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随机删失观测下风险函数估计的半参数方法AI 解读

One method for estimating the hazard function is to use a parametric estimator, provided that the underlying distribution of the data can be assumed to belong to some well known family of distributions depending on an unknown, possibly vector-valued parameter. Another approach is to use nonparametric estimators, such as Cox's proportional hazard models, kernel hazard estimators, and so on. However, nonparametric estimators are less efficient than suitably chosen parametric…

生存数据的半参数贝叶斯分析AI 解读

This review article investigates the potential of Bayes methods for the analysis of survival data using semiparametric models based on either the hazard or the intensity function. The nonparametric part of every model is assumed to be a realization of a stochastic process. The parametric part, which may include a regression parameter or a parameter quantifying the heterogeneity of a population, is assumed to have a prior distribution with possibly unknown hyperparameters.…

带条件异方差的分数积分 ARMA 时间序列模型AI 解读

This article considers fractionally integrated autoregressive moving-average time series models with conditional heteroscedasticity, which combines the popular generalized autoregressive conditional heteroscedastic (GARCH) and the fractional (ARMA) models. The fractional differencing parameter d can be greater than 1/2, thus incorporating the important unit root case. Some sufficient conditions for stationarity, ergodicity, and existence of higher-order moments are derived.…

变点问题的鞅方法AI 解读

The changepoint problem for a binary sequence is considered. A test statistic based on recursive residuals is compared to the test statistic suggested by Pettitt. The new test statistic has more interesting properties for use in sequential testing. However, neither of the two test statistics dominates the other. Sequential versions of the martingale-based test, forward and reverse, are given and compared to other tests by means of a simulation study. The reverse martingale…

不完全依从研究中的处理效应界AI 解读

This article establishes nonparametric formulas that can be used to bound the average treatment effect in experimental studies in which treatment assignment is random but subject compliance is imperfect. The bounds provided are the tightest possible, given the distribution of assignments, treatments, and responses. The formulas show that even with high rates of noncompliance, experimental data can yield useful and sometimes accurate information on the average effect of a…

多个处理与对照比较的近似似然比检验AI 解读

Some parametric tests for comparing several treatments to a control are examined. Those tests developed earlier tend to rest on a single principle: Simplicity or power; those developed later attempt to fill the gap. We propose a new test that represents another such attempt. The basic idea is to find a simple statistic that is a good approximation to the likelihood ratio statistic. This leads to a power function similar to that of the likelihood ratio test, which is optimal…

共同协方差矩阵下两个多元正态总体的贝叶斯判别AI 解读

Here Bayesian and classical estimates of P, the probability that a new observation belongs to one of two multivariate normal populations with equal covariance matrices, are compared. In particular, the regions of location of a new observation for which the estimates differ are shown. The Bayesian and classical allocation rule contours are given and their differences highlighted. The posterior moments of L, the log-density ratio for a new observation, are given, and the…

有序分类数据分析的单变量随机切点理论AI 解读

A new theory is developed for nonparametric analyses of r x k contingency tables, where the columns correspond to k ordered categories. The work is motivated by concern that conventional nonparametric theory yields inferences concerning the given categories, but results are often interpreted as if for a continuum. Asymptotic distributions are derived under random cut-points models for the Mann-Whitney (-Wilcoxon) U statistic. A model is recommended under which the exact…

多项分布数据的拟合优度检验AI 解读

Several new test procedures are proposed for assessing the goodness of fit of a postulated multinomial distribution. The new tests are Neyman smooth-type tests with orders selected adaptively from the data. They are shown, through Fourier and large-sample analyses, to provide potential improvements over classical methods in terms of their ability to detect certain types of alternatives. Simulation results and a real example illustrate the finite-sample validity of the…

协变量匹配的函数均值差单侧检验AI 解读

When testing hypotheses about the effects of different treatments, variation among covariates can become confounded with that between treatments unless the treatments are applied using paired covariates. In the context of unpaired covariates, we propose implicit covariate-matching methods for testing the hypothesis that one treatment effect is greater than another. The methods are founded on the assumption that the mean treatment effect, conditional on the covariate, is a…

高阶偏差核密度估计方法的比较AI 解读

We consider many kernel-based density estimators, all theoretically improving bias from O(h 2), as the smoothing parameter h → 0, to O(h 4). Examples include higher-order kernels, variable kernel methods, and transformation and multiplicative bias-correction approaches. We stress the similarities between what appear to be disparate approaches. In particular, we show how the mean squared errors of all methods have the same form. Our main practical contribution is a…

回归中的子序列方法AI 解读

We extend subseries methods for stationary sequences to the regression setting. To estimate sampling distributions, the subseries approach computes the statistic of interest on all possible subseries of a shorter length than the original series, and uses the distribution of these replicates to mimic the distribution of the original statistic. For proper choice of subseries length, the regression parameters can be estimated to order O(n -2/3), thus improving on the normal…

广义半线性模型的有效估计AI 解读

The generalized semilinear model (GSLIM) extends the generalized linear model by allowing the addition of an unknown smooth function to the predictor parameter, producing a semiparametric model. Some previously proposed score-based estimators for the parametric component in this model are not √n consistent. We propose efficient estimators for both the parametric and nonparametric components of the GSLIM. The estimator for the parametric component is the solution to an…

纵向数据中的部分条件均值建模AI 解读

We propose a general modeling approach to longitudinal data that is a hybrid of the marginal regression models of Zeger and Liang and of the classical transition models such as used in time series analyses. Rather than conditioning at time t only on covariate values, as is typical with the marginal approach, or on the entire history of the process up to t, as is typical with the transition model approach, we suggest models that condition on a subset of the process history.…

脆弱性模型估计的边际似然方法AI 解读

A marginal likelihood approach is proposed for estimating the parameters in a frailty model using clustered survival data. To overcome the analytic intractability of the marginal likelihood function, we propose a Monte Carlo approximation using the technique of importance sampling. Implementation is by means of simulations from the uniform distribution. The suggested method can cope with censoring and unequal cluster sizes and can be applied to any frailty distribution with…

删失回归中扩展的加权对数秩估计函数AI 解读

In the censored regression model, some regression estimators are introduced using weighted integrals of the log-rank estimating functions. Their limiting covariance matrices do not involve the error density and can be reliably estimated. Inference can then be easily obtained. Some of these estimators have high asymptotic efficiency at some important submodels. Some lack-of-fit tests are derived that require little extra computing time. These tests are asymptotically normal…

比例优势模型的最大似然估计AI 解读

We consider maximum likelihood estimation of the parameters in the proportional odds model with right-censored data. The estimator of the regression coefficient is shown to be asymptotically normal with efficient variance. The maximum likelihood estimator of the unknown monotonic transformation of the survival time converges uniformly at a parametric rate to the true transformation. Estimates for the standard errors of the estimated regression coefficients are obtained by…

区间删失比例优势失效时间回归模型的筛估计AI 解读

Estimation of the proportional-odds failure-time regression model with interval censoring is considered. Conditions that allow for positive information for the regression parameter are discussed. The efficient score is characterized by a Fredholm equation of the second kind. The sieve maximum likelihood estimator for the finite-dimensional regression parameter is shown to be asymptotically normal with √n convergence rate and to achieve the information bound. Data analysis…

删失数据非参数最大似然估计的混合计算算法AI 解读

We present a hybrid algorithm for nonparametric maximum likelihood estimation from censored data when the log-likelihood is concave. The hybrid algorithm uses a composite algorithmic mapping combining the expectation-maximization (EM) algorithm and the (modified) iterative convex minorant (ICM) algorithm. Global convergence of the hybrid algorithm is proven; the iterates generated by the hybrid algorithm are shown to converge to the nonparametric maximum likelihood estimator…

层级选择模型及其在元分析中的应用AI 解读

Hierarchical selection models are introduced and shown to be useful in meta-analysis. These models combine the use of hierarchical models, allowing investigation of variability both within and between studies, and weight functions, allowing modeling of nonrandomly selected studies. Markov chain Monte Carlo (MCMC) methods are used to estimate the hierarchical selection model. This is first illustrated for known weight functions, and then extended to allow for estimation of…

利用正态混合模型进行实用贝叶斯密度估计AI 解读

Mixtures of normals provide a flexible model for estimating densities in a Bayesian framework. There are some difficulties with this model, however. First, standard reference priors yield improper posteriors. Second, the posterior for the number of components in the mixture is not well defined (if the reference prior is used). Third, posterior simulation does not provide a direct estimate of the posterior for the number of components. We present some practical methods for…

用 TSMARS 建模海表温度的长程依赖、非线性与周期现象AI 解读

We analyze a time series of 20 years of daily sea surface temperatures measured off the California coast. The temperatures exhibit quite complicated features, such as effects on many different time scales, nonlinear effects, and long-range dependence. We show how a time series version of the multivariate adaptive regression splines (MARS) algorithm, TSMARS, can be used to obtain univariate adaptive spline threshold autoregressive models that capture many of the physical…

用小波分析沿岸次潮汐海平面波动AI 解读

Subtidal coastal sea level fluctuations affect coastal ecosystems and the consequences of destructive events such as tsunamis. We analyze a time series of subtidal fluctuations at Crescent City, California, during 1980–1991 using the maximal overlap discrete wavelet transform (MODWT). Our analysis shows that the variability in these fluctuations depends on the season for scales of 32 days and less. We show how the MODWT characterizes nonstationary behavior succinctly and how…