论文检索

含噪信号的可变潜伏期：脑电位数据中的估计与检验AI 解读

The electric response of the brain related to some event, i.e. stimulus, is usually estimated by repeated stimulation and subsequent averaging of the activity recorded time-locked to the stimulus. The present paper deals with the model that the single responses may have varying latency, i.e. arrival time, after stimulus onset. For estimating the single latencies, a maximum likelihood approach employing iterative Fisher-scoring is developed. Further a statistic for testing on…

随机截断数据的影响曲线AI 解读

Under a random truncation model, observations (X, Y) are lost if X < Y. Properties of the maximum likelihood estimators for the distributions F, G of X and Y and the truncation proportion a have been treated by various authors, for example, Lynden-Bell (1971), and more recently Woodroofe (1985). Asymptotic variances of various estimates, including the mean, the median, the L- and the M-estimates and â, if they can be expressed as functionals of ^ and Ĝ, are obtained through…

因子分析及相关模型中统计推断的稳健性AI 解读

A class of latent variable models which includes the unrestricted factor analysis model is considered. It is shown that minimum discrepancy test statistics and estimators derived under normality assumptions retain their asymptotic properties when the common factors are not normally distributed but the unique factors do have a multivariate normal distribution. The minimum discrepancy test statistics and estimators considered include the usual likelihood ratio test statistic…

N 个观测最大值的分位数估计AI 解读

Given independent and identically distributed random variables from an unknown distribution F, we want to estimate quantiles of FN. Using asymptotic extreme-value theory, two parametric approximations to FN are considered and approximate maximum likelihood estimates are obtained. Conditions for consistency and asymptotic normality of these estimates are given, and properties of the estimates are obtained through a small simulation study.

具有嵌套层级额外泊松变异的广义线性模型AI 解读

We consider a scaled Poisson generalized linear model with random multiplicative errors associated with each stratum of a nested block structure. The normal equations are obtained. The quasi-likelihood is shown to be the product of a sequence of negative binomial quasi-likelihoods using weighted totals and correcting for margins. This is achieved by extending the definition of the quasi-likelihood which now includes a vector of weights. The usual asymptotic results still…

拟似然估计的效率AI 解读

A quasi-likelihood method has been proposed by Wedderburn (1974) for the estimation of parameters in regression models when there is some assumed relationship between the mean and variance of each observation but not necessarily a fully specified likelihood. If the underlying distribution comes from a natural exponential family the quasi-likelihood estimates maximize the likelihood and so have full asymptotic efficiency; under more general distributions there is some loss of…

一种扩展拟似然函数AI 解读

Wedderburn's original definition of quasi-likelihood for generalized linear models is extended to allow the comparison of variance functions as well as those of linear predictors and link functions. The relationship between generalized linear models and the use of transformations of the response variable is explored, and the ideas are illustrated by three examples.

共同主成分模型的两种推广AI 解读

Under the common principal component model the covariance matrices Ψi, of k populations are assumed to have identical eigenvectors, that is, the same orthogonal matrix diagonalizes all Ψi, simultaneously. This paper modifies the common principal component model by assuming that only q out of p eigenvectors are common to all Ψi, while the remaining p–q elgenvectors are specific in each group. This is called a partial common principal component model. A related modification…

同期相关的双变量时间序列AI 解读

Bivariate autoregressive-moving average time series with diagonal parameter matrices for the autoregressive and moving average components exhibit only contemporaneous or instantaneous correlation. In practice, different lengths of each series may be available. An efficient maximum likelihood algorithm for parameter estimation is derived. The statistical efficiency of this new procedure is compared with that of the standard multivariate and univariate procedures which utilize…

非连续观测时间序列参数估计量的渐近分布AI 解读

The asymptotic normal distributions of two estimators, the maximum likelihood estimator and an alternative weighted least-squares estimator proposed by Wincek & Reinsel (1986) for parameter estimation of autoregressive-moving average models with nonconsecutively observed or missing data are derived for the stationary first-order autoregressive model, and also for the moving average model under periodic A-B sampling. Numerical comparisons of the explicit asymptotic variances…

Bootstrap 与置信区间AI 解读

We derive an explicit formula for the first term in an unconditional Edgeworth-type expansion of coverage probability for the nonparametric bootstrap technique applied to a very broad class of "Studentized" statistics. The class includes sample mean, $k$-sample mean, sample correlation coefficient, maximum likelihood estimators expressible as functions of vector means, etc. We suggest that the bootstrap is really an empiric one-term Edgeworth inversion, with the bootstrap…

广义线性模型中的残差AI 解读

Generalized linear models are regression-type models for data not normally distributed, appropriately fitted by maximum likelihood rather than least squares. Typical examples are models for binomial or Poisson data, with a linear regression model for a given, ordinarily nonlinear, function of the expected values of the observations. Use of such models has become very common in recent years, and there is a clear need to study the issue of appropriate residuals to be used for…

基于提名抽样的分布函数估计AI 解读

Nomination sampling is a sampling process in which every observation is the maximum of a random sample from some population. Assuming that all samples are taken from a single underlying distribution F, data may be viewed as consisting of pairs (Xi , Ki ), where Ki is the size of the ith sample and, given Ki = ki, Xi is distributed according to F ki. Willemain (1980), who discussed nomination sampling in the context of health care delivery, proposed an estimator for the…

删失观测、重复测量与混合效应模型：正态误差下的 EM 方法AI 解读

Maximum likelihood estimation of a vector regression parameter and variance com ponents is considered for the mixed effects model when observations are right censored. A general scheme of estimation is given using the EM algorithm and detailed results found for the model with between and within block variation. This model is applied to the logarithms of survival times from a repeated measures design.

非线性回归中的偏差AI 解读

We investigate the biases of the residuals and maximum likelihood parameter estimates from normal nonlinear regression models. Emphasis is placed on a class of partially nonlinear models, on the role of individual cases in determining bias, on how bias affects standard diagnostic methods, and on the relationship between bias and curvature.

序贯检验结束后最大似然估计的偏差AI 解读

The bias of maximum likelihood estimates calculated at the end of a sequential procedure is investigated. For the two sequential designs considered in detail, the sequential probability ratio test and the triangular test, this bias is appreciable. A method of calculating an adjusted estimate with reduced bias is described, and an approximation to the standard error of the new estimate is provided. Examples of the implementation of the method are given, and its advantages and…

基于正态但相依观测的最大似然估计量的渐近正态性AI 解读

In this article we aim to establish intuitively appealing and verifiable conditions for the first-order efficiency and asymptotic normality of ML estimators in a multi-parameter framework, assuming joint normality but neither the independence nor the identical distribution of the observations. We present five theorems (and a large number of lemmas and propositions), each being a special case of its predecessor.

混合存量与流量数据下含外生变量的高阶连续时间动态模型估计AI 解读

This article extends recent work on the Gaussian or quasi-maximum likelihood estimation of the parameters of a closed higher-order continuous time dynamic model by introducing exogenous variables into the model The method presented yields exact maximum likelihood estimates when the innovations are Gaussian and the exogenous variables are polynomials in time of degree not exceeding two, and it can be expected to yield very good estimates under more general conditions. It is…

Tobit 模型的对称修剪最小二乘估计AI 解读

This papjer proposes alternatives to maximum likelihood estimation of the censored and truncated regression models (known to economists as "Tobit" models) .The proposed estimators are based on symmetric censoring or truncation of the upper tail of the distribution of the dependent variable.Unlike methods based on the assumption of identically distributed Gaussian errors/ the estimators are consistent and asymptotically normal for a wide class of error distributions and for…

分组与未分组数据回归模型中最大似然估计的存在性AI 解读

SUMMARY In general, concavity of the log likelihood alone does not imply that the MLE exists always. For a class of linear regression models for grouped and ungrouped data, a necessary and sufficient condition is obtained for the existence of the maximum likelihood estimator. This condition has an intuitively simple interpretation. Further, it turns out that there are similar necessary and sufficient conditions for the existence of maximum likelihood estimates for a number…

线性过程误差回归中 GLSE 与 MLE 的二阶风险结构AI 解读

In a regression model with an error that is a general linear process, the second-order expansion of the risk matrix of GLSE or MLE is obtained. a set of sufficient conditions for the effect of estimating the structural parameter of the linear process to vanish in the above expasion is obtained. The relation of the covariance matrix of SLSE with those of GLSE and MLE up to $O(T^-2)$ is elucidated.

超临界 Galton–Watson 过程子代均值的渐近条件推断AI 解读

Consider a supercritical Galton-Watson process $(Z_n)$ with offspring distribution a member of the power series family, and having unknown mean $\theta$. The conditional asymptotic normality of the suitably normalized maximum likelihood estimator of $\theta$ given the conditional information is established. The conditional information here is proportional to the total number of ancestors $V_n$, and it is also seen that this statistic is asymptotically ancillary for $\theta$ i…

似然与观测几何AI 解读

In the differential geometric approach to parametric statistics, developed by Chentsov, Efron, Amari, and others, the parameter space is set up as a differentiable manifold with expected information as metric tensor and with a family of affine connections, the a-connections, determined from the expected information and the skewness tensor of the score vector. The usefulness of this approach is particularly notable in connection with Edgeworth expansions of estimators.…

抽样设计对主成分分析的影响AI 解读

Most sample surveys are multivariate and many lend themselves to multivariate methods of analysis. The most usual mode of such analysis is a standard statistical package, such as BMDP or SPSS, in which the multivariate analyses are based on the underlying assumption that the data are generated as independent observations from a common probability distribution. This assumption ignores the sample selection procedure involved in the survey, which leads to the following basic…