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使用数据依赖先验进行混合模型渐近推断AI 解读

Summary For certain mixture models, improper priors are undesirable because they yield improper posteriors. However, proper priors may be undesirable because they require subjective input. We propose the use of specially chosen data-dependent priors. We show that, in some cases, data-dependent priors are the only priors that produce intervals with second-order correct frequentist coverage. The resulting posterior also has another interpretation: it is the product of a fixed…

用于自助法迭代的加权自助法AI 解读

Summary The operation of resampling from a bootstrap resample, encountered in applications of the double bootstrap, maybe viewed as resampling directly from the sample but using probability weights that are proportional to the numbers of times that sample values appear in the resample. This suggests an approximate approach to double-bootstrap Monte Carlo simulation, where weighted bootstrap methods are used to circumvent much of the labour involved in compounded Monte Carlo…

L 估计量的精确 Bootstrap 均值与方差AI 解读

Summary Exact analytic expressions for the bootstrap mean and variance of any L-estimator are obtained, thus eliminating the error due to bootstrap resampling. The expressions follow from the direct calculation of the bootstrap mean vector and covariance matrix of the whole set of order statistics. By using these expressions, recommendations can be made about the appropriateness of bootstrap estimation under given conditions.

通过可逆跳跃 MCMC 进行隐马尔可夫模型的贝叶斯推断AI 解读

Summary Hidden Markov models form an extension of mixture models which provides a flexible class of models exhibiting dependence and a possibly large degree of variability. We show how reversible jump Markov chain Monte Carlo techniques can be used to estimate the parameters as well as the number of components of a hidden Markov model in a Bayesian framework. We employ a mixture of zero-mean normal distributions as our main example and apply this model to three sets of data…

最大熵抽样与最优贝叶斯实验设计AI 解读

Summary When Shannon entropy is used as a criterion in the optimal design of experiments, advantage can be taken of the classical identity representing the joint entropy of parameters and observations as the sum of the marginal entropy of the observations and the preposterior conditional entropy of the parameters. Following previous work in which this idea was used in spatial sampling, the method is applied to standard parameterized Bayesian optimal experimental design.…

随机股息与波动率下的美式期权：非参数研究AI 解读

In this paper, we consider American option contracts when the underlying asset has stochastic dividends and stochastic volatility. We provide a full discussion of the theoretical foundations of American option valuation and exercise boundaries. We show how they depend on the various sources of uncertainty which drive dividend rates and volatility, and derive equilibrium asset prices, derivative prices and optimal exercise boundaries in a general equilibrium model. The…

选择 Bootstrap 重复次数的三步法AI 解读

This paper considers the problem of choosing the number of bootstrap repetitions B for bootstrap standard errors, confidence intervals, confidence regions, hypothesis tests, p-values, and bias correction. For each of these problems, the paper provides a three-step method for choosing B to achieve a desired level of accuracy. Accuracy is measured by the percentage deviation of the bootstrap standard error estimate, confidence interval length, test's critical value, test's…

受限协整向量的估计AI 解读

This article suggests the use of simple minimum-distance methods to estimate restricted cointegrating vectors. The method directly employs minimum-distance methods on unrestricted cointegrating matrices estimated in the usual way to estimate restricted parameters that are linearly or nonlinearly related to the unrestricted cointegrating vector coefficients. The limiting distribution of the estimates and the usual test for the restrictions are derived. A Monte Carlo…

自回归模型中基于残差的正态性检验：渐近理论与模拟证据AI 解读

Existing results for the asymptotic validity of the Jarque-Bera test in vector autoregressive (VAR) models assume stationarity. In applied work, however, researchers often work with possibly integrated and cointegrated process. We prove the asymptotic validity of the Jarque-Bera test for vector error-correction (VEC) models and for unrestricted VAR models with possibly integrated or cointegrated variables. We also propose the use of bootstrap critical values in stationary…

基于典型相关的协整秩强一致判定AI 解读

This article is concerned with the statistical analysis of nonstationary, cointegrated time series. The estimation of the cointegrating structure of such time series is considered, and the problem of identifying the cointegrating rank is addressed. A methodology is presented that leads to strongly consistent estimates of this quantity. The identification is based on a canonical correlation analysis of the original variables and presents an alternative approach to those…

尾部行为可能误设时风险管理视角下的最优估计AI 解读

Many financial time series show leptokurtic behavior--that is, fat tails. Such tail behavior is important for risk management. In this article I focus on the calculation of Value-at-Risk (VaR) as a downside-risk measure for optimal asset portfolios. Using a framework centered on the Student-t distribution, I explicitly allow for a discrepancy between the fat-tailedness of the true distribution of asset returns and that of the distribution used by the investment manager. As a…

股票收益与股息收益率再考察：旧问题的新视角AI 解读

The problem of whether stock returns can he predicted from dividend yields is discussed. I apply a new statistical method for finding reliable confidence intervals for regression parameters in the context of dependent and possibly heteroscedastic data, called subsampling. The method works under very weak conditions and avoids the pitfalls of having to choose a structural model to fit to observed data. Appropriate simulation studies suggest that it has better small-sample…

基于秩与符号的替代方差比检验AI 解读

This article proposes using variance-ratio tests based on the ranks and signs of a time series to test the null that the series is a martingale difference sequence. Unlike conventional variance-ratio tests, these tests can be exact. In Monte Carlo simulations, I find that they can also be more powerful than conventional variance-ratio tests. I apply the proposed tests to five exchange-rate series and find that they are capable of detecting violations of the martingale…

生产率的渐近完全收敛与相对收敛AI 解读

In this paper we examine the extent to which countries are converging in per capita productivity levels. We propose to use cluster analysis in order to allow for the endogenous selection of converging countries. We formally define convergence in a time series analytical context, derive the necessary and sufficient conditions for convergence, and introduce a cluster analytical procedure that distinguishes several convergence clubs by testing for these conditions using a…

与最优者的多重比较及其经济应用AI 解读

In this paper we discuss a statistical method called multiple comparisons with the best, or MCB. This paper is meant to introduce MCB to economists. We discuss possible uses of MCB in economics. The application that we treat in most detail is the construction of confidence intervals for inefficiency measures from stochastic frontier models with panel data. We also consider an application to the analysis of labour market wage gaps. Copyright � 2000 John Wiley & Sons, Ltd.

非正则情形的概率匹配先验AI 解读

We study probability matching priors in non-regular cases. Both one-parameter and multi-parameter cases are considered. The resulting priors are shown to satisfy certain differential equations. Several examples are discussed. It is observed that the reference prior in the sense of Bernardo is in many cases also probability matching. As a necessary tool for finding such priors, asymptotic expansion of posterior distributions for multi-parameter non-regular cases is also…

一般条件下的两样本分位数检验AI 解读

A simple, nonparametric two-sample test for equality of a given collection of quantiles is developed which can be applied to a variety of empirical distribution functions, including the Kaplan-Meier estimator, a self-consistent estimator for doubly-censored data and an estimator for repeated measures data. The null hypothesis tested is that the quantiles are equal but other aspects of the distributions may differ between the two samples. This procedure can also be applied to…

基于预测似然或自助法的预测区间AI 解读

We argue that prediction intervals based on predictive likelihood do not correct for curvature with respect to the parameter value when they implicitly approximate an unknown probability density. Partly as a result of this difficulty, the order of coverage error associated with predictive intervals and predictive limits is equal to only the inverse of sample size. In this respect those methods do not improve on the simpler, 'naive' or 'estimative' approach. Moreover, in…

降低半参数模型对滋扰参数的敏感性：拟得分方法AI 解读

This paper proposes a semiparametric extension of the projected score method of Waterman & Lindsay (1996) for the elimination of nuisance parameters. The procedure addresses cases where only the mean and the variance of the response variable are specified and where the mean function involves both parameters of interest and nuisance parameters. Important applications of the semiparametric model include quasilikelihood models for matched designs and for measurement error…

二元回归中响应误分类导致的偏差与效率损失AI 解读

Methods that ignore errors in binary responses yield biased estimators of the associations of covariates with response. This paper derives general expressions for the magnitude of the bias due to errors in the response and shows that, unless both the sensitivity and specificity are very high, ignoring errors in the responses will yield highly biased covariate effect estimators. When the true, error-free response follows a generalised linear model and misclassification…

扩展的部分线性单指标模型AI 解读

Aiming to explore the relation between the response y and the stochastic explanatory vector variable X beyond the linear approximation, we consider the single-index model, which is a well-known approach in multidimensional cases. Specifically, we extend the partially linear single-index model to take the form y=βT0X + φ(θT0X) + ε, where ε is a random variable with Εε=0 and var(ε)=σ2, unknown, β0 and θ0 are unknown parametric vectors and φ(.) is an unknown real function. The…

论高效概率预测系统AI 解读

We study the asymptotic behaviour of probability forecasting systems, and discuss their usefulness as inferential tools for statistical problems such as model verification and selection. Our theoretical setting is the prequential, or predictive sequential, framework proposed by Dawid (1984). We study especially the notion of prequential efficiency of a forecasting system and present some new results. We focus on plug-in, or estimative, forecasting systems, where the forecast…

多重插补中的小样本自由度调整AI 解读

An appealing feature of multiple imputation is the simplicity of the rules for combining the multiple complete-data inferences into a final inference, the repeated-imputation inference (Rubin, 1987). This inference is based on a t distribution and is derived from a Bayesian paradigm under the assumption that the complete-data degrees of freedom, νcom, are infinite, but the number of imputations, m, is finite. When νcom is small and there is only a modest proportion of…

回顾性抽样问题的高阶精确方法AI 解读

In this paper we discuss the relationship between prospective and retrospective sampling problems. Estimates of the parameter of interest may be obtained by solving suitable estimating equations under both sampling schemes. Most common examples of such estimates include the maximum likelihood estimates. Some classical results and more recent development of the first-order asymptotic relationship between the estimators are reviewed. High-order expansions are given for the…