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VAR 维度对估计量偏误的影响AI 解读

Vector AutoRegressions (VARs) have now become the most popular tool of Time Series analysis amongst econometricians. Unfortunately, little is known about the analytic finite-sample properties of parameter estimators for such systems. The asymptotic analysis of VARs published to date does not address questions regarding the influence of the number and nature of the system's variates on parameter estimates. Clearly, both questions will have repercussions on the way VARs are…

ARCH 效应的新检验及其有限样本表现AI 解读

We propose a test for autoregressive conditional heteroscedasticity based on a weighted sum of the squared sample autocorrelations of squared residuals from a regression, typically with greater weight given to lower-order lags. The tests of Engle, Box and Pierce, and Ljung and Box are equivalent to the test with equal weighting. Our test does not require formulation of an alternative and permits choice of the lag number via data-driven methods. Simulation studies show that…

基于对称估计量的双重单位根半参数检验AI 解读

The authors develop new semiparametric tests for double unit roots under a weakly dependent error structure of Phillips for tests for a unit root. The tests are based on symmetric estimation of Sen and Dickey. Through Monte Carlo simulations, the new tests are compared with the tests of Haldrup and of Dickey and Pantula. Their tests have empirical sizes close to the nominal size even when the innovations follow a negatively autocorrelated moving average, for which the…

Jackknife 工具变量估计AI 解读

Two-stage-least-squares (2SLS) estimates are biased towards the probability limit of OLS estimates. This bias grows with the degree of over-identification and can generate highly misleading results. In this paper we propose two simple alternatives to 2SLS and limited-information-maximum-likelihood (LIML) estimators for models with more instruments than endogenous regressors. These estimators can be interpreted as instrumental variables procedures using an instrument that is…

突发政府干预下的单位根检验：巴西数据应用AI 解读

This paper considers econometric issues related to time-series data that have been subject to abrupt governmental interventions. The motivating example for this study is the Brazilian monthly inflation rate (1974:1-1993:6) which we use throughout for illustration. This series has been heavily influenced by the effect of so-called shock plans implemented by various governments starting in the mid-1980s. The plans act as 'inliers' in the sense that the series is temporarily…

短札：通过正态近似由条件信息计算信息矩阵AI 解读

This paper provides a method for computing the asymptotic covariance matrix from a likelihood function with known maximum likelihood estimate of the parameters. Philosophically, the basic idea is to assume that the likelihood function should be well approximated by a normal density when asymptotic results about the maximum likelihood estimate are applied for statistical inference. Technically, the method makes use of two facts: the information for a one-dimensional parameter…

参数化多重插补程序的大样本理论AI 解读

We consider the asymptotic behaviour of various parametric multiple imputation procedures which include but are not restricted to the ‘proper’ imputation procedures proposed by Rubin (1978). The asymptotic variance structure of the resulting estimators is provided. This result is used to compare the relative efficiencies of different imputation procedures. It also provides a basis to understand the behaviour of two Monte Carlo iterative estimators, stochastic EM (Celeux &…

证据不完美时的法医学身份识别AI 解读

We study the problem of forensic identification when the trace evidence from the scene of the crime is imperfect: for example, it might be measured with error, or be partially missing. A general framework for imperfect data is developed, and applied in particular to the following cases, singly and in combination: ‘measurement error’ in the recorded information at the scene of the crime; ‘binning’, i.e. discretisation of an originally continuous crime measurement; ‘paternity…

数据报告延迟下含协变量右删失生存分布的局部有效估计AI 解读

For many sources of survival data, there is a delay between the recording of vital status and its availability to the analyst, and the Kaplan-Meier estimator is typically inconsistent in these situations. In this paper we identify the optimal estimation problem. As a result of the curse of dimensionality, no globally efficient nonparametric estimator exists with a good practical performance at moderate sample sizes. Following the approach of Robins & Rotnitzky (1992), given…

通过估计函数推断点过程的均值与协方差AI 解读

Liang & Zeger (1986) introduced methodology for the analysis of longitudinal data that provides an alternative to likelihood-based inference. They considered modelling the marginal means of the response follow-up measures, and proposed the use of unbiased estimating functions to handle inference. Here we wish to do the same for point or jump processes. We consider parametric models for the marginal means, and possibly the covariance structures, of processes that allow…

生存时间与终点标记变量联合分布的非参数估计AI 解读

SUMMARY In many applications, variables of interest are marks of the endpoint which are not observed when the survival time is censored. This paper focuses on nonparametric estimation of the joint distribution and summaries of survival time and mark variables. We establish a representation of the joint distribution function through the cumulative markspecific hazard function, which is analogous to the product integral representation of univariate survival function. We…

非参数反卷积的保序逆估计量AI 解读

A new nonparametric estimation procedure is introduced for the distribution function in a class of deconvolution problems, where the convolution density has one discontinuity. The estimator is shown to be consistent and its cube root asymptotic distribution theory is established. Known results on the minimax risk for the estimation problem indicate the estimator to be efficient.

经验鞍点与自助法尾部近似的小相对误差概率界AI 解读

To obtain test probabilities based on empirical approximations to the distribution of a Studentized function of a mean, we need the approximations to be accurate with sufficiently high probability. In particular, when these test probabilities are small it is best to consider relative errors. Here we show that in the case of univariate standardized means and in the general case of tests based on smooth functions of means, the empirical approximations have asymptotically small…

多个回归函数的非参数比较：精确与渐近理论AI 解读

A new test is proposed for the comparison of two regression curves $f$ and $g$. We prove an asymptotic normal law under fixed alternatives which can be applied for power calculations, for constructing confidence regions and for testing precise hypotheses of a weighted $L_2$ distance between $f$ and $g$ . In particular, the problem of nonequal sample sizes is treated, which is related to a peculiar formula of the area between two step functions. These results are extended in…

多元模型中单侧备择的方向性检验AI 解读

Consider one-sided testing problems for a multivariate exponential family model. Through conditioning or other considerations, the problem oftentimes reduces to testing a null hypothesis that the natural parameter is a zero vector against the alternative that the natural parameter lies in a closed convex cone $\mathscr{C}$. The problems include testing homogeneity of parameters, testing independence in contingency tables, testing stochastic ordering of distributions and many…

利用时空数据估计随机过程的积分AI 解读

Consider a space–time stochastic process $Z_ t(x)=S(x) + \xi_t(x)$ where $S(x)$ is a signal process defined on $\mathbb{R}^d$ and $\xi_t(x)$ represents measurement errors at time $t$. For a known measurable function $v(x)$ on $\mathbb{R}^d$ and a fixed cube $ D\subset \mathbb{R}^d$, this paper proposes a linear estimator for the stochastic integral $\int_D v(x)S(x)dx$ based on space–time observations $\{Z_t(x_i); i = 1,\ldots,n; t=1,\ldots,T\}$. Under mild conditions, the…

有限半参数混合模型中广义Pólya urn方案的指数后验一致性AI 解读

Advances in Markov chain Monte Carlo MCMC methods now make it computationally feasible and relatively straightforward to apply the Dirichlet process prior in a wide range of Bayesian nonparametric problems. The feasibility of these methods rests heavily on the fact that the MCMC approach avoids direct sampling of the Dirichlet process and is instead based on sampling the finite-dimensional posterior which is obtained from marginalizing out the process. In application, it is…

Gibbs 采样器的信息界AI 解读

If we wish to estimate efficiently the expectation of an arbitrary function on the basis of the output of a Gibbs sampler, which is better: deterministic or random sweep? In each case we calculate the asymptotic variance of the empirical estimator, the average of the function over the output, and determine the minimal asymptotic variance for estimators that use no information about the underlying distribution. The empirical estimator has noticeably smaller variance for…

多维均值泛函的贝叶斯自助法可信集AI 解读

This paper shows that the Bayesian bootstrap (BB) distribution of a multidimensional mean functional based on i.i.d. observations has a strongly unimodal Lebesgue density provided the convex hull of the data has a nonempty interior. This result is then used to construct the finite sample BB credible sets. The influence of an outlier on these credible sets is studied in detail and a comparison is made with the empirical likelihood ratio confidence sets in this context.

最大似然先验AI 解读

Consider an estimate $\theta^*$ of a parameter $\theta$ based on repeated observations from a family of densities $f_\theta$ evaluated by the Kullback–Leibler loss function $K(\theta, \theta^*) = \int \log(f_\theta/f_{\theta^*})f_\theta$. The maximum likelihood prior density, if it exists, is the density for which the corresponding Bayes estimate is asymptotically negligibly different from the maximum likelihood estimate. The Bayes estimate corresponding to the maximum…

多元分布离散度矩阵的极小极大偏差稳健估计AI 解读

Maronna defines affine equivariant $M$-estimators for multivariate location and scatter. They are particularly suited for estimating the pseudo-covariance or scatter matrix of an elliptical population. By defining the bias of a dispersion matrix properly, we consider the maximum bias of an $M$-estimator over an $\varepsilon$ -neighborhood of the underlying elliptical distribution (location known). We find that Tyler’s estimator minimizes the maximum bias.

This paper proposes an Augmented Dickey-Fuller (ADF) coefficient test for detecting the presence of a unit root in autoregressive moving average (ARMA) models of unknown order. Although the limit distribution of the coefficient estimate depends on nuisance parameters, a simple transformation can be applied to eliminate the nuisance parameter asymptotically, providing an ADF coefficient test for this case. When the time series has an unknown deterministic trend, we propose a…

自回归模型中单位根检验的分布近似AI 解读

The present work applies saddlepoint approximation to calculate the left-hand tail of the distribution of the unit root t test and an asymptotic equivalent test under the null hypothesis of a unit root. (This is the tail of interest when testing against a stationary alternative.) The saddlepoint equation is solved numerically. Distribution approximations are obtained both in the asymptotic and finite-sample cases. In the finite-sample case, two slightly different methods are…