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状态空间模型中最大似然估计量的渐近正态性AI 解读

State space models is a very general class of time series models capable of modelling dependent observations in a natural and interpretable way. Inference in such models has been studied by Bickel, Ritov and Rydén, who consider hidden Markov models, which are special kinds of state space models, and prove that the maximum likelihood estimator is asymptotically normal under mild regularity conditions. In this paper we generalize the results of Bickel, Ritov and Rydén to state…

带宽选择：经典方法还是插件法？AI 解读

Bandwidth selection for procedures such as kernel density estimation and local regression have been widely studied over the past decade. Substantial “evidence” has been collected to establish superior performance of modern plug-in methods in comparison to methods such as cross validation; this has ranged from detailed analysis of rates of convergence, to simulations, to superior performance on real datasets. In this work we take a detailed look at some of this evidence,…

可变长度马尔可夫链AI 解读

We study estimation in the class of stationary variable length Markov chains (VLMC) on a finite space. The processes in this class are still Markovian of high order, but with memory of variable length yielding a much bigger and structurally richer class of models than ordinary high-order Markov chains. From an algorithmic view, the VLMC model class has attracted interest in information theory and machine learning, but statistical properties have not yet been explored.…

We present an econometrically tractable life cycle labor supply model for panel data including intertemporally progressive taxes on uncertai wage and nonwge incomes. Our two‐stage fixedeffects generalized method‐of‐moments approach first extimates intretemporal and then intertemporal preferences. Specification testing domonstrates the value of incorporating joint progressive taxation of labor and nonlabor incomes, Results for prime‐age men emphasize the roles played by…

均值—方差有效投资组合权重估计的抽样误差AI 解读

This paper presents an exact finite‐sample statistical procedure for testing hypotheses about the weights of mean‐variance efficient portfolios. The estimation and inference procedures on efficient portfolio weights are performed in the same way as for the coefficients in an OLS regression. OLS t ‐ and F ‐statistics can be used for tests on efficient weights, and when returns are multivariate normal, these statistics have exact t and F distributions in a finite sample. Using…

误差修正机制的非对称生成器及其在银行抵押贷款利率动态中的应用AI 解读

Empirical evidence supports asymmetries in the adjustment of prices, interest rates, and other economic variables. The asymmetry hypothesis, however, is often procedurally difficult to set up and test. This article shows that a wide variety of such mechanisms can be nested within an asymmetry generator, which represents the interactions between the disequilibrium term of an error-correction mechanism and an ancillary driver process. The asymmetry hypothesis can then be…

偏好异质性与需求系统的秩AI 解读

This article examines the effect of preference heterogeneity on nonparametric and parametric tests of the rank of demand systems. Using samples of households drawn from the U.K. Family Expenditure Survey, the authors find that preference heterogeneity increases the rank of demand systems. When the effects of household characteristics on demand are removed by semiparametric techniques, a rank-three demand system appears to be an adequate empirical specification for all…

滞后回归残差与序列相关检验AI 解读

A new family of statistics is proposed to test for the presence of serial correlation in linear regression models. The tests are based on partial sums of lagged cross-products of regression residuals that define a class of interesting Gaussian processes. These processes are characterized in terms of regressor functions, the serial-correlation structure, the distribution of the noise process, and the order of the lag of the cross-products of residuals. It is shown that these…

向量自回归过程中协整向量有效归一化的检验AI 解读

This article develops test procedures for checking the validity of general normalizing restrictions imposed on cointegrating vectors in vector autoregressive processes. Such test procedures are of importance because normalizing restrictions, possibly combined with overidentifying restrictions, are often necessary for a proper interpretation of cointegrating vectors. The null hypothesis of the authors' tests assumes that the employed normalization is valid or, alternatively,…

误差修正机制的非对称性生成器及银行按揭利率动态应用AI 解读

Empirical evidence supports asymmetries in the adjustment of prices, interest rates, and other economic variables. The asymmetry hypothesis, however, is often procedurally difficult to set up and test. This article shows that a wide variety of such mechanisms can be nested within an asymmetry generator, which represents the interactions between the disequilibrium term of an error-correction mechanism and an ancillary driver process. The asymmetry hypothesis can then be…

采用数据依赖模型选择规则的修正平稳性检验AI 解读

We describe some simple methods for improving the performance of stationarity tests (i.e., tests that have a stationary null and a unit-root alternative). Specifically, we increase the rate of convergence of the test under the unit-root alternative from O p(T) to O p (T 2), then suggest an optimal method of selecting the order of the autoregressive component in the fitted autoregressive integrated moving average model on which the test is based. Simulation evidence suggests…

存在异常值时的平滑转换非线性检验AI 解读

Regime-switching models, like the smooth transition autoregressive (STAR) model, are typically applied to time series of moderate length. Hence, the nonlinear features that these models intend to describe may be reflected in only a few observations. Conversely, neglected outliers in a linear time series of moderate length may incorrectly suggest STAR (or other) type(s of) nonlinearity. In this article, the authors propose outlier robust tests for STAR-type nonlinearity.…

自回归过程的柯西估计量及单位根检验与置信区间AI 解读

For autoregressive processes, we propose new estimators whose pivotal statistics have the standard normal limiting distribution for all ranges of the autoregressive parameters. The proposed estimators are approximately median unbiased. For seasonal time series, the new estimators give us unit root tests that have limiting normal distribution regardless of period of the seasonality. Using the estimators, confidence intervals of the autoregressive parameters are constructed. A…

样本量与预测期同步增长时近单位根 AR(1) 模型的预测误差AI 解读

We develop asymptotic approximations to the distribution of forecast errors from an estimated AR(1) model with no drift when the true process is nearly I (1) and both the forecast horizon and the sample size are allowed to increase at the same rate. We find that the forecast errors are the sums of two components that are asymptotically independent. The first is asymptotically normal whereas the second is asymptotically nonnormal. This throws doubt on the suitability of a…

单位根检验统计量的校正因子AI 解读

Despite the fact that it is not correct to speak of Bartlett corrections in the case of nonstationary time series, this paper shows that a Bartlett-type correction to the likelihood ratio test for a unit root can be an effective tool to control size distortions. Using well-known formulae, we obtain second-order (numerical) approximations to the moments and cumulants of the likelihood ratio, which makes it possible to calculate a Bartlett-type factor. It turns out that the…

近不稳定 AR(p) 过程的渐近推断AI 解读

In this paper nearly unstable AR( p ) processes (in other words, models with characteristic roots near the unit circle) are studied. Our main aim is to describe the asymptotic behavior of the least-squares estimators of the coefficients. A convergence result is presented for the general complex-valued case. The limit distribution is given by the help of some continuous time AR processes. We apply the results for real-valued nearly unstable AR( p ) models. In this case the…

创新项属于柯西分布正常吸引域时的零自相关检验AI 解读

We consider the asymptotic null distribution of the empirical autocorrelation function when the innovations of a moving average process belong to the normal domain of attraction of a Cauchy law. A series expansion for the density of the limiting null distribution is developed, and some critical values of the tests are computed numerically.

半参数选择偏差模型的最大似然估计及其艾滋病疫苗试验应用AI 解读

The following problem is treated: given s possibly selection biased samples from an unknown distribution function, and assuming that the sampling rule weight functions for each of the samples are mathematically specified up to a common unknown finite-dimensional parameter, how can we use the data to estimate the unknown parameters? We propose a simple maximum partial likelihood method for deriving the semiparametric maximum likelihood estimator. A discussion of assumptions…

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杂论：模型误设下病例对照分析与完整队列分析的比较AI 解读

We investigate the question of whether or not estimates of relative risk from matched case-control studies well represent the population from which they were drawn. We derive the formula for the asymptotic maximum partial likelihood estimators from nested case-control studies when the Cox proportional hazards model is misspecified and compare these to the corresponding full cohort values under various types of model misspecification, such as covariate omission, mismodelling…

存在干扰参数时的经验似然AI 解读

Empirical likelihood was introduced as a nonparametric analogue of ordinary parametric likelihood. It is well known that the empirical likelihood ratio statistic inherits a number of properties of the parametric likelihood ratio statistic, such as the aymptotic chi-squared distribution and Bartlett correctability. This raises the question of whether or not the same is true in the presence of nuisance parameters. Recent work by Qin & Lawless (1994) indicates that the…

利用单变量分布评估多变量非正态性AI 解读

This paper proposes diagnostics that can indicate regions where multivariate distributions are poorly behaved in the sense that they are far from normal. The measure of nonnormality developed by Slate (1994) for univariate distributions is extended to multivariate parametric models by application to univariate marginal and conditional distributions. The approach is illustrated for univariate conditional distributions using dynamic graphics in Xlisp-Stat (Tierney, 1990).…

评估状态空间过程中的观测预测影响AI 解读

An important inferential objective in state space modelling is to recover unobserved states using fixed-interval smoothing. Thus, the identification of cases which have a substantial influence on the smoothers is a relevant practical problem. To facilitate this identification, we propose a case-deletion diagnostic which can be easily computed using the outputs of the standard filtering and smoothing algorithms. Our diagnostic is defined as the Kullback-Leibler directed…

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