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汇率的长记忆AI 解读

Using the Geweke-Porter-Hudak test, the author finds evidence of long memory in exchange-rate data. This implies t hat the empirical evidence of unit roots in exchange rates may not be robust to long-memory alternatives. Fractionally integrated autoregressive moving average models are estimated by both the time-domain exact maximum likelihood method and the frequency-domain approximate maximum likelihood method. Impulse-response functions and forecasts based.on these…

含测量误差的 probit 回归似然分析AI 解读

Likelihood analysis is proposed for a probit regression model when one of the explanatory variables is measured with error and replicate measurements of that variable are available on some of the subjects. The distribution of the measurement error and of the unknown explanatory variable, conditional on the known variables, are both taken to be normal. The maximum likelihood estimates can be computed exactly with the EM algorithm. Likelihood ratio tests and confidence…

拟似然方法中的偏差函数AI 解读

We introduce a deviance function that can be used in conjunction with the quasi-likelihood method. The need for such functions arises when the quasi-log likelihood function is not uniquely defined. The deviance is obtained by projecting a pair of centred likelihood ratios onto the direct sum of two Hilbert spaces spanned by the observations. Locally at the null and the alternative hypotheses, the deviance function is equivalent to the quasi-log likelihood ratio provided that…

有偏处理分配下的最优估计AI 解读

This paper provides a semi-parametric solution to a problem proposed by Robbins & Zhang (1991). The solution is obtained utilizing the theory of optimum estimating functions (Godambe & Thompson, 1989). Our solution coincides with maximum likelihood estimation for the parametric model suggested by Robbins & Zhang (1991). Even for alternative models investigated in this paper, the efficiency of our estimation appears very close to that of maximum likelihood estimation.

受约束的拟似然估计AI 解读

For maximum likelihood or least squares parameter estimation subject to a constrained parameter, the standard approach is to use the method of Lagrange multipliers. In this paper it is shown that the same formal procedure applies very generally for constrained quasi-likelihood estimation even though there is ordinarily no objective function to maximize or minimize. This allows for optimal estimation in a wide range of problems where maximum likelihood cannot be used, such as…

研究剖面似然调整的符号算法AI 解读

A symbolic algorithm for the derivation of the asymptotic expansion of the maximum likelihood estimate was first introduced by Andrews & Stafford (1993). This algorithm is quite general and can be modified to give asymptotic expansions for the maximum likelihood estimate based on either the conditional, modified or adjusted profile likelihoods. Expansions are obtained quickly with no chance for human clerical error. As a result, these three adjustments can be easily studied…

共同对数优势比的偏差校正最大似然估计AI 解读

A bias-correction factor for the maximum likelihood estimator of the log common odds ratio for sparse data is derived, which is applicable when the design is balanced and/or when the number of strata is large. The corrected maximum likelihood estimator is practically unbiased and its mean squared error is smaller than that of the uncorrected maximum likelihood estimator. The correction factor for the maximum likelihood estimator approaches one as strata sizes increase.…

含个体特定效应的重复有序类别响应比例优势模型AI 解读

Suppose subjects make repeated responses on the same ordered categorical scale. We propose a generalization of the Rasch model that expresses the cumulative logit of the response distribution using subject parameters and a proportional odds structure for item effects. Parameters in the model describe subject-specific, rather than population averaged, effects. Consistent estimation of the effects requires eliminating the subject parameters. We accomplish this by simultaneous…

破纪录数据问题的参数似然推断AI 解读

In this paper we consider the analysis of record breaking data sets, where only observations that exceed, or only those that fall below, the current extreme value are recorded. Example application areas include industrial stress testing, meteorological analysis, sporting and athletic events, and oil and mining surveys. A closely related area is that of threshold modelling, where the observations are those that cross a certain threshold value. The inherent missing data…

具有光滑随机效应密度的非线性混合效应模型AI 解读

The fixed parameters of the nonlinear mixed effects model and the density of the random effects are estimated jointly by maximum likelihood. The density of the random effects is assumed to be smooth but is otherwise unrestricted. The method uses a series expansion that follows from the smoothness assumption to represent the density and quadrature to compute the likelihood. Standard algorithms are used for optimization. Empirical Bayes estimates of random coefficients are…

多步预测中最大似然估计的稳健性：指数平滑情形AI 解读

We extend the argument initiated by Cox (1961) that the exponential smoothing formula can be made more robust for multi-step forecasts if the smoothing parameter is adjusted as a function of the forecast horizon l. The consistency property of the estimator which minimizes the sum of squares of the sample l-step ahead forecast errors makes the robustness result useful in practice. We also generalize the consistency result to some other parsimonious nonstationary models which…

分类协变量观测不完整时的逻辑回归：三种方法比较AI 解读

A logistic regression analysis based on the complete cases neglects the information due to subjects with missing values in at least one but not in all covariates. Three different approaches allowing the use of this information are compared: maximum likelihood estimation, pseudo maximum likelihood estimation, and probability imputation. The first two yield consistent estimates of the regression coefficients and asymptotic normality allows the construction of asymptotically…

通过 ECM 算法进行最大似然估计：一般框架AI 解读

Two major reasons for the popularity of the EM algorithm are that its maximum step involves only complete-data maximum likelihood estimation, which is often computationally simple, and that its convergence is stable, with each iteration increasing the likelihood. When the associated complete-data maximum likelihood estimation itself is complicated, EM is less attractive because the M-step is computationally unattractive. In many cases, however, complete-data maximum…

一般乘法截距风险模型下病例对照数据的前瞻式分析AI 解读

We show that, under a general multiplicative-intercept model for risk, case-control data can be analyzed by maximum likelihood as if they had arisen prospectively, up to an unidentifiable multiplicative constant which depends on the relative sampling fractions. This generalizes earlier work of Anderson (1972, 1979), by showing that not only the point estimates but also the standard errors based on the observed information matrix are correct when the prospective likelihood is…

用于多项分布额外变异建模的有限混合分布AI 解读

We propose a new distribution to model categorical data exhibiting overdispersion when the overdispersion is believed to be caused by clumped sampling. The proposed distribution is a finite mixture of multinomial random variables. The finite mixture representation facilitates computation of the maximum likelihood estimator. For large cluster sizes, we derive an approximation for the Fisher information matrix of the model, and an explicit expression for the joint asymptotic…

利用先验信息的非参数样条回归AI 解读

SUMMARY By using prior information about the regression curve we propose new nonparametric regression estimates. We incorporate two types of information. First, we suppose that the regression curve is similar in shape to a family of parametric curves characterized as the solution to a linear differential equation. The regression curve is estimated by penalized least squares with the differential operator defining the smoothness penalty. We discuss in particular growth and…

由置信区间进行贝叶斯与似然计算AI 解读

Recently there has been considerable progress on setting good approximate confidence intervals for a single parameter θ in a multi-parameter family. Here we use these frequentist results as a convenient device for making Bayes, empirical Bayes and likelihood inferences about θ. A simple formula is given that produces an approximate likelihood function Lx†(θ) for θ, with all nuisance parameters eliminated, based on any system of approximate confidence intervals. The…

最大似然估计的偏差缩减AI 解读

It is shown how, in regular parametric problems, the first-order term is removed from the asymptotic bias of maximum likelihood estimates by a suitable modification of the score function. In exponential families with canonical parameterization the effect is to penalize the likelihood by the Jeffreys invariant prior. In binomial logistic models, Poisson log linear models and certain other generalized linear models, the Jeffreys prior penalty function can be imposed in…

纵向二元响应的似然分析方法AI 解读

In this paper, we discuss a likelihood-based method for analysing correlated binary responses based on a multivariate model. It is related to the pseudo-maximum likelihood approach suggested recently by Zhao & Prentice (1990). Their parameterization results in a simple pairwise model, in which the association between responses is modelled in terms of correlations, while the present paper uses conditional log odds-ratios. With this approach, higher-order associations can be…

通过条件化总渔获量估计渔具的体长选择性AI 解读

A conditional maximum likelihood model is used to estimate the size-selectivity of trawls, gillnets, and hooks when the data are obtained by simultaneous fishing with meshes or hooks of different size and/or shape. Size-selectivity is expressed here by the selection curve, r(l), the probability that a fish of length l, if contacting the gear, will be retained (caught). In many selectivity studies r(l) is fitted either by eye, by heuristic means, or by improper application of…

自变量缺失的回归分析：综述AI 解读

The literature of regression analysis with missing values of the independent variables is reviewed. Six classes of procedures are distinguished: complete case analysis, available case methods, least squares on imputed data, maximum likelihood, Bayesian methods, and multiple imputation. Methods are compared and illustrated when missing data are confined to one independent variable, and extensions to more general patterns are indicated. Attention is paid to the performance of…

生存与计划处死实验中约束极大似然估计的显式解AI 解读

Regulatory agencies routinely base conclusions regarding carcinogenicity of compounds tested in long-term animal studies on tests which are known to be biased under conditions of treatment lethality and tumour lethality. The recognition of these biases has led to a variety of proposed approaches which rely on survival and sacrifice data. Williams & Portier (1992) derived analytic expressions for maximum likelihood estimators of the tumour incidence rate and discrete death…

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似然、拟似然与伪似然的若干比较AI 解读

SUMMARY There is considerable interest in the fitting of models jointly to the mean and dispersion of a response. For the mean parameter, the Wedderburn estimating equations are widely accepted. However, there is some controversy about estimating the dispersion parameters. Finite sampling properties of several dispersion estimators are investigated for three models by simulation. We compare the maximum extended quasi-likelihood estimator, the maximum pseudolikelihood…