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Exploiting occurrence times in likelihood inference for componentwise maxima

利用发生时点对逐分量最大值进行似然推断

Multivariate extreme value distributions arise as the limiting distributions of normalised componentwise maxima. They are often used to model multivariate data that can be regarded as the componentwise maxima of some unobserved underlying multivariate process. In many applications we have extra information. We often know the locations of the maxima within the underlying process. If the process is temporal this knowledge is frequently available through the dates on which the…

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Adaptive two-stage test procedures to find the best treatment in clinical trials

临床试验中寻找最佳治疗的自适应两阶段检验

A main objective in clinical trials is to find the best treatment in a given finite class of competing treatments and then to show superiority of this treatment against a control treatment. The traditional procedure estimates the best treatment in a first trial. Then in an independent second trial superiority of this treatment, estimated as best in the first trial, is to be shown against the control treatment by a size α test. In this paper we investigate these two trials of…

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Nonparametric tests for and against likelihood ratio ordering in the two-sample problem

两样本问题中支持与反对似然比序的非参数检验

We derive nonparametric procedures for testing for and against likelihood ratio ordering in the two-population setting with continuous distributions. We account for this ordering by examining the least concave majorant of the ordinal dominance curve formed from the nonparametric maximum likelihood estimators of the continuous distribution functions F and G. In particular, we focus on testing equality of F and G versus likelihood ratio ordering and testing for a violation of…

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Standard errors and covariance matrices for smoothed rank estimators

平滑秩估计量的标准误与协方差矩阵

A ‘pseudo-Bayesian’ interpretation of standard errors yields a natural induced smoothing of statistical estimating functions. When applied to rank estimation, the lack of smoothness which prevents standard error estimation is remedied. Efficiency and robustness are preserved, while the smoothed estimation has excellent computational properties. In particular, convergence of the iterative equation for standard error is fast, and standard error calculation becomes…

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Discrete-transform approach to deconvolution problems

反卷积问题的离散变换方法

If Fourier series are used as the basis for inference in deconvolution problems, the effects of the errors factorise out in a way that is easily exploited empirically. This property is the consequence of elementary addition formulae for sine and cosine functions, and is not readily available when one is using methods based on other orthogonal series or on continuous Fourier transforms. It allows relatively simple estimators to be constructed, founded on the addition of…

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Bayesian exponentially tilted empirical likelihood

贝叶斯指数倾斜经验似然

While empirical likelihood has been shown to exhibit many of the properties of conventional parametric likelihoods, a formal probabilistic interpretation has so far been lacking. We show that a likelihood function very closely related to empirical likelihood naturally arises from a nonparametric Bayesian procedure which places a type of noninformative prior on the space of distributions. This prior gives preference to distributions having a small support and, among those…

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Calibrated interpolated confidence intervals for population quantiles

总体分位数的校准插值置信区间

Beran & Hall's (1993) simple linear interpolation provides a very convenient approach for constructing nonparametric confidence intervals for population quantiles based on a random sample of size n. We show that the coverage error of the interpolated interval, which is of order O(n−1), can be improved upon by calibrating the nominal coverage level. Three distinct methods of calibration are considered. The analytical and Monte Carlo methods succeed in reducing the order of…

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Semiparametric regression analysis of mean residual life with censored survival data

删失生存数据平均剩余寿命的半参数回归分析

As function of time t, a mean residual life is the remaining life expectancy of a subject given survival up to t. The proportional mean residual life model, proposed by Oakes & Dasu (1990), provides an alternative to the Cox proportional hazards model for studying the association between survival times and covariates. In the presence of censoring, we use counting process theory to develop semiparametric inference procedures for the regression coefficients of the Oakes–Dasu…

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Power of edge exclusion tests in graphical Gaussian models

高斯图模型中删边检验的功效

Asymptotic multivariate normal approximations to the joint distributions of edge exclusion test statistics for saturated graphical Gaussian models are derived. Non-signed and signed square-root versions of the likelihood ratio, Wald and score test statistics are considered. Noncentral chi-squared approximations are also considered for the non-signed versions. These approximations are used to estimate the power of edge exclusion tests and an example is presented.

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Multiscale generalised linear models for nonparametric function estimation

用于非参数函数估计的多尺度广义线性模型

We present a method for extracting information about both the scale and trend of local components of an inhomogeneous function in a nonparametric generalised linear model. Our multiscale framework combines recursive partitions, which allow for the incorporation of scale in a natural manner, with systems of piecewise polynomials supported on the partition intervals, which serve to summarise the smooth trend within each interval. Our estimators are formulated as solutions of…

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Semiparametric analysis of short-term and long-term hazard ratios with two-sample survival data

两样本生存数据中短期与长期风险比的半参数分析

Standard approaches to semiparametric modelling of two-sample survival data are not appropriate when the two survival curves cross. We introduce a two-sample model that accommodates crossing survival curves. The two scalar parameters of the model have the interpretations of being the short-term and long-term hazard ratios respectively. The time-varying hazard ratio is expressed semiparametrically by the two scalar parameters and an unspecified baseline distribution. The new…

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On testing for unit roots and the initial observation

单位根检验与初始观测值

Recent work has highlighted the crucial dependence of the power of existing unit root tests on the deviation of the initial observation from the deterministic component of the series. In practical applications, it is useful to have a test available with power more robust to the initial condition. In this paper, we propose such a procedure based on a data-dependent weighted average of the standard Dickey--Fuller and Elliott--Rothenberg--Stock tests. Simulation of the new…

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Testing for stationarity in heterogeneous panel data where the time dimension is finite

时间维度有限时异质面板数据的平稳性检验

and hence makes the test valid for any (T, N) combination. The asymptotic distributions of the tests are derived under the null and are shown to be normally distributed. Their moments for T fixed are derived analytically using Ghazal's (1994, Statistics and Probability letters 20, 313--319) 1 lemma 1. Finite sample size and power are considered in a Monte Carlo experiment. The proposed tests have empirical sizes that are very close to the nominal 5% level. The Monte Carlo…

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Bootstrap estimation of covariance matrices via the percentile method

Consistency of the bootstrap second moments does not usually follow from the proofs of consistency of the distribution of the bootstrap. Here it is shown that the convergence of the bootstrap distribution to a normal variate implicitly defines a consistent estimator for the asymptotic second moments. The estimator is based on the L-estimation of the scale parameter of arbitrary linear combinations of the bootstrap sequence and uses Classical Minimum Distance techniques to…

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False Discovery Rate–Adjusted Multiple Confidence Intervals for Selected Parameters

所选参数的错误发现率调整多重置信区间

Often in applied research, confidence intervals (CIs) are constructed or reported only for parameters selected after viewing the data. We show that such selected intervals fail to provide the assumed coverage probability. By generalizing the false discovery rate (FDR) approach from multiple testing to selected multiple CIs, we suggest the false coverage-statement rate (FCR) as a measure of interval coverage following selection. A general procedure is then introduced,…

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Classification of Missense Mutations of Disease Genes

疾病基因错义突变的分类

Clinical management of individuals found to harbor a mutation at a known disease-susceptibility gene depends on accurate assessment of mutation-specific disease risk. For missense mutations (MMs)-mutations that lead to a single amino acid change in the protein coded by the gene-this poses a particularly challenging problem. Because it is not possible to predict the structural and functional changes to the protein product for a given amino acid substitution, and because…

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Sequential Monte Carlo Methods for Statistical Analysis of Tables

表格统计分析的序贯蒙特卡洛方法

We describe a sequential importance sampling (SIS) procedure for analyzing two-way zero–one or contingency tables with fixed marginal sums. An essential feature of the new method is that it samples the columns of the table progressively according to certain special distributions. Our method produces Monte Carlo samples that are remarkably close to the uniform distribution, enabling one to approximate closely the null distributions of various test statistics about these…

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Functional Association Models for Multivariate Survival Processes

多变量生存过程的函数型关联模型

We consider multivariate temporal processes that are continuously observed within overlapping time windows. The intended application is in censored multistate and multivariate survival settings, where point processes are continuously observed. These data differ from other functional data, like longitudinal data, which are discretely observed at irregular times. Existing functional approaches to survival processes use intensity models, which require smoothing and depend…

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Homogeneous Linear Predictor Models for Contingency Tables

列联表的齐次线性预测模型

Maximum likelihood (ML) inference for the class of homogeneous linear predictor (HLP) models for contingency tables is described. HLP models constrain the expected table counts m through L(m) = Xβ, where the link L is allowed to be a many-to-one, nonlinear function. Generalized log-linear, association trend, marginal cumulative probit, and conditional marginal homogeneity models are given as specific examples. ML fit results, which include point estimates, goodness-of-fit…

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Variance Estimation in a Model With Gaussian Submodels

具有高斯子模型结构的方差估计

This paper considers the problem of estimating the dispersion parameter in a Gaussian model which is intermediate between a model where the mean parameter is fully known (fixed) and a model where the mean parameter is completely unknown. One of the goals is to understand the implications of the two-step process of first selecting a model among a finite number of sub-models, and then estimating a parameter of interest after the model selection, but using the same sample data.…

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Constrained Inverse Regression for Incorporating Prior Information

用于纳入先验信息的约束逆回归

Inverse regression methods facilitate dimension-reduction analyses of high-dimensional data by extracting a small number of factors that are linear combinations of the original predictor variables. But the estimated factors may not lend themselves readily to interpretation consistent with prior information. Our approach to solving this problem is to first incorporate prior information via theory- or data-driven constraints on model parameters, and then apply the proposed…

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Efficient Semiparametric Marginal Estimation for Longitudinal/Clustered Data

纵向与聚类数据的有效半参数边际估计

We consider marginal generalized semiparametric partially linear models for clustered data. Lin and Carroll derived the semiparametric efficient score function for this problem in the multivariate Gaussian case, but they were unable to construct a semiparametric efficient estimator that actually achieved the semiparametric information bound. Here we propose such an estimator and generalize the work to marginal generalized partially linear models. We investigate asymptotic…

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Approximate and Asymptotic Distributions of Chi-Squared–Type Mixtures With Applications

卡方型混合分布的近似与渐近分布及其应用

In this article we study how to approximate a random variable T of general chi-squared–type mixtures by a random variable of the form via matching the first three cumulants. The approximation error bounds for the density functions of the chi-squared approximation and the normal approximation are established. Applications of the results to some nonparametric goodness-of-fit tests, including those tests based on orthogonal series, smoothing splines, and local polynomial…

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Causal Inference Using Potential Outcomes

使用潜在结果进行因果推断

Causal effects are defined as comparisons of potential outcomes under different treatments on a common set of units. Observed values of the potential outcomes are revealed by the assignment mechanism—a probabilistic model for the treatment each unit receives as a function of covariates and potential outcomes. Fisher made tremendous contributions to causal inference through his work on the design of randomized experiments, but the potential outcomes perspective applies to…

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