each noise term is modeled as the mean of a finite set of a priori known points in the interval [−1,1] with unknown probabilities where no parametric…

连续时间中的纵向有序响应数据分析AI 解读

A simple Markov model is developed for assessing the predictive effect of time-dependent covariates on an intermittently observed ordinal response in continuous time. This is accomplished by reparameterizing an ergodic intensity matrix in terms of its equilibrium distribution and a parametrically independent component that assesses the rate of movement between ordinal categories. The effect of covariates on the equilibrium distribution can then be modeled using any link…

协变量含误差的病例对照研究：半参数混合方法AI 解读

Methods are devised for estimating the parameters of a prospective logistic model in a case-control study with dichotomous response D that depends on a covariate X. For a portion of the sample, both the gold standard X and a surrogate covariate W are available; however, for the greater portion of the data, only the surrogate covariate W is available. By using a mixture model, the relationship between the true covariate and the response can be modeled appropriately for both…

现时状态数据分析的半参数比例优势回归模型AI 解读

An approach to covariate analysis of current status data is described. The method is applicable when the logit of the conditional probability of survival given the covariates is some increasing function of time plus a linear combination of the covariates. The approach is based on approximating the infinite-dimensional nuisance parameter, the baseline log-odds of failure, with a step function, and carrying out a maximum likelihood procedure. The resulting finite dimensional…

回归问题中实用的小样本渐近近似AI 解读

Saddlepoint approximations are derived for sums of independent, but not necessarily identically distributed random variables, along with generalizations to estimating equations and multivariate problems. These results are particularly useful for accurately approximating the distribution of regression coefficients. General formulas are given for the distribution of the coefficients arising out of a generalized linear model with both canonical and noncanonical link functions.…

一般线性模型中响应变量的测量误差AI 解读

Problems where there is measurement error in the response variable in a general linear model are considered. With Y denoting the true value and U the observed/surrogate value, a rich class of measurement error models is considered in which (a) the mean of U given Y = y can be either linear or nonlinear in y, (b) the variance of U given Y = y can depend on y, and (c) the parameters in the model for U given Y can change across observations in the study. This could occur, for…

离散化事件序列的若干模型AI 解读

A discretized series of events is a binary time series that indicates whether or not events of a point process in the line occur in successive intervals. Such data are common in environmental applications. We describe a class of models for them, based on an unobserved continuous-time discrete-state Markov process, which determines the rate of a doubly stochastic Poisson process, from which the binary time series is constructed by discretization. We discuss likelihood…

弱假设下的自相关推断AI 解读

In this article we consider the large-sample behavior of estimates of autocorrelations and autoregressive moving average (ARMA) coefficients, as well as their distributions, under weak conditions. Specifically, the usual text book formulas for variances of these estimates are based on strong assumptions and should not be routinely applied without careful consideration. Such is the case when the time series follows an ARMA process with uncorrelated innovations that may not be…

重复样本直方图AI 解读

The “replicate histogram” is introduced as a simple diagnostic tool for describing the sampling distribution of a general statistic. It can be applied to virtually any statistic that has an asymptotic distribution, and the data on which the statistic is computed may be serially or spatially dependent. The method is completely sample based, requiring no theoretical analysis by the user, no knowledge of the proper standardization for the statistic, and no specification of the…