论文检索

“解析”小波阈值化AI 解读

We introduce so-called analytic stationary wavelet transform thresholding where, using the discrete Hilbert transform, we create a complex-valued ‘analytic’ vector from which an amplitude vector is defined. Thresholding of a real-valued wavelet coefficient at some transform level is carried out according to the corresponding value in this amplitude vector; relevant statistical results follow from properties of the discrete Hilbert transform. Analytic stationary wavelet…

干扰参数与投影估计函数中的一个悖论AI 解读

This paper is concerned with a paradox associated with parameter estimation in the presence of nuisance parameters. In a statistical model with unknown nuisance parameters, the efficiency of an estimator of a parameter usually increases when the nuisance parameters are known. However the opposite phenomenon can sometimes occur. In this paper, we elucidate the occurrence of this paradox by examining estimating functions. In particular, we focus on the projected estimating…

自适应聚类双重抽样AI 解读

We present a multi-phase variant of adaptive cluster sampling which allows the sampler to control the number of measurements of the variable of interest. A first-phase sample is selected using an adaptive cluster sampling design based on an inexpensive auxiliary variable associated with the survey variable. Then the network structure of the adaptive cluster sample is used to select an ordinary one-phase or two-phase subsample of units and the values of the survey variable…

通过非参数评估真实协变量分布校正协变量误差AI 解读

A well-known and useful method for generalised regression analysis when a linear covariate x is available only through some approximation z is to carry out more or less the usual analysis with E(x|z) substituted for x. Sometimes, but not always, the quantity var (x|z) should be used to allow for overdispersion introduced by this substitution. These quantities involve the distribution of true covariates x, and with some exceptions this requires assessment of that distribution…

一种半参数变点模型AI 解读

A semiparametric changepoint model is considered and the empirical likelihood method is applied to detect the change from a distribution to a weighted distribution in a sequence of independent random variables. The maximum likelihood changepoint estimator is shown to be consistent. The empirical likelihood ratio test statistic is proved to have the same limit null distribution as that with parametric models. A data-based test for the validity of the models is also proposed.…

函数型测量误差模型的局部有效半参数估计量AI 解读

A class of semiparametric estimators are proposed in the general setting of functional measurement error models. The estimators follow from estimating equations that are based on the semiparametric efficient score derived under a possibly incorrect distributional assumption for the unobserved ‘measured with error’ covariates. It is shown that such estimators are consistent and asymptotically normal even with misspecification and are efficient if computed under the truth. The…

条件密度估计的交叉验证方法AI 解读

We extend the idea of crossvalidation to choose the smoothing parameters of the ‘double-kernel’ local linear regression for estimating a conditional density. Our selection rule optimises the estimated conditional density function by minimising the integrated squared error. We also discuss three other bandwidth selection rules, an ad hoc method used by Fan et al. (1996), a bootstrap method of Hall et al. (1999) for bandwidth selection in the estimation of conditional…

非规则问题中的模型选择：数量性状基因座定位应用AI 解读

Two methods of model selection are discussed for changepoint-like problems, especially those arising in genetic linkage analysis. The first is a method that selects the model with the smallest p-value, while the second is a modification of the Bayes information criterion. The methods are compared theoretically and on examples from the literature. For these examples, they are roughly comparable although the p-value-based method is somewhat more liberal in selecting a…

We consider estimation of the received treatment effect on a dichotomous outcome in randomised trials with non-compliance. We explore inference about the parameters of the structural mean models of Robins (1994, 1997) and Robins et al. (1999). We show that, in contrast to the additive and multiplicative structural mean models for continuous and count outcomes, unbiased estimating functions for a nonzero (structural) treatment effect parameter do not exist in the presence of…

基于非光滑估计函数的统计推断AI 解读

When the estimating function for a vector of parameters is not smooth, it is often rather difficult, if not impossible, to obtain a consistent estimator by solving the corresponding estimating equation using standard numerical techniques. In this paper, we propose a simple inference procedure via the importance sampling technique, which provides a consistent root of the estimating equation and also an approximation to its distribution without solving any equations or…

多元失效时间数据的加性风险模型AI 解读

Marginal additive hazards models are considered for multivariate survival data in which individuals may experience events of several types and there may also be correlation between individuals. Estimators are proposed for the parameters of such models and for the baseline hazard functions. The estimators of the regression coeffcients are shown asymptotically to follow a multivariate normal distribution with a sandwich-type covariance matrix that can be consistently…

组序贯临床试验设计中的功效、样本量与适应性AI 解读

A class of flexible and asymptotically efficient group sequential designs is developed herein for one-sided and two-sided tests of the parameter of an exponential family. Efficiency is measured in terms of the expected sample size and power function, under prespecified constraints on the maximum sample size and Type I error probability. It is shown how these designs achieve asymptotic efficiency by adapting to the information about the unknown parameter during the course of…

一般可因子分解模型的高效递推AI 解读

Let n S‐valued categorical variables be jointly distributed according to a distribution known only up to an unknown normalising constant. For an unnormalised joint likelihood expressible as a product of factors, we give an algebraic recursion which can be used for computing the normalising constant and other summations. A saving in computation is achieved when each factor contains a lagged subset of the components combining in the joint distribution, with maximum…

关于由边际密度构造伪似然的说明AI 解读

For likelihood‐based inference involving distributions in which high‐dimensional dependencies are present it may be useful to use approximate likelihoods based, for example, on the univariate or bivariate marginal distributions. The asymptotic properties of formal maximum likelihood estimators in such cases are outlined. In particular, applications in which only a single q×1 vector of observations is observed are examined. Conditions under which consistent estimators of…

时间过程回归AI 解读

We consider regression for response and covariates which are temporal processes observed over intervals. A functional generalised linear model is proposed which includes extensions of standard models in multi‐state survival analysis. Simple nonparametric estimators of time‐indexed parameters are developed using ‘working independence’ estimating equations and are shown to be uniformly consistent and to converge weakly to Gaussian processes. The procedure does not require…

半变系数模型的有效估计AI 解读

Motivated by two practical problems, we propose a new procedure for estimating a semivarying‐coefficient model. Asymptotic properties are established which show that the bias of the parameter estimator is of order h3 when a symmetric kernel is used, where h is the bandwidth, and the variance is of order n−1 and efficient in the semiparametric sense. Undersmoothing is unnecessary for the root‐n consistency of the estimators. Therefore, commonly used bandwidth selection…

具有非平稳相关误差的多元回归模型AI 解读

We consider the estimation of parameters of a multiple regression model with nonstationary errors. We assume the nonstationary errors satisfy a time‐dependent autoregressive process and describe a method for estimating the parameters of the regressors and the time‐dependent autoregressive parameters. The parameters are rescaled as in nonparametric regression to obtain the asymptotic sampling properties of the estimators. The method is illustrated with an example taken from…

利用 Cholesky 分解进行多元谱分析AI 解读

We propose to smooth the Cholesky decomposition of a raw estimate of a multivariate spectrum, allowing different degrees of smoothness for different elements. The final spectral estimate is reconstructed from the smoothed Cholesky elements, and is consistent and positive definite. More importantly, the Cholesky decomposition matrix of the spectrum can be used as a transfer function in generating time series whose spectrum is identical to the given spectrum at the Fourier…

季节性持久过程周期图估计量的大样本性质AI 解读

Seasonally persistent models were first introduced by Anděl (1986) and Gray et al. (1989) to extend autoregressive moving‐average and fractionally differenced models and to encompass long‐memory quasi‐periodic behaviour. These models are, for certain ranges of parameters, stationary, and we prove here that the behaviour of the periodogram and other tapered estimators cannot be simply extended from the work of Künsch (1986) and Hurvich & Beltrao (1993) on long memory induced…

高斯浓度图的模型选择AI 解读

A multivariate Gaussian graphical Markov model for an undirected graph G, also called a covariance selection model or concentration graph model, is defined in terms of the Markov properties, i.e. conditional independences associated with G, which in turn are equivalent to specified zeros among the set of pairwise partial correlation coefficients. By means of Fisher's z‐transformation and Šidák's correlation inequality, conservative simultaneous confidence intervals for the…

基于局部影响的模型诊断程序AI 解读

Cook's (1986) normal curvature measure is useful for sensitivity analysis of model assumptions in statistical models. However, there is no rigorous approach based on the normal curvature for addressing two fundamental issues: to assess the extent of discrepancy between an assumed model and the underlying model from which the data are generated, and to identify suspicious data points for which the discrepancy is most evident. Our purpose is to establish a theoretically sound…

失效原因被遮蔽的竞争风险模型：基于 EM 算法的推断AI 解读

In this paper we propose inference methods based on the EM algorithm for estimating the parameters of a weakly parameterised competing risks model with masked causes of failure and second‐stage data. With a carefully chosen definition of complete data, the maximum likelihood estimation of the cause‐specific hazard functions and of the masking probabilities is performed via an EM algorithm. Both the E‐ and M‐steps can be solved in closed form under the full model and under…

病例对照抽样下的现状数据AI 解读

In this paper, we show that the distribution function of survival times is identified, up to a one‐parameter family of distribution functions, based on information from case‐control current status data. With supplementary information on the population frequency of cases relative to controls, a simple weighted version of the nonparametric maximum likelihood estimator for prospective current status data provides a natural estimator for case‐control samples. Following the…

多元二元数据交替逻辑回归的置换不变性AI 解读

A practically important but not so obvious result is that alternating logistic regression is invariant to permutations of the response variables within clusters. In this note, we give a short proof of the invariance result using a pairwise likelihood argument. The same proof can be used to establish invariance for a more general class of estimating equations based on conditional residuals. As it stands, the invariance theory is incomplete because existing standard error…